Fusing radar and optical remote sensing for biomass prediction in mountainous tropical forests

Melissa Fedrigo, Patrick Meir, Douglas Sheil, Miriam Van Heist, Iain H. Woodhouse, Edward T.A. Mitchard

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Field measured estimates of aboveground biomass (AGB) in the mountainous region of Bwindi Impenetrable National Park ('Bwindi'), Uganda were used to train remote sensing models in order to estimate AGB within the park. AGB estimates were extrapolated using dual-polarization radar satellite data from ALOS PALSAR, optical imagery from Landsat 7 and a fusion of both, and compared to field estimates as indicators of the model prediction strength. Significant geolocation errors existed in the radar data due to the extreme terrain. Fusing the radar and optical data using the non-parametric algorithm Random Forest (RF) in R, provided lower error than using either radar or optical data alone (RMSE ∼120 Mg ha-1), however, saturation at higher biomass levels was evident. The AGB in Bwindi was estimated at 8.91 Tg ± 0.39 Tg (260.9 Mg ha-1 ± 11.4 Mg ha-1).

Original languageEnglish
Title of host publication2013 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 - Proceedings
Pages975-978
Number of pages4
DOIs
Publication statusPublished - 1 Dec 2013
Event2013 33rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 - Melbourne, VIC, Australia
Duration: 21 Jul 201326 Jul 2013

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)

Conference

Conference2013 33rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013
Country/TerritoryAustralia
CityMelbourne, VIC
Period21/07/1326/07/13

Keywords

  • ALOS PALSAR
  • Biomass
  • forestry
  • radar remote sensing
  • tropical forest

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