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Mapping forest biomass through digital processing of IRS-IA data

 

作者: A. K. TIWARI,  

 

期刊: International Journal of Remote Sensing  (Taylor Available online 1994)
卷期: Volume 15, issue 9  

页码: 1849-1866

 

ISSN:0143-1161

 

年代: 1994

 

DOI:10.1080/01431169408954212

 

出版商: Taylor & Francis Group

 

数据来源: Taylor

 

摘要:

The present study deals with the mapping of forest basal cover and biomass using IRS data. IRS-LISS-I data were classified into forest types and crown cover categories. A stand biomass was computed for selected sites using density, basal cover data and biomass estimation equations. Allometric relations were developed between crown cover and basal cover and between crown cover and biomass. Using these relations basal cover and biomass were computed for each crown cover class of each forest type. The classes having identical biomass were merged together. Total biomass for each forest type was computed by using mean values and the aerial extent. The average total above-ground biomass density between forest types ranged between 52–36tha-1∥Plantations) and 371–08tha-1(Sal forest). The estimates of the study compared well with the estimates for 19 sites computed through conventional techniques. The method described in the present study is expected to play a significant role in global biomass estimations.

 

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