Title :
Permafrost classification on the Tibet Plateau based on surface emissivity retrieval from Terra-MODIS data
Author_Institution :
Dept. of Remote Sensing & Geographic Inf. Syst., Jilin Univ., Changchun, China
Abstract :
Surface emissivity is a measure of the inherent efficiency of the surface to convert heat energy into radiant energy outside the surface. It depends largely on the composition, roughness, and other physical parameters of the surface. The knowledge of surface emissivity permits discrimination and sometimes identification of different types of surfaces. The largest area of mountainous permafrost is on the Tibet plateau across the world, except the polar regions. Cloud free thermal infrared (TIR) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra satellite in early winter (Beijing time: Oct.20, 2001, 14:46:25) were chosen to retrieve the surface emissivity on the Tibet plateau by employing a spectral method (the emissivity normalization, NOR). The surface emissivity images were classified by an un-supervised classification method, and some segments were merged into a permafrost distribution map, which includes continuous permafrost, isolated ´island´ permafrost, seasonal permafrost (around the mountain or along the valley), and snow-ice. The results are rigorously consistent with field survey. And more details of the distribution of permafrost are also possible by this method.
Keywords :
hydrological techniques; ice; image classification; image segmentation; infrared imaging; microwave measurement; radiometry; snow; terrain mapping; AD 2001 10 20; China; MODIS; Moderate Resolution Imaging Spectroradiometer; TIR data; Terra satellite; Terra-MODIS data; Tibet Plateau; cloud free thermal infrared; emissivity normalization; heat energy; image segmentation; isolated island permafrost; mountainous permafrost; permafrost classification; permafrost distribution map; radiant energy; seasonal permafrost; snow ice; spectral method; surface composition; surface emissivity retrieval; surface roughness; unsupervised image classification; Clouds; Energy measurement; Image retrieval; Information retrieval; Infrared imaging; Infrared spectra; MODIS; Rough surfaces; Satellites; Surface roughness;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International
Print_ISBN :
0-7803-8742-2
DOI :
10.1109/IGARSS.2004.1369857