Volume 20, Issue 4-4, December 2016
INLAND EXCESS WATER MAPPING USING HYPERSPECTRAL IMAGERY
Authors: Bálint Csendes, László Mucsi
Abstract: Hyperspectral imaging combined with the potentials of airborne scanning is a powerful tool to monitor environmental processes. The aim of this research was to use high resolution remotely sensed data to map the spatial extent of inland excess water patches in a Hungarian study area that is known for its oil and gas production facilities. Periodic floodings show high spatial and temporal variability, nevertheless, former studies have proven that the affected soil surfaces can be accurately identified. Besides separability measurements, we performed spectral angle classification, which gave a result of 85% overall accuracy and we also compared the generated land cover map with LIDAR elevation data.
Keywords: inland excess water, SAM classification, spectral separability, LIDAR, hyperspectral remote sensing.
Article info: 191–196
Received: May 17, 2016 | Revised: July 21, 2016 | Accepted: October 12, 2016