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Improving spatial distribution estimation of forest biomass with geostatistics: A case study for Rondônia, Brazil

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  • Sales, Marcio H.
  • Souza, Carlos M.
  • Kyriakidis, Phaedon C.
  • Roberts, Dar A.
  • Vidal, Edson

Abstract

Mapping aboveground forest biomass is of fundamental importance for estimating CO2 emissions due to land use and land cover changes in the Brazilian Amazon. However, existing biomass maps for this region diverge in terms of the total biomass estimates derived, as well as in the spatial patterns of mapped biomass. In addition, no regional or location-specific measure of reliability accompanies most of these maps. In this study, 330 one-hectare plots from the RADAMBRASIL survey, acquired over and along areas adjacent to the state of Rondônia, were used to generate a biomass map over the entire region using geostatistics. The RADAMBRASIL samples were used to generate a biomass map, along with a measure of reliability for each biomass estimate at each location, using kriging with external drift with elevation, vegetation type and soil texture considered as biomass predictor variables. Cross-validation was performed using the sample plots to compare the performance of kriging against a simple biomass estimation using the sample mean. Overall, biomass varied from 225 to 486Mgha−1, with a local standard deviation ranging from 62 to 202Mgha−1. Large uncertainty values were obtained for regions with low sampling density, in particular in savanna areas. The geostatistical method adopted in this paper has the potential to be applied over the entire Brazilian Amazon region to provide more accurate local estimates of biomass, which would aid carbon flux estimation, along with measures of their reliability, and to identify areas where more sampling efforts should be concentrated.

Suggested Citation

  • Sales, Marcio H. & Souza, Carlos M. & Kyriakidis, Phaedon C. & Roberts, Dar A. & Vidal, Edson, 2007. "Improving spatial distribution estimation of forest biomass with geostatistics: A case study for Rondônia, Brazil," Ecological Modelling, Elsevier, vol. 205(1), pages 221-230.
    • Handle: RePEc:eee:ecomod:v:205:y:2007:i:1:p:221-230
    DOI: 10.1016/j.ecolmodel.2007.02.033
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    References listed on IDEAS

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    1. R. A. Houghton & D. L. Skole & Carlos A. Nobre & J. L. Hackler & K. T. Lawrence & W H. Chomentowski, 2000. "Annual fluxes of carbon from deforestation and regrowth in the Brazilian Amazon," Nature, Nature, vol. 403(6767), pages 301-304, January.
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    Cited by:

    1. Stéphane Guitet & Bruno Hérault & Quentin Molto & Olivier Brunaux & Pierre Couteron, 2015. "Spatial Structure of Above-Ground Biomass Limits Accuracy of Carbon Mapping in Rainforest but Large Scale Forest Inventories Can Help to Overcome," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-22, September.
    2. Claudio Petucco & Antonello Lobianco & Sylvain Caurla, 2020. "Economic Evaluation of an Invasive Forest Pathogen at a Large Scale : The Case of Ash Dieback in France," Post-Print hal-02625280, HAL.
    3. Viana, H. & Aranha, J. & Lopes, D. & Cohen, Warren B., 2012. "Estimation of crown biomass of Pinus pinaster stands and shrubland above-ground biomass using forest inventory data, remotely sensed imagery and spatial prediction models," Ecological Modelling, Elsevier, vol. 226(C), pages 22-35.
    4. Claudio Petucco & Antonello Lobianco & Sylvain Caurla, 2020. "Economic Evaluation of an Invasive Forest Pathogen at a Large Scale : The Case of Ash Dieback in France," Post-Print hal-03639337, HAL.

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