A neural network technique for separating land surface emissivity and temperature from ASTER imagery

NCUIR > Research Center > Center for Space and Remote Sensing Research > journal & Dissertation > Item 987654321/35800

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/35800

Title:	A neural network technique for separating land surface emissivity and temperature from ASTER imagery
Authors:	Mao,Kebiao;Shi,Jiancheng;Tang,Huajun;Li,Zhao-Liang;Wang,Xlufeng;Chen,Kun-Shan
Contributors:	太空及遙測研究中心
Keywords:	SPACEBORNE THERMAL EMISSION;REFLECTION RADIOMETER ASTER;SPLIT-WINDOW ALGORITHM;HIGH-RESOLUTION RADIOMETER;AVHRR DATA;WATER-VAPOR;MODIS DATA;RETRIEVAL;CLASSIFICATION;FEASIBILITY
Date:	2008
Issue Date:	2010-07-07 15:51:34 (UTC+8)
Publisher:	中央大學
Abstract:	Four radiative transfer equations for Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) bands 11, 12,13, and 14 are built involving six unknowns (average atmospheric temperature, land surface temperature, and four band emissivities),
Relation:	IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING????
Appears in Collections:	[Center for Space and Remote Sensing Research ] journal & Dissertation

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