DocumentCode :
298035
Title :
Spatial resolution enhancement of SSM/I data: vegetation studies of the Amazon Basin
Author :
Long, David G. ; Daum, Douglas R. ; Hardin, Perry J.
Author_Institution :
Dept. of Electr. & Comput. Eng., Brigham Young Univ., Provo, UT, USA
Volume :
3
fYear :
1996
fDate :
27-31 May 1996
Firstpage :
1606
Abstract :
The relatively low resolution of the Special Sensor Microwave/Imager (SSM/I) radiometer limits its utility in vegetation studies. However, resolution enhancement techniques can be used to ameliorate this limitation. To this end the Backus Gilbert inversion (BGI) technique and a modified form of the Scatterometer Image Reconstruction (SIR) algorithm are investigated as methods to create enhanced spatial resolution images from SSM/I data. A new method for generating cloud-free composite images is presented. The utility of the composite images is illustrated through a tropical vegetation discrimination study of general vegetation classes. An overall discrimination accuracy of 81.4% is achieved for 14 classes with most of the misclassification within broader vegetation categories
Keywords :
forestry; geophysical signal processing; geophysical techniques; image enhancement; image resolution; microwave measurement; millimetre wave measurement; radiometry; remote sensing; Amazon Basin; Backus Gilbert inversion; Brazil; EHF; SHF; SSM/I; Scatterometer Image Reconstruction; Special Sensor Microwave/Imager; algorithm; cloud-free composite image; discrimination accuracy; geophysical measurement technique; image classification; image enhancement; image resolution; microwave radiometry; millimetre radiometry; mm wave; satellite remote sensing; spatial resolution enhancement; tropical forest; vegetation class; vegetation mapping; Brightness; Clouds; Image reconstruction; Image resolution; Microwave radiometry; Ocean temperature; Radar measurements; Sea surface; Spatial resolution; Vegetation mapping;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium, 1996. IGARSS '96. 'Remote Sensing for a Sustainable Future.', International
Conference_Location :
Lincoln, NE
Print_ISBN :
0-7803-3068-4
Type :
conf
DOI :
10.1109/IGARSS.1996.516745
Filename :
516745
Link To Document :
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