First Experience with Figure Condition Analysis Aided Bias Compensated Rational Function Model for Georeferencing of High Resolution Satellite Images

Topan H.

Article | 2013 | Journal of the Indian Society of Remote Sensing41 ( 4 ) , pp.807 - 818

Georeferencing of high resolution satellite images using sensor-dependent Rational Function Model (RFM) is a common approach in the remote sensing community since the turn of the millennium. In the case of mono image evaluation, the georeferencing is performed using the ground control points (GCPs), and the image-wide georeferencing accuracy is estimated at the independent check points (ICPs). Nevertheless, such an accuracy assessment approach has some disadvantages and must be overcomed by a proper method as suggested by the figure condition analysis (FCA). Considering various bias compensation methods, the FCA is adopted to RFM an . . .d a case study is performed on three high resolution satellite images (HRSIs), IKONOS Geo, QuickBird OrthoReady Standard and OrbView-3 Basic, covering undulating and mountainous Zonguldak test site. The results demonstrate that a bias compensation is required for all images, and IKONOS has the highest accuracy both at GCPs and figure condition points (FCPs) where OrbView-3 has the lowest accuracy. The innovative characteristics of FCA and further research issues are also discussed. © 2013 Indian Society of Remote Sensing Daha fazlası Daha az

Evaluation of image fusion methods using PALSAR, RADARSAT-1 and SPOT images for land use/ land cover classification

Sanli F.B. | Abdikan S. | Esetlili M.T. | Sunar F.

Article | 2017 | Journal of the Indian Society of Remote Sensing45 ( 4 ) , pp.591 - 601

This research aimed to explore the fusion of multispectral optical SPOT data with microwave L-band ALOS PALSAR and C-band RADARSAT-1 data for a detailed land use/cover mapping to find out the individual contributions of different wavelengths. Many fusion approaches have been implemented and analyzed for various applications using different remote sensing images. However, the fusion methods have conflict in the context of land use/cover (LULC) mapping using optical and synthetic aperture radar (SAR) images together. In this research two SAR images ALOS PALSAR and RADARSAT-1 were fused with SPOT data. Although, both SAR data were gath . . .ered in same polarization, and had same ground resolution, they differ in wavelengths. As different data fusion methods, intensity hue saturation (IHS), principal component analysis, discrete wavelet transformation, high pass frequency (HPF), and Ehlers, were performed and compared. For the quality analyses, visual interpretation was applied as a qualitative analysis, and spectral quality metrics of the fused images, such as correlation coefficient (CC) and universal image quality index (UIQI) were applied as a quantitative analysis. Furthermore, multispectral SPOT image and SAR fused images were classified with Maximum Likelihood Classification (MLC) method for the evaluation of their efficiencies. Ehlers gave the best score in the quality analysis and for the accuracy of LULC on LULC mapping of PALSAR and RADARSAT images. The results showed that the HPF method is in the second place with an increased thematic mapping accuracy. IHS had the worse results in all analyses. Overall, it is indicated that Ehlers method is a powerful technique to improve the LULC classification. © 2016, Indian Society of Remote Sensing Daha fazlası Daha az

DEM Extraction in Urban Areas Using High-Resolution TerraSAR-X Imagery

Sefercik U.G. | Yastikli N. | Dana I.

Article | 2014 | Journal of the Indian Society of Remote Sensing42 ( 2 ) , pp.279 - 290

Three-dimensional (3D) spatial information is crucial for improving the quality of human life through urban planning and management, and it is widely utilized due to its rapid, periodic and inexpensive acquisition. In this context, extraction of digital surface and elevation models (DSM and DEM) is a significant research topic for space-borne optical and synthetic aperture radar (SAR) remote sensing. The DSMs include visible features on the earth's surface such as vegetation, forest and elevated man-made objects, while DEMs contain only the bare ground. In this paper, using TerraSAR-X (TSX) high resolution Spotlight (HS) images, hig . . .h-resolution interferometric DEM generation in a part of Istanbul urban area is aimed. This is not an easy task because of SAR imaging problems in complex geometry of urban settlements. The interferometric processing steps for DSM generation were discussed including critical parameters and thresholds to improve the quality of the final product and a 3 m gridded DSM was generated. The DSM-DEM conversion was performed by filtering and the quality of generated DEM was verified against a reference DEM from stereo photogrammetry with 3 m original grid spacing. The achieved root mean square error of height differences (RMSZ) varies from 7.09 to 8.11 m, depending on the terrain slope. The differential DEM, illustrates the height differences between generated DEM and the reference DEM, was generated to show the correlation between height differences and the coherence map. Finally, a perspective view of test area was created draping extracted DEM and a high-resolution IKONOS panchromatic image. © 2013 Indian Society of Remote Sensing Daha fazlası Daha az

Performance Estimation of Aster Global DEM Depending upon the Terrain Inclination

Sefercik U.G.

Article | 2012 | Journal of the Indian Society of Remote Sensing40 ( 4 ) , pp.565 - 576

A digital elevation model (DEM) is a source of immense three dimensional data revealing topographic characteristics of any region. The performance of a DEM can be described by accuracy and the morphologic conformity. Both depend upon the quality of data set, the used production technique and the roughness of the terrain. The global DEM of ASTER (Advanced Space-borne Thermal Emission and Reflection Radiometer) was released to public utilization as free of charge on June 2009. It covers virtually overall the globe using 1 arc-second posting interval. Especially easy availability renders ASTER Global DEM (GDEM) one of the most popular . . .and considerable global topographic data for scientific applications. From this point of view, the performance of ASTER GDEM has to be estimated for different kinds of topographies. Accordingly, six test fields from Spain (Barcelona) and Turkey (Istanbul and Zonguldak) have been preferred depending upon the terrain inclination. Thus, the advantages and disadvantages of the DEM product have been proved by means of a group of advanced performance analysis. The analyses indicate that the performance of ASTER GDEM is quite satisfying at urban areas because of flat topography. On the other hand, terrain slope has negative effect on the results. Especially steep, mountainous, forestry topographic formations and the regions which have sudden changes at the altitude have lower accuracy. © 2012 Indian Society of Remote Sensing Daha fazlası Daha az

Monitoring spatial and temporal land use/cover changes; a case study in Western Black Sea region of Turkey.

Alkan, Mehmet | Oruç, Murat | Yıldırım, Yılmaz | Şeker, Dursun Zafer | Jacobsen, Karsten

Article | 2013 | Journal of the Indian Society of Remote Sensing41 ( 3 ) , pp.587 - 596

Rapid land use/land cover changes have taken place in many cities of Turkey. Land use and land cover changes are essential for wide range of applications. In this study, Landsat TM satellite imageries date from 1987, 1993, 2000 and 2010 were used to analyse temporal and spatial changes in the Western Black Sea Region of Turkey. Zonguldak and Eregli two largest and economic important cities which have been active coal mining and iron fabric areas. Maximum Likelihood Classification technique was implemented and the results were represented in classes of open area, forest, agricultural, water, mining, urban and pollution in the sea. Ur . . .ban areas on both cities increased from 1987 to 2010. The agricultural and open areas from 1987 to 2010 decreased in parallel to land use and land cover change in both cities. Meanwhile, forest areas increased continuously with about 20 % from 1987 to 2010 in both cities. As industrial activity, the coal fields doubled from 1987 to 2010. © 2013 Indian Society of Remote Sensing Daha fazlası Daha az

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