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Artificial neural networks in the improvement of spatial resolution of thermal infrared data for improved landuse classification

DSpace at IIT Bombay

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Title Artificial neural networks in the improvement of spatial resolution of thermal infrared data for improved landuse classification
 
Creator VENKATESHWARLU, C
RAO, KG
PRAKASH, A
 
Subject landsat-tm
visible and near infrared
thermal infrared
spatial resolution improvement
artificial neural networks
 
Description The spatial resolution of remotely sensed (RS) data in the thermal infrared (TIR) range is very coarse compared to the very fine resolutions in the visible (VIS) and near infrared (NIR) ranges. Despite, the information on emissive properties of TIR data that is complementary to the reflective properties of the VIS and NIR data, the application of TIR data has been rather restricted, mainly due to its coarse spatial resolution. Artificial Neural Networks (ANN) have proved to be far superior [1][2] to the statistical methods in many applications. Studies have been carried out on the applicability of ANN in the improvement of effective spatial resolution of Landsat-5, TM band 6 (TIR) daytime and nighttime data. The present paper reports the methodology developed and the results of the studies. The results are compared with those of a statistical approach.
 
Publisher IEEE
 
Date 2011-10-24T11:53:55Z
2011-12-15T09:11:36Z
2011-10-24T11:53:55Z
2011-12-15T09:11:36Z
2003
 
Type Proceedings Paper
 
Identifier 2ND GRSS/ISPRS JOINT WORKSHOP ON REMOTE SENSING AND DATA FUSION OVER URBAN AREAS,162-166
0-7803-7719-2
http://dx.doi.org/10.1109/DFUA.2003.1219979
http://dspace.library.iitb.ac.in/xmlui/handle/10054/15412
http://hdl.handle.net/100/2173
 
Source 2nd GRS/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas,BERLIN, GERMANY,MAY 22-23, 2003
 
Language English