Evaluation of cross-track illumination in EO-1 Hyperion imagery for lithological mapping

2011-01-01
San, B. Taner
Süzen, Mehmet Lütfi
Hyperspectral remote sensing data is a powerful tool for discriminating lithological units and for the preparation of mineral maps for alteration studies. The spaceborne hyperspectral Hyperion sensor, despite its narrow swath width (similar to 7.5 km), possesses great potential with its 196 channels within the wavelength range 426.82-2395.50 nm. Although it has many advantages such as low cost and on-demand coverage, much uncertainty exists in the utility of its applications. For example, poor signal-to-noise ratio, the presence of sensor-specific defects and thicker atmospheric column due to its spaceborne platform makes certain environmental and geological applications difficult or impossible. In this article we demonstrate these calibration-related uncertainties, which are manifest from the preprocessing stage to the classification stage. In addition, the intimate mixing of minerals within specific targets, for example within individual outcropping lithological units or endmembers, adds uncertainty to our spectral discrimination results. The aim of this study was to develop and evaluate an approach for geological mapping of outcrops with Earth Observing- 1 (EO-1) Hyperion data. Atmospheric corrections and correction for cross-track illumination (CTI) variations (smile) were determined at different wavelength regions: the visible-near-infrared (VNIR; 420-1000 nm) and shortwave infrared (SWIR; 1000-2400 nm) regions. Our methodology was tested in a selected site at Central Anatolia, Turkey containing minimal vegetation cover. The results obtained from the image analyses were then compared and assessed with field observations and spectral measurements.
INTERNATIONAL JOURNAL OF REMOTE SENSING

Suggestions

Evaluation of the NDVI in plant community composition mapping: a case study of Tersakan Valley, Amasya County, Turkey
DOĞAN, Hakan Mete; Celep, Ferhat; Karaer, Fergan (Informa UK Limited, 2009-01-01)
Mapping the composition of plant community types requires reliable spatial data obtained from field surveys and satellite-derived indices. The normalized difference vegetation index (NDVI) is the simplest and most frequently used index in plant applications. If relationships between the NDVI and plant cover abundance are determined, this information can be used in the mapping process. In this study, we investigated these possible connections for mapping the plant community composition of Tersakan Valley in ...
Integration of environmental variables with satellite images in regional scale vegetation classification
Domaç, Ayşegül; Süzen, Mehmet Lütfi; Bilgin, Cemal Can (Informa UK Limited, 2006-04-01)
The difficulty of collecting information at conventional field studies and relatively coarse spatial and spectral resolution of Landsat images forced the use of environmental variables as ancillary data in vegetation mapping. The aim of this study is to increase the accuracy of species level vegetation classification incorporating environmental variables in the Amanos Mountains region of southern central Turkey. In the first part of the study, ordinary vegetation classification is attained by using a maximu...
Evaluation of Remotely-Sensed and Model-Based Soil Moisture Products According to Different Soil Type, Vegetation Cover and Climate Regime Using Station-Based Observations over Turkey
Bulut, Burak; Yılmaz, Mustafa Tuğrul; Afshar, Mahdı Hesamı ; Sorman, A. Unal; Yücel, İsmail; Cosh, Michael H.; Simsek, Osman (MDPI AG, 2019-08-01)
This study evaluates the performance of widely-used remotely sensed- and model-based soil moisture products, including: The Advanced Scatterometer (ASCAT), the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E), the European Space Agency Climate Change Initiative (ESA-CCI), the Antecedent Precipitation Index (API), and the Global Land Data Assimilation System (GLDAS-NOAH). Evaluations are performed between 2008 and 2011 against the calibrated station-based soil moisture observations coll...
Hierarchical classification of Sentinel 2-a images for land use and land cover mapping and its use for the CORINE system
Demirkan, Doga C.; Koz, Alper; Duzguna, H. Sebnem (SPIE-Intl Soc Optical Eng, 2020-06-01)
The aim of this study is to investigate the potential of the Sentinel-2 satellite for land use and land cover (LULC) mapping. The commonly known supervised classification algorithms, support vector machines (SVMs), random forest (RF), and maximum likelihood (ML) classification are adopted for investigation along with a proposed hierarchical classification model based on a coordination of information on the environment land cover system. The main classes for land cover and mapping in the proposed hierarchica...
Evaluation of GPM-era Global Satellite Precipitation Products over Multiple Complex Terrain Regions
Derin, Yagmur; Anagnostou, Emmanouil; Berne, Alexis; Borga, Marco; Boudevillain, Brice; Buytaert, Wouter; Chang, Che-Hao; Chen, Haonan; Delrieu, Guy; Hsu, Yung Chia; Lavado-Casimiro, Waldo; Manz, Bastian; Moges, Semu; Nikolopoulos, Efthymios I.; Sahlu, Dejene; Salerno, Franco; Rodriguez-Sanchez, Juan-Pablo; Vergara, Humberto J.; Yılmaz, Koray Kamil (MDPI AG, 2019-12-02)
The great success of the Tropical Rainfall Measuring Mission (TRMM) and its successor Global Precipitation Measurement (GPM) has accelerated the development of global high-resolution satellite-based precipitation products (SPP). However, the quantitative accuracy of SPPs has to be evaluated before using these datasets in water resource applications. This study evaluates the following GPM-era and TRMM-era SPPs based on two years (2014-2015) of reference daily precipitation data from rain gauge networks in te...
Citation Formats
B. T. San and M. L. Süzen, “Evaluation of cross-track illumination in EO-1 Hyperion imagery for lithological mapping,” INTERNATIONAL JOURNAL OF REMOTE SENSING, pp. 7873–7889, 2011, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/35509.