Remote Sensing Lab.
Remote Sensing Lab was established in the Geomatics Engineering department in 2005 to provide students with up-to-date knowledge on “Mapping with Remote Sensing Technologies and Applications”. Remote Sensing Lab helps students have a deeper understanding and a broader horizon to the professional life. With this hands-on experience, the lab also enables students to explore the connection between mapping practices and environmental monitoring.
Hands-on learning in the lab spans a broad range of geoscience and remote sensing topics with laser scan, hyperspectral and radar imaging data.
Lectures :
Graduate | Code | Course Name |
GEO505
| Data Processing Meth. and Syst. in Rem. Sen. |
GEO510E
| Environ. Mod. with GIS and Remote Sensing |
GEO520
| Risk Analyses with Remote Sensing |
GEO521E
| Data Acquisition Systems in Remote Sensing |
GEO602
| Disaster Manage. with GIS and Remote Sensing |
GEO604
| Hyperspect. and Lidar Data Anal. in Geom. Eng. |
GEO608
| Radar and Microwave Remote Sensing |
GEO619E
| Quantitative Remote Sensing |
GEO621E
| Sensor Integration and Data Fusion |
GEO526E
| Mapping with Remotely Sensed Data |
UAH525E
| Principles of Remote Sensing |
Recent Publications :
@ARTICLE{Sekertekin20161,
author={Sekertekin, A.a b and Kutoglu, S.H.a and Kaya, S.c },
title={Evaluation of spatio-temporal variability in Land Surface Temperature: A case study of Zonguldak, Turkey},
journal={Environmental Monitoring and Assessment},
year={2016},
volume={188},
number={1},
pages={1-15},
doi={10.1007/s10661-015-5032-2},
art_number={30},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84950322189&partnerID=40&md5=9597e6a52662248c399a80a6b40fcaf1},
affiliation={Department of Geomatics Engineering, Bulent Ecevit University, Zonguldak, Turkey; Department of Geomatics Engineering, Cukurova University, Adana, Turkey; Department of Geomatics Engineering, Istanbul Technical University, Istanbul, Turkey},
abstract={The aim of this study is to analyze spatio-temporal variability in Land Surface Temperature (LST) in and around the city of Zonguldak as a result of the growing urbanization and industrialization during the last decade. Three Landsat 5 data and one Landsat 8 data acquired on different dates were exploited in acquiring LST maps utilizing mono-window algorithm. The outcomes obtained from this study indicate that there exists a significant temperature rise in the region for the time period between 1986 and 2015. Some cross sections were selected in order to examine the relationship between the land use and LST changes in more detail. The mean LST difference between 1986 and 2015 in ERDEMIR iron and steel plant (6.8 °C), forestland (3 °C), city and town centers (4.2 °C), municipal rubbish tip (−3.9 °C), coal dump site (12.2 °C), and power plants’ region (7 °C) were presented. In addition, the results indicated that the mean LST difference between forestland and city centers was approximately 5 °C, and the difference between forestland and industrial enterprises was almost 8 °C for all years. Spatio-temporal variability in LST in Zonguldak was examined in that study and due to the increase in LST, policy makers and urban planners should consider LST and urban heat island parameters for sustainable development. © 2015, Springer International Publishing Switzerland.},
author_keywords={Land Surface Temperature (LST); Landsat; Mono-window algorithm; Spatio-temporal variability; Zonguldak},
document_type={Article},
source={Scopus},
}
@ARTICLE{Erten20151501,
author={Erten, E.a and Rossi, C.b and Yüzügüllü, O.c },
title={Polarization Impact in TanDEM-X Data over Vertical-Oriented Vegetation: The Paddy-Rice Case Study},
journal={IEEE Geoscience and Remote Sensing Letters},
year={2015},
volume={12},
number={7},
pages={1501-1505},
doi={10.1109/LGRS.2015.2410339},
art_number={7063930},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84933505685&partnerID=40&md5=96dd50a2c7921d4b4e71e497747cd5b5},
affiliation={Department of Geomatics Engineering, Istanbul Technical University, Istanbul, Turkey; Remote Sensing Technology Institute, German Aerospace Center, Wessling, Germany; Institute of Environmental Engineering, Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland},
abstract={It has been recently shown that the TanDEM-X mission is capable of tracking the plant growth of rice paddies. The precision of the elevation measure depends on the physical interaction between the synthetic aperture radar (SAR) signal and the canopy. In this letter, this interaction is studied by considering the signal polarization. In particular, the vertical and horizontal wave polarizations are compared, and their performance in the temporal mapping of the crop height is analyzed. The temporal elevation difference analysis shows a monotonically increasing trend within the reproductive stage of the canopy, with maximum height discrepancies between polarizations of about 9 cm. From an operational point of view of InSAR-based vegetation height measurements, this letter demonstrates that the oriented structure of the canopy shall be considered not only in polarimetric InSAR studies but also in the interpretation of bistatic spaceborne interferometric elevation models. © 2004-2012 IEEE.},
author_keywords={Agriculture; copolar phase difference (CPD); polarimetry; synthetic aperture radar (SAR); TanDEM-X; X-Band},
document_type={Article},
source={Scopus},
}
@Article{Bozkaya2015,
author="Bozkaya, A. Gonca and Balcik, Filiz Bektas and Goksel, Cigdem and Esbah, Hayriye",
title="Forecasting land-cover growth using remotely sensed data: a case study of the Igneada protection area in Turkey",
journal="Environmental Monitoring and Assessment",
year="2015",
volume="187",
number="3",
pages="1--18",
abstract="Human activities in many parts of the world have greatly affected natural areas. Therefore, monitoring and forecasting of land-cover changes are important components for sustainable utilization, conservation, and development of these areas. This research has been conducted on Igneada, a legally protected area on the northwest coast of Turkey, which is famous for its unique, mangrove forests. The main focus of this study was to apply a land use and cover model that could quantitatively and graphically present the changes and its impacts on Igneada landscapes in the future. In this study, a Markov chain-based, stochastic Markov model and cellular automata Markov model were used. These models were calibrated using a time series of developed areas derived from Landsat Thematic Mapper (TM) imagery between 1990 and 2010 that also projected future growth to 2030. The results showed that CA Markov yielded reliable information better than St. Markov model. The findings displayed constant but overall slight increase of settlement and forest cover, and slight decrease of agricultural lands. However, even the slightest unsustainable change can put a significant pressure on the sensitive ecosystems of Igneada. Therefore, the management of the protected area should not only focus on the landscape composition but also pay attention to landscape configuration.",
issn="1573-2959",
doi="10.1007/s10661-015-4322-z",
url="http://dx.doi.org/10.1007/s10661-015-4322-z"
}
@ARTICLE{Basaran201582,
author={Basaran, S.T.a and Dogru, A.O.b and Balcik, F.B.b and Ulugtekin, N.N.b and Goksel, C.b and Sozen, S.a },
title={Assessment of renewable energy potential and policy in Turkey - Toward the acquisition period in European Union},
journal={Environmental Science and Policy},
year={2015},
volume={46},
pages={82-94},
doi={10.1016/j.envsci.2014.08.016},
note={cited By 1},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84918830594&partnerID=40&md5=5a32e7ecf16b2de6b64fedd09eed3ebe},
affiliation={Faculty of Civil Engineering, Environmental Engineering Department, Istanbul Technical University, Maslak, Istanbul, Turkey; Faculty of Civil Engineering, Geomatics Engineering Department, Istanbul Technical University, Maslak, Istanbul, Turkey},
abstract={This paper aims to assess the renewable energy capacity of Turkey in order to consider main priorities in the energy policy of Turkey. In this paper, renewable energy potential and regulatory conditions are discussed in Turkey in comparison with European Union. The results of the study implemented within the framework of EnviroGRIDS project indicated a promising yet very susceptible future for the implementation of renewable energy power plants in Turkey. The forecasts have shown that the solar power potential utilization is becoming more significant after 2020. The projections for 2050 indicate that electricity consumption from small and medium renewable energy sources including solar and wind will constitute 15% of the total, whereas the solar thermal will constitute around 16%. Geothermal and other renewables will remain around 3%. According to the high demand scenario, in 2050 the share of hydropower in overall electricity generation will be 12%, followed by solar power at 7% and wind power at 3%. Additionally, renewable energy policy and regulations in Turkey and in EU are overviewed in this study. On the contrary to EU, the constant feed-in tariff amount does not consider capital investments of specific energy sources in Turkey that brings disadvantage to the implementation. However, new regulations published and currently applied should be accepted as milestones in acquisition period of Turkey in EU. © 2014 Elsevier Ltd.},
author_keywords={Energy policy; Energy potential; Renewable energy; Renewable sources},
document_type={Article},
source={Scopus},
}
@ARTICLE{Rossi2015900,
author={Rossi, C.a and Erten, E.b },
title={Paddy-rice monitoring using tan DEM-X},
journal={IEEE Transactions on Geoscience and Remote Sensing},
year={2015},
volume={53},
number={2},
pages={900-910},
doi={10.1109/TGRS.2014.2330377},
art_number={6868225},
note={cited By 5},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84906313833&partnerID=40&md5=bf1bd264b6534914619a6ab49d21d87b},
affiliation={Remote Sensing Technology Institute, German Aerospace Center (DLR), D-82234 Oberpfaffenhofen, Germany; Department of Geomatics Engineering, Istanbul Technical University, Istanbul 34469, Turkey},
abstract={This paper evaluates the potential of spaceborne bistatic interferometric synthetic aperture radar images for the monitoring of biophysical variables in wetlands, with a special interest on paddy rice. The assessment is made during the rice cultivation period, from transplanting to harvesting time (May to October) for fields around Gala lake (Turkey), one of the largest and most productive paddy rice planting area in the country. Detailed ground truth measurements describing biophysical parameters are collected in a dedicated campaign. A stack of 16 dual-pol TanDEM-X images is used for the generation of 32 digital elevation models (DEMs) over the studied area. The quality of the data allows the use of the interferometric phase as a state variable capable to estimate crop heights for almost all the growing stages. The early vegetative rice stage, which is characterized by flooded fields, cannot be represented by the interferometric phase due to a low signal-to-noise ratio but can be easily detected by amplitude and interferometric coherence thresholding. A study on the impact of the polarization in the signal backscatter is also performed. An analysis of the differences between HH and VV DEMs shows the varying signal penetration for the two polarizations at different growing stages. The validation with reference data demonstrates the capability to establish a direct relationship between interferometric phase and rice growth. The very high coherence of TanDEM-X data yields elevation estimates with root-mean-square error in a decimetric level, supporting temporal change analysis on a field-by-field basis. © 2014 IEEE.},
author_keywords={Agriculture; digital elevation model (DEM); paddy-rice monitoring; polarimetry; synthetic aperture radar (SAR) interferometry; TanDEM-X},
document_type={Article},
source={Scopus},
}
@CONFERENCE{Demir2015,
author={Demir, M.A.a and Sertel, E.b and Musaoglu, N.b and Ormeci, C.b },
title={Accuracy assessment of radargrammetric DEMs derived from RADARSAT-2 ultrafine mode},
journal={International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives},
year={2015},
volume={38},
number={1W17},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84923809305&partnerID=40&md5=d0abc3163c02d689329c81bf25cc8f7e},
affiliation={ITU, Informatics Institute, Satellite Communication and Remote Sensing Programme, Maslak Istanbul, Turkey; ITU, Geomatics Dept., Remote Sensing Div., Maslak Istanbul, Turkey},
abstract={The aim of this study is to investigate the accuracy and reliability of radargrammetric DEMs generated from RADARSAT-2 stereo pairs. Two ultrafine mode images U7 and U26 were acquired over an area in Istanbul from descending orbit, HH polarization, in SGF format. U7 and U26 were taken on August 2, 2009 and July 30, 2009 with view angles of 34.00 - 35.30 and 48.50 - 49.50 at the near-far edges, respectively. The main project steps for DEM generation were; 1) Stereo model set up; 2) creating epipolar images; 3) image matching; 4) DEM editing. In order to set up the stereo model, ground control points (GCPs) were obtained from IKONOS image for planimetric information. Also 1:5000 scaled topographic maps were used for elevation information. After the setting up the stereo model with Toutin's 3D physical model developed at the Canada Centre for Remote Sensing (CCRS) and rational function model, radargrammetric DEMs were generated. Root mean square errors (RMSEs) of both GCPs and Independent Check Points (ICPs) were analyzed to evaulate the planimetric and elevation accuracy. Several transects were selected and elevation values obtained from Toutin's and rational function models were statistically compared with a reference DEM. Generated DEMs were also visually compared with Global Digital Elevation Model (GDEM).},
author_keywords={Accuracy; GDEM; Radargrammetric DEM; RADARSAT-2; Rational function model; Stereo SAR},
document_type={Conference Paper},
source={Scopus},
}
@ARTICLE{Yuzugullu20151218,
author={Yuzugullu, O.a and Erten, E.b and Hajnsek, I.a c },
title={Rice Growth Monitoring by Means of X-Band Co-polar SAR: Feature Clustering and BBCH Scale},
journal={IEEE Geoscience and Remote Sensing Letters},
year={2015},
volume={12},
number={6},
pages={1218-1222},
doi={10.1109/LGRS.2015.2388953},
art_number={7038185},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84924953491&partnerID=40&md5=7c882fa4cb76deb4a1855ec090d8f694},
affiliation={Institute of Environmental Engineering, ETH Zurich, Zurich, Switzerland; Istanbul Technical University (ITU), Geomatics Engineering, Istanbul, Turkey; Microwaves and Radar Institute, German Aerospace Center (DLR), Wessling, Germany},
abstract={Precision agriculture research, which aims to monitor agricultural fields and to manage agricultural practice by considering overall environmental impacts, has gained momentum with the recent improvements in the remote sensing area. The objective of this letter, as a part of precision farming, is to implement Biologische Bundesanstalt, Bundessortenamt und CHemische Industrie (BBCH) scale assignment in plant growth monitoring by means of SAR. The proposed approach copes with structural heterogeneity in agricultural fields by grouping together similar morphologies. For this, densely cultivated paddy rice fields are analyzed using TerraSAR-X (TSX) co-polar SAR data. For generating structurally similar groups, K-means clustering is used in a polarimetric feature vector space, which is composed of backscattering intensities and polarimetric phase differences. This step is followed by a preliminary classification approach based on the temporal separability of the explanatory parameters. In the last step of the proposed methodology, assigned classes are updated based on the biological principles that are followed in rice cultivation. This letter provides the results of the proposed algorithm and compares them to the standard threshold-based approach in two independent agricultural areas. The results show the superiority of the feature-clustering-based classification compared with the standard approach in handling field heterogeneity. © 2015 IEEE.},
author_keywords={Agriculture; Biologische Bundesanstalt, Bundessortenamt und CHemische Industrie (BBCH) scale; feature-clustering; heterogeneity; monitoring; polarimetry; rice phenology; synthetic aperture radar (SAR); X-band},
document_type={Article},
source={Scopus},
}
@ARTICLE{Musaoglu201554,
author={Musaoglu, N.a and Tanik, A.b and Dikerler, T.c and Buhur, S.c },
title={Use of remote sensing and geographic information systems in the determination of high-risk areas regarding marine traffic in the Istanbul Strait},
journal={Environmental Hazards},
year={2015},
volume={14},
number={1},
pages={54-73},
doi={10.1080/17477891.2014.986042},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84919456539&partnerID=40&md5=4ba88e91ab4da3eea7ff62e13a4d25b0},
affiliation={Civil Engineering Faculty, Geomatics Engineering Department, Istanbul Technical University, Maslak, Istanbul, Turkey; Civil Engineering Faculty, Environmental Engineering Department, Istanbul Technical University, Maslak, Istanbul, Turkey; Graduate School of Science, Engineering and Technology, Istanbul Technical University, Maslak, Istanbul, Turkey},
abstract={Istanbul Strait, Bosphorus, is one of the important waterways of the world due to its combination of natural beauty, human resources, and the high number of oil-carrying tankers passing through it. A considerable increase in the number of vessels over the past decade has indicated the high potential for oil spillage and fire hazards. This study aims to determine the coastal areas that are under an oil spill/fire/explosion risk in the Istanbul Strait by using geoinformatics. Remote sensing technology, providing relatively quick and low-cost analysis of large areas, is used for classifying the shoreline and land-use activities in the fore-scene and back-scene zones followed by assigning risk scores to various GIS data layers and suitability evaluation based on the weight of each score. The risk components are prioritized and layers are allocated according to their risk scores. Major components that classify risk-posing areas are accident likelihood, number of historical assets, human-use resources, population, and lack of critical facilities. Segment-wise risk levels that resulted in comparatively higher scores indicate the vulnerable areas along the Strait to draw the attention of the society and the decision-makers who are responsible for the policy implications. The study acts as a guideline for developing coastal management strategies and implementing corresponding human policies. © 2014 Taylor & Francis.},
author_keywords={Coastal zone management; developing countries; environmental impact; oceanic hazard; risk awareness},
document_type={Article},
source={Scopus},
}
@ARTICLE{Ozcan2014289,
author={Ozcan, O.a and Musaoglu, N.b and Ustundag, B.c },
title={Crop water requirement estimation of wheat cultivated fields by remote sensing and GIS},
journal={Journal of Food, Agriculture and Environment},
year={2014},
volume={12},
number={1},
pages={289-293},
note={cited By 1},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84896703239&partnerID=40&md5=c5860625d6f91422d1437e52b147ebea},
affiliation={ITU, Application and Research Center for Satellite Communications and Remote Sensing, 34469, Maslak, Istanbul, Turkey; ITU, Department of Geomatics Engineering, 34469, Maslak, Istanbul, Turkey; ITU, Department of Computer Engineering, 34469, Maslak, Istanbul, Turkey},
abstract={In water resources and hydrological studies, transpiration from plants and evaporation from the underlying soil is an important factor for estimating irrigation water requirements when planning irrigation systems, especially in arid and semi-arid conditions of South-Eastern Anatolia in Turkey. The aim of the study is to investigate the water requirement for wheat fields cultivated on different soil types by estimating the actual crop evapotranspiration of wheat crop via Remote Sensing (RS) and Geographical Information System (GIS) techniques. The data used in this study was obtained from selected real-time monitoring areas for wheat cultivated fields located on the area of South-Eastern Anatolia Region. SPOT 5 satellite images that were acquired at the growing season of wheat crop were used to determine the Normalized Difference Vegetation Index (NDVI), Modified Soil Adjusted Vegetation Index (MSAVI) and to generate the crop coefficients (KC) for each month of wheat crop season. As a result, the MSAVI values were found to have a high correlation with KC values (R2 ~ 0.89) for both selected wheat cultivated fields with different soil types in Hilvan and Akcakale districts of Sanliurfa province. The pixel-wise KC values of these fields were computed from corresponding MSAVI maps by using the developed empirical regression relationships of MSAVI. These KC values of wheat crop from different fields were generated by using their correlation with remote sensing based NDVI and MSAVI values. Preliminary results have shown that water demands may vary for cultivated wheat fields on different soil types having different land use capability classes.},
author_keywords={Crop coefficient; Evapotranspiration; Real-time monitoring stations; Remote sensing; SPOT 5},
document_type={Article},
source={Scopus},
}
@ARTICLE{Alganci20148,
author={Alganci, U.a and Ozdogan, M.b and Sertel, E.c and Ormeci, C.c },
title={Estimating maize and cotton yield in southeastern Turkey with integrated use of satellite images, meteorological data and digital photographs},
journal={Field Crops Research},
year={2014},
volume={157},
pages={8-19},
doi={10.1016/j.fcr.2013.12.006},
note={cited By 2},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84891059193&partnerID=40&md5=03484a439e323549832bfd17fce45141},
affiliation={Center for Satellite Communication and Remote Sensing (CSCRS), Istanbul Technical University, ITU Ayazaga Campus, 34469 Maslak, Istanbul, Turkey; Center for Sustainability and the Global Environment (SAGE), University of Wisconsin - Madison, 1710 University Avenue, Madison, WI 53726, United States; Civil Engineering Faculty - Geomatics Engineering Division, Istanbul Technical University, ITU Ayazaga Campus, 34469 Maslak, Istanbul, Turkey},
abstract={This study focuses on yield estimates of planted areas of cotton and maize in southeastern Turkey. It integrates multi-temporal satellite images, daily digital photographs of cultivated parcels, and daily meteorological data. Our research produced vegetation cover fraction (VF) estimates from digital photos and defined relationships between this information and the spectral vegetation index (VI) obtained from satellite images. Meteorological parameters limiting the light use efficiency of crops (LUE), such as temperature and vapor pressure deficit, were also calculated and incorporated into the yield estimation process. Results showed that the use of digital photo-based VF rather than the fraction of photosynthetically active radiation (fAPAR) in the LUE model provided the most accurate yield estimates. It produced less than 5 percent relative error in cotton and maize test parcels. In general, the VF-SVI relationship showed high linear correlation, with a range of 0.825-0.980 R2 in all test parcels. Crop specific regression equations derived from these relationships enabled yield estimates at the parcel level across the study area. When compared to statistical yield information at four districts, the remote sensing-based method proved to be reliable, with relative errors below 10 percent in most cases. Moreover, greenness index (GI) was also used in gross primary production (GPP) approximation, and yield estimates using this method also provided reasonable accuracy. Results also provided valuable information about the effects of region-specific meteorological conditions and crop management activities on yields. Finally, the higher yield estimation errors that result from the use of generic SVI-fAPAR equations in the literature indicate the need for local calibration of this relationship. © 2013 Elsevier B.V.},
author_keywords={Crop cover fraction; Digital photographs; Light use efficiency; Satellite images; Spectral vegetation index; Yield estimation},
document_type={Article},
source={Scopus},
}
@ARTICLE{BektaşBalçik2014859,
author={Bektaş Balçik, F.},
title={Determining the impact of urban components on land surface temperature of Istanbul by using remote sensing indices},
journal={Environmental Monitoring and Assessment},
year={2014},
volume={186},
number={2},
pages={859-872},
doi={10.1007/s10661-013-3427-5},
note={cited By 1},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84893710295&partnerID=40&md5=bbfb3bc81cff0c7df68dc61fc40d53b7},
affiliation={Civil Engineering Faculty, Geomatics Engineering, Istanbul Technical University, 34469 Maslak Istanbul, Turkey},
abstract={For the past 60 years, Istanbul has been experiencing an accelerated urban expansion. This urban expansion is leading to the replacement of natural surfaces by various artificial materials. This situation has a critical impact on the environment due to the alteration of heat energy balance. In this study, the effect upon the urban heat island (UHI) of Istanbul was analyzed using 2009 dated Landsat 5 Thematic Mapper (TM) data. An Index Based Built-up Index (IBI) was used to derive artificial surfaces in the study area. To produce the IBI index, Soil-Adjusted Vegetation Index, Normalized Difference Built-up Index, and Modified Normalized Difference Water Index were calculated. Land surface temperature (LST) distribution was derived from Landsat 5 TM images using a mono-window algorithm. In addition, 24 transects were selected, and different regression models were applied to explore the correlation between LST and IBI index. The results show that artificial surfaces have a positive exponential relationship with LST rather than a simple linear one. An ecological evaluation index of the region was calculated to explore the impact of both the vegetated land and the artificial surfaces on the UHI. Therefore, the quantitative relationship of urban components (artificial surfaces, vegetation, and water) and LST was examined using multivariate statistical analysis, and the correlation coefficient was obtained as 0.829. This suggested that the areas with a high rate of urbanization will accelerate the rise of LST and UHI in Istanbul. © 2013 Springer Science+Business Media Dordrecht.},
author_keywords={Index based built up index; Istanbul; Land surface temperature; Landsat 5 TM; Mono-window method},
document_type={Article},
source={Scopus},
}
@CONFERENCE{Cokgor2014607,
author={Cokgor, S. and Soufiani, S.J. and Aydar, U. and Kaya, S.},
title={Geosynthetic based scour protection around the slender pile under waves},
journal={International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM},
year={2014},
volume={2},
number={3},
pages={607-614},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84946572700&partnerID=40&md5=55be3c10acaf531e350a8f06d48bb86a},
affiliation={Istanbul Technical University, College of Civil Engineering, Turkey},
abstract={Conventional and geosynthetic scour protections around the slender pile under the waves were experimentally studied in the laboratory flume. One layer dumped stones was used for conventional protection. As a geosynthetic supported protection, geogrid wrapped one layer stones and geomembrane applications under the stone layer were used for protection around the pile. Experiments show that stones behave individual and turn, slide and roll through scour at the edge of protection at conventional random stone dump. Geogrid wrapped stone layer shows elastic behavior against edge scour and supplies better protection then classical way and geomembrane solution. Geomembrane which spreads under the stone layer also give better protection regarding classical way against edge scour although stones move over geomembrane and edges of membrane moves with waves. © 2014, SGEM. All Rights Reserved.},
author_keywords={Geogrid; Geomembrane; Scour; Scour protection; Slender pile; Waves},
document_type={Conference Paper},
source={Scopus},
}
@ARTICLE{Tok20141857,
author={Tok, E.a and Kaya, S.b },
title={Monitoring components of urban environment using vegetation-impervious-soil model and remotely sensed data},
journal={Journal of Environmental Protection and Ecology},
year={2014},
volume={15},
number={4},
pages={1857-1865},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84946840026&partnerID=40&md5=d5a97408f19bcce48f799e562802669c},
affiliation={Mimar Sinan Fine Arts University, Meclisi Mebusan Street, Salipazari, Istanbul, Turkey; Geomatics Engineering Department, Istanbul Technical University, Maslak, Istanbul, Turkey},
abstract={The Istanbul Metropolitan area, facing rapid - frequently uncontrolled - urbanisation, is the most bipolar urbanised city in Turkey. One of the main reasons of urbanisation is the lack of adequate legal enforcement on planning regulations that leads to illegal settlements and uncontrolled urban sprawl. This expansion is affected by physical, socio-economic, and demographic phenomena that influence the morphological patterns of the districts like Sultanbeyli, Kartal and Pendik that are identified as the most significant districts regarding rapid and uncontrolled growth between 1987-1997. This study mainly aimed to monitor spatial growth in these highly urbanised districts in the Istanbul Metropolitan Area through determining the urban characterisation or pattern via Vegetation-Impervious Area-Soil (V-I-S) components model using Landsat TM images belonging to years of 1987 and 1997. The urban movement and its trend in the study area have been analysed by two different methods to confirm their respective accuracies within the conceptual framework of the V-I-S model. Classified and unclassified images were used as model inputs. Maps were generated in four main components of urban land cover: vegetation, impervious area, soil, and water. The results of the V-I-S model applied to the districts were further evaluated and tested in terms of their effectiveness in identifying and measuring the urban ecosystem composition. The results showed that both methods were successful in the V-I-S modelling using Landsat 5 TM images for the analysis of the urban ecology. Unclassified image data indicated approximately similar values as those in the unsupervised classification data. In other words, method analysis presented positive coherent conclusions.},
author_keywords={human impacts; remote sensing; urban ecosystems.; urban pattern; V-I-S model},
document_type={Article},
source={Scopus},
}
@CONFERENCE{Erten20141017,
author={Erten, E.a and Rossi, C.b and Yuzugullu, O.c and Hajnsek, I.c },
title={Phenological growth stages of paddy rice according to the BBCH scale and SAR images},
journal={International Geoscience and Remote Sensing Symposium (IGARSS)},
year={2014},
pages={1017-1020},
doi={10.1109/IGARSS.2014.6946600},
art_number={6946600},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84911407904&partnerID=40&md5=9a488e2c0ce580e4618ace99fb9b868f},
affiliation={Faculty of Civil Engineering, Istanbul Technical University, Istanbul, Turkey; Institute of Remote Sensing Technology, German Aerospace Center, Oberpfaffenhofen, Germany; Institute of Environmental Engineering, ETH Zurich, Zurich, Switzerland},
abstract={Paddy rice is a staple food that feeds more than half of the world's population. As such, monitoring paddy rice with Synthetic Aperture Radar (SAR) image is a critical area of research. Many possible measures of rice growth as canopy height, LAI, biomass and etc. are considered in the previous works. Among them, canopy height is the most direct measurement and has direct relationship with growth rate. In this study, to monitor paddy rice fields canopy heights are estimated by SAR images containing phase and amplitude information. These two inherent properties of SAR images are examined to retrieve canopy height by a canopy scattering and by a differential interferometric method at X-band. Accuracy analysis showed that differential interferometric technique gives very precise results in terms of canopy height if the canopy is fresh. However, in the case of dry canopy layer, the X-band canopy backscattering model gives much more precise results than the interferometric method as the X-band radar signals penetrate more into canopy in dry case. Even though interferometric techniques do not give detailed information about the physical structure of the canopy as backscattering model do, in this work it is shown that they can be used in operational monitoring. © 2014 IEEE.},
author_keywords={Agriculture; Canopy height and density; SAR; TanDEM-X},
document_type={Conference Paper},
source={Scopus},
}
@CONFERENCE{Erten2014116,
author={Erten, E.a and Yuzugullu, O.b },
title={Observation of phenological changes by using dual polarization SAR data [Fenolojik deǧişimlerin ikili polarizasyonlu yar verileri ile incelenmesi]},
journal={2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings},
year={2014},
pages={116-119},
doi={10.1109/SIU.2014.6830179},
art_number={6830179},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84903787832&partnerID=40&md5=1d66718998d4eb90c61bda45689ff030},
affiliation={Geomatik Mühendisligi Bölümü, Istanbul Teknik Üniversitesi, Turkey; Earth Observation and Remote Sensing, ETH Zürih, Switzerland},
abstract={Remote sensing is actively used in observation of the nature. Synthetic aperture radar (SAR) systems are capable of obtaining physical based data under day/night and clear/cloudy sky situations. With sensitivity over the physical changes, they have importance in monitoring of agricultural areas. Paddy rice has been a widely used crop in the World, which requires wetland areas. In Turkey, it is mainly irrigated in Edirne and Samsun. With its importance in World's agricultural economy, researches regarding the precision farming of rice increased significantly, which includes remote sensing methods. Here, the effect of phenological changes during growth of rice over dual-pol SAR (phase + amplitude) data are discussed. Fields that are located in Ipsala (Edirne) are chosen as test-site. Ground measurements are conducted during May-September 2013. SAR data that are used to explain the physical changes, are obtained in horizontal-horizontal and vertical-vertical polarization configurations from TerraSAR-X (TSX) and TanDEM-X (TDX) satellites in 2012 and 2013. © 2014 IEEE.},
author_keywords={interferometry; polarimetry; SAR},
document_type={Conference Paper},
source={Scopus},
}
@CONFERENCE{Rossi2014958,
author={Rossi, C.a and Erten, E.b },
title={Generation of rice crops temporal change maps with differential TanDEM-x interferometry},
journal={International Geoscience and Remote Sensing Symposium (IGARSS)},
year={2014},
pages={958-961},
doi={10.1109/IGARSS.2014.6946585},
art_number={6946585},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84911423711&partnerID=40&md5=e1aa51cbf0f4f153772bde82925e693c},
affiliation={German Aerospace Center (DLR), Remote Sensing Technology Institute, Wessling, Germany; Istanbul Technical University (ITU), Geomatics Engineering, Istanbul, Turkey},
abstract={A strategy to evaluate rice plant growth from TanDEM-X data is assessed in this paper. Single fields are segmented exploiting their early vegetative stage, when they are flooded. Height is then extracted from the bistatic interferometric phase in a field-by-field basis and temporal change maps useful to production estimation are generated. The accuracy of the plant height estimation is in a decimetric level. © 2014 IEEE.},
author_keywords={DEM; InSAR; paddy rice; TanDEM-X},
document_type={Conference Paper},
source={Scopus},
}
@CONFERENCE{Marangoz2014,
author={Marangoz, M.a and Musaoglu, N.b },
title={Site selection for base stations based on a new method},
journal={ASPRS 2014 Annual Conference: Geospatial Power in Our Pockets, Co-Located with Joint Agency Commercial Imagery Evaluation Workshop, JACIE 2014},
year={2014},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84903979361&partnerID=40&md5=5d4d3dba539571e7a64ec811c09ea296},
affiliation={Istanbul Technical University, Institute of Informatics, 34469 Maslak, Istanbul, Turkey; Istanbul Technical University, Civil Engineering Faculty, Geomatic Engineering Department, 34469 Maslak, Istanbul, Turkey},
abstract={In mobile telecommunication systems (GSM/2G, EDGE/2.5G, UMTS/3G, LTE/4G ...), the planning of the location of the base station is key for uninterrupted communication. The major problem in achieving ideal signaling between mobile phones and base stations is inaccurate site selection due to the altitude of the region. In addition to altitude, there are many important parameters such as height of buildings and population density. If site selection is inaccurate and determined without reference to any previous parameters, the connection between mobile phones and base stations can be often interrupted and calls can drop. If old or new communication technologies have lots of problems such as inaccurate site selection, these should be fixed and regularly checked by optimization engineers. When a new technology is developed, firstly it should be applied to a trial area. After a period of study, results will indicate its suitability. After the region is determined, the next stage is determination of base station location depending on legal and expert opinion and carried out with site selection tools. When calculations are made to determine site locations, radio wave propagation (Okumura-Hata, Erceg-Greenstein, SUI, etc) should be simulated using by RF tools to make a coverage map. In this study we created a site selection tool to select sites before calculating the LTE coverage map in built up area for the Beykoz district of Istanbul.},
author_keywords={Base station; LTE coverage map; Site selection; Tool for site selection},
document_type={Conference Paper},
source={Scopus},
}
@CONFERENCE{Alganci201393,
author={Alganci, U.a and Sertel, E.b and Kaya, S.b and Ustundag, B.B.c },
title={A research on Agricultural Mapping Capabilities of the SPOT 6 satellite images},
journal={2013 2nd International Conference on Agro-Geoinformatics: Information for Sustainable Agriculture, Agro-Geoinformatics 2013},
year={2013},
pages={93-96},
doi={10.1109/Argo-Geoinformatics.2013.6621886},
art_number={6621886},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84888861639&partnerID=40&md5=70aed4b463ce3310a384a946ccb75031},
affiliation={Application and Research Center for Satellite Communication and Remote Sensing, Istanbul Technical University, Istanbul, Turkey; Civil Engineering Faculty, Geomatics Engineering Department, Istanbul Technical University, Istanbul, Turkey; Agricultural and Environmental Informatics Research Center, Istanbul Technical University, Istanbul, Turkey},
abstract={This study focused on crop type identification and area estimation of the cultivated parcels using images with 1.5m spatial resolution and 60km × 60km coverage from newly launched SPOT 6 satellite. A test site and a district in Sanliurfa Province, Southeastern Turkey were selected as study region where ground truth data was also available. After the geometric correction of SPOT 6 images; further image processing methods were applied. In the first step, a comparative analysis was performed at a test site to find out optimum parameters to be applied for this research. For this analysis, object based image classification (OBC) was applied to SPOT 6 image and feature extraction was performed from classification results to identify different parcels within the study area. Extracted features were compared to parcel vector database and accuracy metrics of parcel identification and area estimation was produced. In the second step, analysis was extended to district scale and classification OBC classification was performed for Suruc district of Sanliurfa. Accuracy assessment was performed with stratified random point selection for district scale classification results.},
author_keywords={Area estimation; Crop type identification; Object based classification; Parcel level analysis; SPOT6 satellite image},
document_type={Conference Paper},
source={Scopus},
}
@CONFERENCE{Senturk201361,
author={Senturk, S.a and Taşdemir, K.b and Kaya, S.c and Sertel, E.c },
title={Unsupervised classification of vineyard parcels using SPOT5 images by utilizing spectral and textural features},
journal={2013 2nd International Conference on Agro-Geoinformatics: Information for Sustainable Agriculture, Agro-Geoinformatics 2013},
year={2013},
pages={61-65},
doi={10.1109/Argo-Geoinformatics.2013.6621880},
art_number={6621880},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84888858988&partnerID=40&md5=f0e1b64c80966e7cc20b1f2431c92e89},
affiliation={Satellite Comm. and Remote Sensing, Istanbul Technical University, Ayazaga, Istanbul, Turkey; Department of Computer Engineering, Antalya International University, Döşemealtl, 07190, Antalya, Turkey; Department of Geomatics Engineering, Istanbul Technical University, Ayazaǧa Istanbul, Turkey},
abstract={In order to support agricultural management of vineyards, high spatial resolution remote sensing images (less than 1 meter) enables textural representation of their periodic plantation pattern which helps for delineation. Even though this texture analysis may provide highly accurate delineation of vineyards, it may be infeasible at national scale, due to the computational complexity of texture extraction. In addition, particularly for Turkey, plantation practices for vineyards deviate from common periodic pattern, which can make those textures insufficient. In this study, we used SPOTS images to explore their capabilities for delineation of vineyard parcels, without any a priori parcel information. As the inter-row distance and the spacing between the individual vine plants are less than the used 2.5m panchromatic, which is generated from 2×5m scenes (nadir) for panchromatic and 10m (nadir) spatial resolutions for multi-spectral bands, currently used periodicity based (Fourier) texture analysis may be vague. Therefore, we used Gabor textures (with different scales and directions) to define texture characteristics at this relatively coarse resolution, and we integrated these textures with image bands (visible, near infrared and shortwave infrared) which hold the ability to spectrally distinguish the vine plants from the remaining crops. For the vineyards parcels recognition, we classified the extracted features by a recent hierarchical clustering method based on self-organizing neural networks. We compared the performance of this proposed method to the object-based image analysis (by eCognition) which depends on multi-scale image segmentation and user-defined decision rules with corresponding thresholds.},
author_keywords={CONN linkage; Gabor textures; ORI; Self-organizing maps; SPOTS; Vineyards mapping},
document_type={Conference Paper},
source={Scopus},
}
@CONFERENCE{Senturk201366,
author={Senturk, S.a and Sertel, E.b and Kaya, S.b },
title={Vineyards mapping using object based analysis},
journal={2013 2nd International Conference on Agro-Geoinformatics: Information for Sustainable Agriculture, Agro-Geoinformatics 2013},
year={2013},
pages={66-70},
doi={10.1109/Argo-Geoinformatics.2013.6621881},
art_number={6621881},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84888858993&partnerID=40&md5=8519a45c6bb0e0a76bb9e58e8d5cee9b},
affiliation={Satellite Comm. and Remote Sensing, Istanbul Technical University, Istanbul, Turkey; Geomatics Engineering, Istanbul Technical University, Istanbul, Turkey},
abstract={Precise vineyards digital plotting for grape-growing regions can produce thematic maps, which subsequently could be employed within Geographical Information Systems (GIS) as a part of the formation of national Vineyard Information System (VIS) in Turkey. This study proposed vineyards parcels delineation approach using sub-meter Worlview-2 (WV2) VHR satellite images. The WV2 satellite data fles incorporate featured 8 (eight) multi-spectral and one panchromatic bands. They were used to differentiate and label the spatial distribution of viticulture practices in Tekirdag Province, Eastern Thrace region, which is one of the areas with highest efficiency for grape-growing practices. The applied classification process employed object-based image analysis method (OBIA, using eCognition). It is a technique that aggregates neighboring pixels into groups acknowledged as image objects. These object primitives convey similar values for several variables according to predefined spatial likelihood and homogeneity measures. Spectral, textural, customized vegetation indices, various band ratios, and other object features were integrated into the object-based image analysis with aim to produce consistent classification results. WV2 pan-sharpened images of 0.5m spatial resolution were taken as the input data. The validation of the created land cover mapping was assessed using formerly produced labeled maps from field work. The plantations with linear, straight row vineyards planting were almost completely mapped, while the allocation accuracies for the other planting types were comparatively lower. Nonetheless, these accuracy results for the dissimilar vineyards planting routines put forward that OBIA can support further in vineyards mapping for wine producers and classification of viticulture practices in general.},
author_keywords={OBIA; Precision farming; Vineyards mapping; WorldView-2},
document_type={Conference Paper},
source={Scopus},
}
@ARTICLE{Alganci20131053,
author={Alganci, U.a and Sertel, E.b and Ozdogan, M.c and Ormeci, C.b },
title={Parcel-level identification of crop types using different classification algorithms and multi-resolution imagery in Southeastern Turkey},
journal={Photogrammetric Engineering and Remote Sensing},
year={2013},
volume={79},
number={11},
pages={1053-1065},
doi={10.14358/PERS.79.11.1053},
note={cited By 5},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84887290816&partnerID=40&md5=abfeea9ae395450cddc5776cf26870c3},
affiliation={Center for Satellite Communication and Remote Sensing (CSCRS), Istanbul Technical University, ITU Ayazaga Campus 34469 Maslak, Istanbul, Turkey; Istanbul Technical University, ITU Ayazaga Campus 34469 Maslak, Istanbul, Turkey; Center for Sustainability and the Global Environment (SAGE), University of Wisconsin, 1710 University Avenue, Madison, WI 53726, United States},
abstract={This research investigates the accuracy of pixel- and object-based classification techniques across varying spatial resolutions to identify crop types at parcel level and estimate the area at six test sites to find the optimum data source for the identification of crop parcels. Multi-sensor data with spatial resolutions of 2.5 m, 5 m and 10 m from SPOT5 and 30 m from Landsat-5 TM were used. Maximum Likelihood (ML), Spectral Angle Mapper (SAM), and Support Vector Machines (SVM) were used as pixel-based methods in addition to object-based image classification (OBC). Post-classification methods were applied to the output of pixel-based classification to minimize the noise effects and heterogeneity within the agricultural parcels. In addition, processing-time performance of the algorithms was evaluated for the test sites and district scale classification. OBC results provided comparatively the best performance for both parcel identification and area estimation at 10 m and finer spatial resolution levels. SVM followed OBC at 2.5 m and 5 m resolutions but accuracies decreased dramatically with coarser resolutions. ML and SAM results were worse up to 30 m resolution for both crop type identification and area estimation. In general, parcel identification efficiency was strongly correlated with spatial resolution while the classification algorithm was a more effective factor than spatial resolution for area estimation accuracy. Results also provided an opportunity to discuss the effects of image resolution and the classification algorithm independent factors such as parcel size, spatial distribution of crop types and crop patterns. © 2013 American Society for Photogrammetry and Remote Sensing.},
document_type={Article},
source={Scopus},
}
@ARTICLE{Erten20133319,
author={Erten, E.},
title={Glacier velocity estimation by means of a polarimetric similarity measure},
journal={IEEE Transactions on Geoscience and Remote Sensing},
year={2013},
volume={51},
number={6},
pages={3319-3327},
doi={10.1109/TGRS.2012.2219873},
art_number={6410023},
note={cited By 3},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84878146046&partnerID=40&md5=e242b4b966167c048d343a1cfc6f081d},
affiliation={Department of Geomatics Engineering, Faculty of Civil Engineering, Istanbul Technical University (ITU), 34469 Istanbul, Turkey},
abstract={The contribution of polarimetric synthetic aperture radar (PolSAR) images compared with that of single-channel SAR images in terms of temporal scene characterization has been found and described to add valuable information in the literature. However, despite a number of recent studies focusing on single-polarized glacier monitoring, the potential of polarimetry to estimate the surface velocity of glaciers has not been explored due to the complex mechanism of polarization through glacier/snow. In this paper, a new approach to the problem of monitoring glacier surface velocity is proposed by means of temporal PolSAR images, using a basic concept from information theory, i.e., mutual information (MI). The proposed polarimetric tracking method applies the MI to measure the statistical dependence between temporal polarimetric images, which is assumed to be maximum if the images are geometrically aligned. Since the proposed polarimetric tracking method is very powerful and general, it can be implemented into any kind of multivariate remote sensing data such as multichannel optical and single-channel SAR images. The proposed polarimetric tracking is then used to retrieve the surface velocity of the Aletsch Glacier in Switzerland and the Inylchek Glacier in Kyrgyzstan with two different SAR sensors: the Experimental SAR airborne L-band (fully polarimetric) and Envisat C-band (single-polarized) systems, respectively. The effect of the number of channels (polarimetry) into tracking investigations demonstrated that the presence of snow, as expected, affects the location of the phase center in different polarization and frequency channels, as for the glacier tracking with temporal HH compared to temporal VV channels. In this paper, it is shown how it is possible to optimize these two different contributions, considering the multichannel SAR statistics. © 1980-2012 IEEE.},
author_keywords={Cryosphere; glacier monitoring; mutual information (MI); polarimetry; synthetic aperture radar (SAR)},
document_type={Article},
source={Scopus},
}
@ARTICLE{Chesnokova2013303,
author={Chesnokova, O.a and Erten, E.b },
title={A comparison between coherent and incoherent similarity measures in terms of crop inventory},
journal={IEEE Geoscience and Remote Sensing Letters},
year={2013},
volume={10},
number={2},
pages={303-307},
doi={10.1109/LGRS.2012.2203783},
art_number={6247462},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84869491679&partnerID=40&md5=c30a69c41d76197b697080236b215545},
affiliation={Department of Earth Observation and Remote Sensing, Institute of Environmental Engineering, ETH Zurich, CH-8093 Zurich, Switzerland; Department of Geomatic Engineering, Istanbul Technical University, 34469 Istanbul, Turkey},
abstract={Polarimetric synthetic aperture radar (PolSAR) images are widely used for agricultural fields monitoring and change detection applications due to their all-weather acquisition possibilities and inherent properties including phase and amplitude information. The techniques used for such temporal applications can be cast in two groups: polarimetric (incoherent) and polarimetric- interferometric ( coherent), being represented in this letter by the Kullback-Leibler distance and the mutual information, respectively. The goal of this letter is to characterize these two kinds of different information sources in terms of ground measurement parameters of the agricultural fields and to figure out the relationship between temporal trends of the similarity measures versus temporal trends of the physical parameters without dealing with inverse problems. For this purpose, multitemporal fully polarimetric SAR images, which are acquired in the frame of the AgriSAR 2006 campaign with synchronous ground surface measurements over a whole vegetation period, are analyzed. The results have clearly demonstrated that the coherent measures have a strong relationship with wet biomass of crops. Although incoherent measures would be the preferred ones due to their simplicity in implementation, they showed to be very sensitive to changes in precipitation, causing misleading temporal interpretation at longer wavelength in some cases. © 2004-2012 IEEE.},
author_keywords={Agriculture; airborne L-band sensor; crop inventory; statistical similarity measures; synthetic aperture radar (SAR)},
document_type={Article},
source={Scopus},
}
@BOOK{Ekercin2013157,
author={Ekercin, S.a and Sertel, E.b and Dadaser-Celik, F.c and Durduran, S.d },
title={Investigating the climate change impacts on the water resources of the konya closed basin area (Turkey) using satellite remote sensing data},
journal={Causes, Impacts and Solutions to Global Warming},
year={2013},
pages={157-168},
doi={10.1007/9781461475880},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84949818244&partnerID=40&md5=90397a780c24740c5e90d70258746c8e},
affiliation={Dept. of Geomatics Engineering, Aksaray University, Aksaray, Turkey; Dept. of Geomatics Engineering, Istanbul Technical University, Istanbul, Turkey; Dept. of Environmental Engineering, Erciyes University, Kayseri, Turkey; Dept. of Geomatics Engineering, Selçuk University, Konya, Turkey},
abstract={This chapter presents the pre-results from an ongoing study that mainly focuses on the use of remote sensing data to investigate the climate change effects on water resources in the Konya Closed Basin Area (KCBA), Turkey. In this study, multitemporal Landsat images along with climatic data were used to explore the dimension of drought effects on water lands and lakes located in the basin area. Image processing procedure includes both normalized difference vegetation index (NDVI) image interpretation and pre-processing stages (geometric and atmospheric correction). Our results suggest that in addition to socioeconomic profits of the use of groundwater for agricultural purposes, its effects on the ecological balance and water reserves in the KCBA should be analyzed in detail. Also, management strategies and plans should be developed to protect and/or rehabilitate current conditions in terms of drought in the KCBA. Furthermore, the region should regularly be monitored by up-to-date remote sensing data (at least annually) for better management of the water resources in the basin. © Springer Science+Business Media New York 2013. All rights reserved.},
document_type={Book Chapter},
source={Scopus},
}
@CONFERENCE{Ozcan2013195,
author={Ozcan, O.a and Bookhagen, B.b and Musaoglu, N.c },
title={Analyzing spatiotemporal patterns of extreme precipitation events in Southeastern Anatolia},
journal={International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives},
year={2013},
volume={40},
number={7W2},
pages={195-200},
doi={10.5194/isprsarchives-XL-7-W2-195-2013},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84924249741&partnerID=40&md5=dc0d96540a3e8cf0efd5d318fbe3a1fd},
affiliation={ITU, Application and Research Center for Satellite Communications and Remote Sensing, Istanbul, Turkey; UC Santa Barbara, Geography Department, Santa Barbara, CA, United States; ITU, Department of Geomatics Engineering, Maslak, Istanbul, Turkey},
abstract={Extreme environmental events, such as floods, droughts, rainstorms, and strong winds have severe consequences for human society. Changes in extreme weather and climate events have significant impacts and are among the most serious challenges to society in coping with a changing climate. The cost of damage caused by extreme climate events is rising all over the world. The European Environment Agency (EEA) report ("Climate Change, Impacts and Vulnerabilities in Europe 2012") stated that the cost of damage had increased from € 9 billion in the 1980s to €13 billions in the 2000s. In the United States, the National Oceanic and Atmospheric Administration (NOAA) reported that $188 billion in damage was caused by the severe weather events in 2011 and 2012. Understanding and identifying hydrometeorologic extreme events and their changes through time are key in sustaining agriculture and socio-economic development. Planning for weather-related emergencies, agricultural and reservoir management and insurance risk calculations, all rely on knowledge of the frequency of these extreme events. The assessment of extreme precipitation is an important problem in hydrologic risk analysis and design. Erosion and removal of the fertile soil layer through hydroclimatic extreme events is also a serious problem in semi-arid to arid regions, especially in mediterranean climates. Accurate measurements of precipitation on a variety of space and time scales are important to climate scientists and decision makers, including hydrologists, agriculturalists and emergency managers. The historical record of precipitation observations is limited mostly to land areas where rain gauges can be deployed, and measurements from those instruments are sparse over large and meteorologically important regions of the Turkey, such as over the Southeastern Anatolia Region. While rain gauge measurements are often used to tune hydrologic models, they are limited by their spatial coverage. Remote sensing techniques using spaceborne sensors provide an excellent complement to continuous monitoring of rain events both spatially and temporally. In this study we compare ground-station data with Tropical Rainfall Measurement Mission (TRMM) products at the 3-hour time scale to evaluate satellite rain estimates for agricultural and hydrological applications in Turkey. The remote sensing dataset TRMM product 3B42 has been validated with daily rain gauge measurements in order to characterize rainfall variability in the Southeastern Anatolia region. The precipitation retrievals from the TRMM satellite were compared with data from 7 surface rain gauges within the period of 1998-2012. Spatiotemporal patterns through statistical analyses were identified by fitting Generalized Extreme Value (GEV) rainfall distribution to the rainfall time series, and the fitting results were analyzed focusing on the behaviour of the shape parameter. Spatial patterns and correlations of rainfall events across the study area were also analysed by the calculation of the 90th, 95th and 99th percentiles. Regional frequency relationship were developed using the chosen GEV distribution. The recurrence intervals for different years have been estimated using the GEV distribution and their spatial variability has been described. The recurrence intervals of large rainstorms have also been identified for the rain gauge stations with the related TRMM pixel time series and spatial patterns in the study area have been evaluated. Preliminary results indicate that there exist large discrepancies between rain gauge and TRMM data at mean rainfall values; however, least squares fits indicate reliable and quite linear correlation for the 90th, 95th, 99th percentiles (r2=0.70, 0.77, and 0.75 respectively) and the annual maximum daily amount of precipitation (r2=0.69). In other words, TRMM product 3B42 can be used to assess first-order rainfall statistics and recurrence intervals, but rainfall magnitudes vary significantly from ground measurements.},
author_keywords={Extreme events; GEV; Precipitation; Shape parameter; Southeastern Anatolia; TRMM},
document_type={Conference Paper},
source={Scopus},
}
@CONFERENCE{Kaya2013703,
author={Kaya, S.a and Pekin, F.b and Seker, D.Z.a },
title={Automation of V-I-S model using Matlab&Simulink on user selected areas},
journal={34th Asian Conference on Remote Sensing 2013, ACRS 2013},
year={2013},
volume={1},
pages={703-708},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84903444926&partnerID=40&md5=a5d85821406d307cc91624fa1573684a},
affiliation={Istanbul Technical University, Department of Geomatics, 34469, Istanbul, Turkey; Istanbul Technical University, Institute of Informatics, 34469, Istanbul, Turkey},
abstract={Accurate calculation of land cover/use based on remote sensing data is very important for interpreters who analyze time or event based change on certain areas. Also any method that gives user flexibility on area selection provides great simplicity during analysis, since the analyzer may need to work on a specific area of interest instead of whole remote sensing data. The objectives of this study is develop an algorithm using Matlab&Simulink in order to filter V-I-S (Vegetation, Impervious, Soil) model surfaces from multispectral remote sensing data and acquire percentage distribution of the corresponding components to analyze a red, green and near infrared band composite of a Landsat 5 TM 7 bands image of a selected region in Istanbul by using the developed algorithms. The acquired results for each band were correlated in order to produce combined percentage values of each component OF V-I-S model.},
author_keywords={Algorithm; Filtering; Landsat TM; Matlab&Simulink; V-I-S},
document_type={Conference Paper},
source={Scopus},
}
@CONFERENCE{Sipka2013815,
author={Sipka, T. and Musaoglu, N.},
title={Accuracy assesment of WorldView-1 digital elevation model},
journal={34th Asian Conference on Remote Sensing 2013, ACRS 2013},
year={2013},
volume={1},
pages={815-822},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84903456663&partnerID=40&md5=a0c3cccb9c11486ca7f7b3fddebbf900},
affiliation={Istanbul Technical University, Geomatics Engineering Department, 34469 Maslak Istanbul, Turkey},
abstract={In this study, the accuracy of digital elevations derived from WorldView-1 stereo ortho-ready images covering an area of 25km2 was examined. The area of this study consists of an elevation range between 115-245m including cumulative heights. During the study, a digital elevation model with a 1m spatial resolution was derived using the Rational Polynomial Coefficients (RPC) of the stereo images from 14 ground control points (GCP) and 50 tie points. In accordance with these parameters, a parallax error of about 2 resulted from the processing of the images. Accuracy assessment was performed between the vertical accuracy of the absolute digital elevation model and the ground control points measured on site. As a result, the vertical accuracy varied between 0.12m and 1.4192m.},
author_keywords={Accuracy; Stereo digital elevation; WorldView-1},
document_type={Conference Paper},
source={Scopus},
}
@CONFERENCE{Simsek2013642,
author={Simsek, D. and Kaya, S. and Ipbuker, C. and Sertel, E.},
title={Determination of characteristic properties of rural residental areas using remotely sensed data},
journal={34th Asian Conference on Remote Sensing 2013, ACRS 2013},
year={2013},
volume={1},
pages={642-649},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84903437960&partnerID=40&md5=632f4143ec35205a4c9de8f60f8fdc35},
affiliation={Istanbul Technical University, Department of Geomatics Engineering, Maslak-Istanbul, Turkey},
abstract={The shanty, haphazard and unplanned settlements have become one of the most essential issues in the Third-World and developing countries, resulting from the unfilled provision of a planned development at rural areas. Determination of rural areas prior to rural planning is an important task in order to provide a healthy social and economic structure and protect natural environment by preventing shanty settlements. In this respect, preparing rural plans to protect the structures of the natural and rural areas require accurate and up-to-date geographical data and extensive spatial analysis that could be employed by the integration of remote sensing technology and geographic information systems. In this research, Karabuk Province located on the western part of Blacksea region having broad rural settlements was selected as study area to determine the characteristic features of the rural settlements using satellite sensor images. Furthermore, an assessment was conducted to analyze the correlation of these features with the spatial configuration of the rural settlements.},
author_keywords={GIS; Remote sensing; Rural characteristics; Rural planning},
document_type={Conference Paper},
source={Scopus},
}
@CONFERENCE{Seker20131815,
author={Seker, D.Z. and Kaya, S. and Tanik, A. and Bitik, E. and Denli, H.},
title={Urbanisation and deforestration: A case study from a mega city - Istanbul},
journal={34th Asian Conference on Remote Sensing 2013, ACRS 2013},
year={2013},
volume={2},
pages={1815-1819},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84903471548&partnerID=40&md5=f866395631dfaea305b5b01da7dc876e},
affiliation={Istanbul Technical University, 34469 Istanbul, Turkey},
abstract={This study aims to examine the temporal impact of rapid urban growth on forest cover in the mega city of Istanbul between the years 1987-2011. Currently, Istanbul is ranked among the most crowded cities of the world with an approximate current population of 14 million. It hosts 18.3% of the overall population of the country. Urbanization and industrialization in addition to migration from the other regions of Turkey for benefitting from better employment opportunities within years are the main causes of the urban sprawl especially within the past few decades. The main forestry area located mostly at the northern part of the city has been severely damaged during the examined period. In the study, spatial distribution of forests and their corresponding temporal changes were analyzed and presented by utilizing the modern technological tools of Remote Sensing (RS) and Geographical Information Systems (GIS).},
author_keywords={Deforestation; Istanbul; Remote sensing; Temporal land-use change; Urbanization},
document_type={Conference Paper},
source={Scopus},
}
@ARTICLE{Almeida20143995,
author={Almeida, C.a and Gamba, P.b and Juergens, C.c and Maktav, D.d and Salmon, B.e },
title={Foreword to the special issue on human settlement observation and monitoring from space},
journal={IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
year={2014},
volume={7},
number={10},
pages={3995-3996},
doi={10.1109/JSTARS.2014.2380291},
art_number={6994941},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84920986586&partnerID=40&md5=7371ef09a3837b3799fe6f71a47b9148},
affiliation={Division for Remote Sensing, National Institute for Space Research, Sao Paulo, Brazil; Department of Electronics, University of Pavia, Pavia, Italy; Department of Geography, Ruhr-University Bochum, Bochum, Germany; Geomatics Engineering Department, Istanbul Technical University, Istanbul, Turkey; School of Engineering and ICT, University of Tasmania, Hobart, TAS, Australia},
document_type={Editorial},
source={Scopus},
}
@ARTICLE{Topan20143683,
author={Topan, H.a and Maktav, D.b },
title={Efficiency of orientation parameters on georeferencing accuracy of SPOT-5 HRG level-1A stereoimages},
journal={IEEE Transactions on Geoscience and Remote Sensing},
year={2014},
volume={52},
number={6},
pages={3683-3694},
doi={10.1109/TGRS.2013.2274775},
art_number={6587541},
note={cited By 2},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84896388631&partnerID=40&md5=7173047ea3ebe53a151c2aaa1406fe54},
affiliation={Department of Geomatics Engineering, Bülent Ecevit University, 67100 Zonguldak, Turkey; Department of Geomatics Engineering, Istanbul Technical University, 34469 Istanbul, Turkey},
abstract={The efficiency of interior orientation parameters (IOPs) and exterior orientation parameters (EOPs) of the Satellite Pour l'Observation de la Terre 5 (SPOT-5) has been investigated with respect to georeferencing accuracy. A couple of SPOT-5 high-resolution geometric panchromatic level-1A stereoimages with 5-m ground sampling distance covering Zonguldak (Turkey) test field were used for this purpose using orientation parameters provided by metadata files. Ground control points are obtained by Global Positioning System observations. For the purpose of establishing geometric relationship between image and ground coordinate systems, an orbit-attitude parametric model has been used considering imaging geometry of sensor and ephemeris data of satellite. Adjustment consisting of the Gauss-Helmert model was performed in pre- and bundle-adjustment steps. Analyses show that the most efficient parameters are IOPs defined by look angles while EOPs are not significant on the accuracy. The validation of the EOPs and the correlation among IOPs and EOPs are also statistically analyzed. Different variations of point distribution and EOP configurations were preferred, achieving the georeferencing accuracies as ∼±1m and ∼± 5m at control and check points, respectively. All computations are performed via the developed program package called GeoSpot in Matlab platform. © 2013 IEEE.},
author_keywords={Block adjustment; Gauss-Helmert model; georeferencing accuracy; interior orientation parameters (IOPs) and exterior orientation parameters (EOPs); satellite orbital data; Satellite Pour l'Observation de la Terre 5 (SPOT-5) high-resolution geometric (HRG) level 1A},
document_type={Article},
source={Scopus},
}
@CONFERENCE{Kalkan2013125,
author={Kalkan, K.a and Bayram, B.b and Maktav, D.a and Sunar, F.a },
title={Comparison of support vector machine and object based classification methods for coastline detection},
journal={International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives},
year={2013},
volume={40},
number={7W2},
pages={125-127},
doi={10.5194/isprsarchives-XL-7-W2-125-2013},
note={cited By 1},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84924225614&partnerID=40&md5=6724586053a2ed555c1a15cbd079671b},
affiliation={ITU, Civil Engineering Faculty, Department of Geomatics Engineering, Maslak, Istanbul, Turkey; YTU, Civil Engineering Faculty, Department of Geomatics Engineering, Davutpaşa, Istanbul, Turkey},
abstract={Detection of coastline is an important procedure for management of coastal zones. According to the International Geographic Data Committee (IGDC), coastlines are one of the most important environmental heritages on the earth's surface. In the coastal areas, main challenge is to understand the present coastline dynamics and to predict its future developments. Therefore the coastal zone monitoring is an essential process for sustainable coastal management and environmental protection. Shoreline extraction is an important issue for coastal zone monitoring. In this study, efficiency of two different methods for detection of coastline features from satellite images, which cover Lakeland region of Turkey, has been tested. Firstly, object based classification method (OBC) has been used to extract shoreline automatically. Developed process based rule set extracts coastline as a vector file from satellite imagery. As a second method, support vector machine (SVM) algorithm has been used to extract coastline. For the application of these two different methods, Landsat 8 data have been used. The results of these two automatic coastline extraction methods were compared with the results derived from manual digitization process. Random control points over the coastline were used in the evaluation. Results showed that both methods have a sub-pixel accuracy to detect coastline features from Landsat 8 imagery.},
author_keywords={Coastline detection; Object-based classification (OBC); Support vector machine (SVM)},
document_type={Conference Paper},
source={Scopus},
}
@ARTICLE{Akın2015,
author={Akın, A.a and Sunar, F.b and Berberoğlu, S.c },
title={Urban change analysis and future growth of Istanbul},
journal={Environmental Monitoring and Assessment},
year={2015},
volume={187},
number={8},
page_count={15},
doi={10.1007/s10661-015-4721-1},
art_number={506},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84937852190&partnerID=40&md5=9cc0871c99a652861fb0ec3f2c0d3e03},
affiliation={Department of Urban and Regional Planning, Bursa Technical University, Bursa, Turkey; Department of Geomatics Engineering, Istanbul Technical University, Istanbul, Turkey; Landscape Architecture Department, Çukurova University, Adana, Turkey},
abstract={This study is aimed at analyzing urban change within Istanbul and assessing the city’s future growth potential using appropriate approach modeling for the year 2040. Urban growth is a major driving force of land-use change, and spatial and temporal components of urbanization can be identified through accurate spatial modeling. In this context, widely used urban modeling approaches, such as the Markov chain and logistic regression based on cellular automata (CA), were used to simulate urban growth within Istanbul. The distance from each pixel to the urban and road classes, elevation, and slope, together with municipality and land use maps (as an excluded layer), were identified as factors. Calibration data were obtained from remotely sensed data recorded in 1972, 1986, and 2013. Validation was performed by overlaying the simulated and actual 2013 urban maps, and a kappa index of agreement was derived. The results indicate that urban expansion will influence mainly forest areas during the time period of 2013–2040. The urban expansion was predicted as 429 and 327 km2 with the Markov chain and logistic regression models, respectively. © 2015, Springer International Publishing Switzerland.},
author_keywords={Istanbul; Logistic regression; Markov chain; Urban growth},
document_type={Article},
source={Scopus},
}
@ARTICLE{DamlaUcaAvci20151635,
author={Damla Uca Avci, Z.a and Sunar, F.b },
title={Process-based image analysis for agricultural mapping: A case study in Turkgeldi region, Turkey},
journal={Advances in Space Research},
year={2015},
volume={56},
number={8},
pages={1635-1644},
doi={10.1016/j.asr.2015.07.021},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84942194652&partnerID=40&md5=936c14c8281ff11a40bf09db2eeb389e},
affiliation={Istanbul Technical University, Department of Astronautics, Faculty of Aeronautics and Astronautics, Ayazaga Campus, Istanbul, Turkey; Istanbul Technical University, Department of Geomatics, Faculty of Civil Engineering, Ayazaga Campus, Istanbul, Turkey},
abstract={The need for timely, accurate, and interoperable geospatial information is steadily increasing. In this context, process-based image processing systems will be the initial segment for future's automatic systems. A process-based system is believed to be a good approach for agricultural purpose because agricultural activities are carried out according to a periodic (annual) cycle. Therefore, a process-based image analysis procedure was designed for routine crop classification for an agricultural region in KIrklareli, Turkey. The process tree developed uses a multi-temporal image data set as an input and gives the final crop classification as an output by using an incremental rule set. The test data set was composed of five images of Satellite Pour l'Observation de la Terre 4 (SPOT 4) data acquired in 2007. Basically, image objects were first extracted and then classified. A rule set was structured depending on class definitions. A decision-based process was executed and formed a multilevel image classification system. The final classification was obtained by merging classes from the appropriate levels where they were extracted. To evaluate the success of the application the accuracy of the classification was assessed. The overall accuracy and kappa index of agreement was found to be 80% and 0.78, respectively. At the end of the study, problems of segmentation and classification operations were discussed and solution approaches were outlined. To assess the process in terms of its scope for automation, the efficiency and success of the rule set were also discussed. © 2015 COSPAR. Published by Elsevier Ltd. All rights reserved.},
author_keywords={Crop mapping; Image processing; Object-based classification},
document_type={Article},
source={Scopus},
}
@CONFERENCE{Akin20149,
author={Akin, A.a and Aliffi, S.b and Sunar, F.c },
title={Spatio-temporal urban change analysis and the ecological threats concerning the third bridge in istanbul city},
journal={International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives},
year={2014},
volume={40},
number={7},
pages={9-14},
doi={10.5194/isprsarchives-XL-7-9-2014},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84924274782&partnerID=40&md5=7ac866bac25c068627571ff5a5c525e7},
affiliation={Bursa Technical University, Department of Urban and Regional Planning, Bursa, Turkey; Polytechnic of Turin, Department of Environment, Land and Infrastructure Engineering, Turin, Italy; Istanbul Technical University, Department of Geomatics Engineering, Istanbul, Turkey},
abstract={Urban growth is a complex dynamical process associated with landscape change driving forces such as the environment, politics, geography and many others that affect the city at multiple spatial and temporal scales. Istanbul, one of the largest agglomerations in Europe and the fifth-largest city in the world in terms of population within city limits, has been growing very rapidly over the late 20th century at a rate of 3.45%, causing to have many environmental issues. Recently, Istanbul's new third bridge and proposed new routes for across the Bosphorus are foreseen to not only threaten the ecology of the city, but also it will give a way to new areas for unplanned urbanization. The dimensions of this threat are affirmed by the urban sprawl especially after the construction of the second bridge and the connections such as Trans European Motorway (TEM). Since the spatial and temporal components of urbanization can be more simply identified through modeling, this study aims to analyze the urban change and assess the ecological threats in Istanbul city through the proper modeling for the year 2040. For this purpose, commonly used urban modeling approach, the Markov Chain within Cellular Automata (CA), was selected to simulate urban/non-urban growth process. CA is a simple and effective tool to capture and simulate the complexity of urban system dynamic. The key factor for a Markov is the transition probability matrix, which defines change trend from past to today and into the future for a certain class type, and land use suitability maps for urban. Multi Criteria Analysis was used to build these suitability maps. Distance from each pixel to the urban, road and water classes, plus the elevation, slope and land use maps (as excluded layer) were defined as factors. Calibration data were obtained from remotely sensed data recorded in 1972, 1986 and 2013. Validation was performed by overlaying the simulated and actual 2013 urban maps and Kappa Index of Agreement was calculated. The results indicate that the urban expansion will influence mainly forest areas during the time period of 1972-2040.},
author_keywords={CA Markov; Istanbul; MCA; Sprawl; Urban},
document_type={Conference Paper},
source={Scopus},
}
@CONFERENCE{Zirek2014221,
author={Zirek, E. and Sunar, F.},
title={Change detection of seafloor topography by modeling multitemporal multibeam echosounder measurements},
journal={International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives},
year={2014},
volume={40},
number={7},
pages={221-227},
doi={10.5194/isprsarchives-XL-7-221-2014},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84924247879&partnerID=40&md5=13eb79fb129fa272edbe1849b9716824},
affiliation={Istanbul Technical University, Department of Geomatics Engineering, Maslak, Turkey},
abstract={The term "topography" implies the study of numerous landforms that exist on or below the Earth and a detailed knowledge of topography is required to understand the most Earth processes. In the oceans, sea floor topography refers the geographic features of the sea floor including the configuration of a surface and the position of its natural and man-made features; and detailed nautical charts are fundamental for many sciences such as physical oceanography, biology and marine geology. The hydrographic offices, which use the Multi Beam Echo sounder (MBE) system for the establishment of nautical charts, have their own set of accuracy standards for hydrographic surveys, which generally comply with the standards defined by the International Hydrographic Organization. MBE systems include multiple measurement systems such as sonar head, positioning system, motion sensor that work in a synchronized manner. Before the measurements, the 'Patch Test' is required to eliminate the systematic errors due to instrumental synchronization and installation. In this test, signal delay test (latency), Y-axis rotation (roll), X-axis rotation (pitch), Z-axis rotation (yaw) errors are calculated. Besides, the effects of the sound velocity measurement through water column and the sea level changes need to be taken into consideration especially in the multi-temporal data analysis and 3D modeling. In this paper, the seafloor of the Anamur -TRNC Drinking Water Pipeline route in the 'Northern Cyprus Water Project' is selected as a study area. This project, a unique in the world, is an international water diversion project designed to supply water for drinking and irrigation from southern Turkey to Northern Cyprus via pipeline under Mediterranean Sea. Multi temporal multi beam echo sounder measurements are used in the change analysis and surface modeling and the efficiency of this system is outlined together with its limitations.},
author_keywords={3D sea floor modeling; Change detection; Multibeam Echo sounder},
document_type={Conference Paper},
source={Scopus},
}
@ARTICLE{Abdikan2014671,
author={Abdikan, S.a and Balik Sanli, F.a and Sunar, F.b and Ehlers, M.c },
title={A comparative data-fusion analysis of multi-sensor satellite images},
journal={International Journal of Digital Earth},
year={2014},
volume={7},
number={8},
pages={671-687},
doi={10.1080/17538947.2012.748846},
note={cited By 3},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84902493863&partnerID=40&md5=1ed35b195d6fe8089f754ba434e2b1ca},
affiliation={Geomatic Engineering Department, Yildiz Technical University, Istanbul, Turkey; Geomatic Engineering Department, Istanbul Technical University, Istanbul, Turkey; Institute for Geoinformatics and Remote Sensing, University of Osnabrück, Osnabrück, Germany},
abstract={Remote-sensing data play an important role in extracting information with the help of various sensors having different spectral, spatial and temporal resolutions. Therefore, data fusion, which merges images of different spatial and spectral resolutions, plays an important role in information extraction. This research investigates quality-assessment methods of multisensor (synthetic aperture radar [SAR] and optical) data fusion. In the analysis, three SAR data-sets from different sensors (RADARSAT-1, ALOS-PALSAR and ENVISAT-ASAR) and optical data from SPOT-2 were used. Although the PALSAR and the RADARSAT-1 images have the same resolutions and polarisations, images are gathered in different frequencies (L and C bands, respectively). The ASAR sensor also has C-band radar, but with lower (25 m) resolution. Since the frequency is a key factor for penetration depth, it is thought that the use of different SAR data might give interesting results as an output. This study describes a comparative study of multisensor fusion methods, namely the intensity-hue-saturation, Ehlers, and Brovey techniques, by using different statistical analysis techniques, namely the bias of mean, correlation coefficient, standard deviation difference and universal image quality index methods. The results reveal that Ehlers' method is superior to the others in terms of spectral and statistical fidelity. © 2012 Taylor & Francis.},
author_keywords={accuracy; image fusion; image processing; multisensor; SAR},
document_type={Article},
source={Scopus},
}
@CONFERENCE{Osmanoglu2013189,
author={Osmanoglu, B.a and Ozkan, C.b and Sunar, F.c },
title={Comparison of semi-automatic and automatic slick detection algorithms for Jiyeh Power Station oil spill, Lebanon},
journal={International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives},
year={2013},
volume={40},
number={7W2},
pages={189-193},
doi={10.5194/isprsarchives-XL-7-W2-189-2013},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84924275764&partnerID=40&md5=1ea3b246de25c5b0924ceb7553e54fc6},
affiliation={USRA, NASA Goddard Space Flight Center, United States; Erciyes University, Kayseri, Turkey; Istanbul Technical University, Istanbul, Turkey},
abstract={After air strikes on July 14 and 15, 2006 the Jiyeh Power Station started leaking oil into the eastern Mediterranean Sea. The power station is located about 30km south of Beirut and the slick covered about 170 km of coastline threatening the neighboring countries Turkey and Cyprus. Due to the ongoing conflict between Israel and Lebanon, cleaning efforts could not start immediately resulting in 12,000 to 15,000 tons of fuel oil leaking into the sea. In this paper we compare results from automatic and semi-automatic slick detection algorithms. The automatic detection method combines the probabilities calculated for each pixel from each image to obtain a joint probability, minimizing the adverse effects of atmosphere on oil spill detection. The method can readily utilize X-, C- and L-band data where available. Furthermore wind and wave speed observations can be used for a more accurate analysis. For this study, we utilize Envisat ASAR ScanSAR data. A probability map is generated based on the radar backscatter, effect of wind and dampening value. The semi-automatic algorithm is based on supervised classification. As a classifier, Artificial Neural Network Multilayer Perceptron (ANN MLP) classifier is used since it is more flexible and efficient than conventional maximum likelihood classifier for multi-source and multi-temporal data. The learning algorithm for ANN MLP is chosen as the Levenberg-Marquardt (LM). Training and test data for supervised classification are composed from the textural information created from SAR images. This approach is semiautomatic because tuning the parameters of classifier and composing training data need a human interaction. We point out the similarities and differences between the two methods and their results as well as underlining their advantages and disadvantages. Due to the lack of ground truth data, we compare obtained results to each other, as well as other published oil slick area assessments.},
author_keywords={Oil spill; SAR},
document_type={Conference Paper},
source={Scopus},
}
@CONFERENCE{BalikSanli201327,
author={Balik Sanli, F.a and Abdikan, S.b and Esetlili, M.T.c and Ustuner, M.a and Sunar, F.d },
title={Fusion of terrasar-X and rapideye data: A quality analysis},
journal={International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives},
year={2013},
volume={40},
number={7W2},
pages={27-30},
doi={10.5194/isprsarchives-XL-7-W2-27-2013},
note={cited By 0},
url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84924243187&partnerID=40&md5=a8364dca9fdf306d33325b969a5d85c4},
affiliation={Yildiz Technical University, Civil Engineering Faculty, Department of Geomatic Engineering, Esenler-Istanbul, Turkey; BeeSense, Consultancy and Engineering on Geo-Information Technologies, Delft, Netherlands; Ege University, Faculty of Agriculture, Deparment of Soil Science and Plant Nutrition, Bornova-Izmir, Turkey; Istanbul Technical University, Civil Engineering Faculty, Department of Geomatic Engineering, Maslak-Istanbul, Turkey},
abstract={This research compares and evaluates image fusion algorithms to achieve spatially improved images while preserving the spectral information. In order to compare the performance of fusion techniques both active and passive images were used. As an active image a high resolution, X-band, VV polarized TerraSAR-X data and as a multispectral image RapidEye data were used. RapidEye provides five optical bands in the 400-850 nm range and it is the first space-borne sensor which operationally gathers the red edge spectrum (690-730 nm) besides the standard channels of multi-spectral satellite sensors. The selected study area is in the low lands of Menemen (Izmir) Plain on the west of Gediz Basin covering both agricultural fields and residential areas. For the quality analysis, Adjustable SAR-MS Fusion (ASMF), Ehlers fusion and High Pass Filtering (HPF) approaches were investigated. In this study preliminary results of selected image fusion methods were given. The quality of the fused images was assessed with qualitative and quantitative analyses. For the qualitative analysis visual comparison was applied using different band combinations of fused image and original multispectral Rapid-Eye image. In the merged images color distortions regarding to SAR-optical synergy were investigated. Statistical analysis was carried out as quantitative analyses. In this respect Correlation Coefficient (CC), Standard Deviation Difference (SDD), Universal Image Quality Index (UIQI) and Root Mean Square Error (RMSE) were performed for quality assessments. In general HPF was performed best while ASMF was performed the worst in all results.},
author_keywords={Image fusion; Multi-sensor; RapidEye; TerraSAR-X},
document_type={Conference Paper},
source={Scopus},
}
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