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Airborne MSS data to estimate GLAI

 

作者: P. J. CURRAN,   H. D. WILLIAMSON,  

 

期刊: International Journal of Remote Sensing  (Taylor Available online 1987)
卷期: Volume 8, issue 1  

页码: 57-74

 

ISSN:0143-1161

 

年代: 1987

 

DOI:10.1080/01431168708948615

 

出版商: Taylor & Francis Group

 

数据来源: Taylor

 

摘要:

Airborne multispectral scanner ( MSS) data, collected in June 1984, were used to estimate the green leaf area index ( GLAI) for 60 km2 of grassland. The methodology involved (i) radiometric and atmospheric correction, (ii) production of a vegetation index image, (iii) calculation of a calibration relationship between a vegetation index and GLAI, (iv) production of an image of estimated GLAI by inversion of the calibration relationship in (iii), and (v) accuracy assessment. The initial accuracy of GLAI estimation was ± 0-75 GLAI for an area and 17-40 per cent at the 95 per cent confidence level, for a six-class classification. Refinements to the methodology were evaluated by their effect upon the accuracy of GLAI estimation. In order of increasing importance these refinements were: suppression of environmental effects on the remotely sensed data, processing on a per-field rather than a per-pixel basis, calculation of the calibration relationship between a vegetation index and GLAI, using ground-based radiometric data and a modified least-squares regression up to the asymptote of the vegetation index and allowance for error in the ground data. By utilizing all of these refinements the accuracy of GLAI estimation increased to + 009 GLAI for an area and 60-82 per cent at the 95 per cent confidence level, for a five-class classification.

 

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