Title of article
Measuring biomass changes due to woody encroachment and deforestation/degradation in a forest–savanna boundary region of central Africa using multi-temporal L-band radar backscatter
Author/Authors
Mitchard، نويسنده , , E.T.A. and Saatchi، نويسنده , , S.S. and Lewis، نويسنده , , S.L. and Feldpausch، نويسنده , , T.R. and Woodhouse، نويسنده , , I.H. and Sonké، نويسنده , , B. and Rowland، نويسنده , , C. and Meir، نويسنده , , P.، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2011
Pages
13
From page
2861
To page
2873
Abstract
Satellite L-band synthetic aperture radar backscatter data from 1996 and 2007 (from JERS-1 and ALOS PALSAR respectively), were used with field data collected in 2007 and a back-calibration method to produce biomass maps of a 15 000 km2 forest–savanna ecotone region of central Cameroon. The relationship between the radar backscatter and aboveground biomass (AGB) was strong (r2 = 0.86 for ALOS HV to biomass plots, r2 = 0.95 relating ALOS-derived biomass for 40 suspected unchanged regions to JERS-1 HH). The root mean square error (RMSE) associated with AGB estimation varied from ~ 25% for AGB < 100 Mg ha− 1 to ~ 40% for AGB > 100 Mg ha− 1 for the ALOS HV data. Change detection showed a significant loss of AGB over high biomass forests, due to suspected deforestation and degradation, and significant biomass gains along the forest–savanna boundary, particularly in areas of low population density. Analysis of the errors involved showed that radar data can detect changes in broad AGB class in forest–savanna transition areas with an accuracy > 95%. However, quantitative assessment of changes in AGB in Mg ha− 1 at a pixel level will require radar images from sensors with similar characteristics collecting data from the same season over multiple years.
Keywords
Degradation , Forest–savanna boundary , REDD , Woody encroachment , Radar , CAMEROON , Change detection , ALOS PALSAR , JERS-1 , Ecotone , Aboveground biomass , SAR , Deforestation
Journal title
Remote Sensing of Environment
Serial Year
2011
Journal title
Remote Sensing of Environment
Record number
1631111
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