文章基本信息

标题：SURFACE TEMPERATURE ESTIMATION OF GANGOTRI GLACIER USING THERMAL REMOTE SENSING
本地全文：下载
作者：M. Anul Haq ; Dr. K. Jain ; Dr. K. P. R. Menon 等
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2012
卷号：XXXIX - B8
页码：115-119
DOI：10.5194/isprsarchives-XXXIX-B8-115-2012
出版社：Copernicus Publications
摘要：Land surface temperature (LST) is important factor in global climate change studies, for estimating radiation into heat balance studies and as a control for climate change models. The knowledge of surface temperature is important to a range of issues and themes in earth sciences, climate change and human interactions with environment. In this investigation an attempt has been made to estimate surface temperature from ASTER and Landsat Thermal Band data for the Gangotri Glacier. ASTER and Landsat Calibration had been performed to convert digital numbers to exoatmospheric radiance using published post-launch gains and offsets. The exoatmospheric radiance is then converted to surface radiance by applying the Emissivity Normalization method, assuming the emissivity of the Investigation area is constant (0.97, the emissivity of glacier ice). The surface temperature is then extracted from the surface radiance. Based on images from Oct 1990, 2001 and 2010 mean temperatures of 15.763, 15.893 and 17.154 respectively, are inferred. The extracted temperature data were compared to observed temperatures and showed a good correlation, with differences of 1–2oc.The variability of these retrieved Land surface Temperatures has been investigated with respect snout point, ELA and highest point of Gangotri Glacier determined from the Landsat visible bands and ASTER DEM. The emissivity per pixel is retrieved directly from satellite data and has been estimated as narrow band emissivity at the satellite sensor channel in order to minimize the errors in the land surface temperature estimation of study area
关键词：DEM; Classification; Snow Ice; Multitemporal; Multispectral