TY - GEN
T1 - An estimation of tropical forest biomass with a combination of JERS-1 and Landsat TM data
AU - Cutler, M. E. J.
AU - Foody, G. M.
AU - Boyd, D. S.
PY - 2009
Y1 - 2009
N2 - The use of remote sensing to estimate biomass in tropical forests has met with varying degrees of success. Previous work has demonstrated that reliable estimates of biomass can be made with Artificial Neural Networks, using data from single sites and with a degree of transferability between other tropical forests. Here JERS-1 data for three sites is combined with Landsat TM images, with the aim of improving the spatial transferability of the method. The image data were compared to ground data from sites in Malaysia, Brazil and Thailand using a feed-forward artificial neural network. The SAR data were weakly correlated with biomass, and when combined with optical data led to a marginal increase in the correlation coefficient for each site individually. However, improved relationships were observed when combined SAR/optical data for all sites were presented to the network, thus indicating marginally improved transferability in the method compared to using optical data alone.
AB - The use of remote sensing to estimate biomass in tropical forests has met with varying degrees of success. Previous work has demonstrated that reliable estimates of biomass can be made with Artificial Neural Networks, using data from single sites and with a degree of transferability between other tropical forests. Here JERS-1 data for three sites is combined with Landsat TM images, with the aim of improving the spatial transferability of the method. The image data were compared to ground data from sites in Malaysia, Brazil and Thailand using a feed-forward artificial neural network. The SAR data were weakly correlated with biomass, and when combined with optical data led to a marginal increase in the correlation coefficient for each site individually. However, improved relationships were observed when combined SAR/optical data for all sites were presented to the network, thus indicating marginally improved transferability in the method compared to using optical data alone.
UR - http://www.scopus.com/inward/record.url?scp=84879896452&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84879896452
SN - 093291313X
SN - 9780932913135
T3 - Proceedings of the International Symposium on Remote Sensing of Environment
SP - 262
EP - 265
BT - Sustaining the Millennium Development Goals
PB - International Center for Remote Sensing of Environment,
CY - Tucson
T2 - 33rd International Symposium on Remote Sensing of Environment, ISRSE 2009
Y2 - 4 May 2009 through 8 May 2009
ER -