Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 65-69, 2016
https://doi.org/10.5194/isprs-archives-XLI-B7-65-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
17 Jun 2016
A STUDY OF THE IMPACT OF INSOLATION ON REMOTE SENSING-BASED LANDCOVER AND LANDUSE DATA EXTRACTION
K. Becek1,2, A. Borkowski3, and Ç. Mekik2 1Dept. of Geomatics, Bülent Ecevit University, Zonguldak, Turkey
2Dept. of Geodesy & Geoinformatics, Wroclaw University of Sciences & Technology, Wroclaw, Poland
3Inst. of Geodesy and Geoinformatics, Wroclaw University of Environmental and Life Sciences, Wroclaw, Poland
Keywords: LiDAR, DSM, NTII, Insolation, Hyperspectral Imaging Spectrometer Data Abstract. We examined the dependency of the pixel reflectance of hyperspectral imaging spectrometer data (HISD) on a normalized total insolation index (NTII). The NTII was estimated using a light detection and ranging (LiDAR)-derived digital surface model (DSM). The NTII and the pixel reflectance were dependent, to various degrees, on the band considered, and on the properties of the objects. The findings could be used to improve land cover (LC)/land use (LU) classification, using indices constructed from the spectral bands of imaging spectrometer data (ISD). To study this possibility, we investigated the normalized difference vegetation index (NDVI) at various NTII levels. The results also suggest that the dependency of the pixel reflectance and NTII could be used to mitigate the shadows in ISD. This project was carried out using data provided by the Hyperspectral Image Analysis Group and the NSF-funded Centre for Airborne Laser Mapping (NCALM), University of Houston, for the purpose of organizing the 2013 Data Fusion Contest (IEEE 2014). This contest was organized by the IEEE GRSS Data Fusion Technical Committee.
Conference paper (PDF, 881 KB)


Citation: Becek, K., Borkowski, A., and Mekik, Ç.: A STUDY OF THE IMPACT OF INSOLATION ON REMOTE SENSING-BASED LANDCOVER AND LANDUSE DATA EXTRACTION, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 65-69, https://doi.org/10.5194/isprs-archives-XLI-B7-65-2016, 2016.

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