4.7 Article

Biomass estimation with high resolution satellite images: A case study of Quercus rotundifolia

Journal

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.isprsjprs.2014.12.004

Keywords

Quercus rotundifolia; Biomass; Forest inventory; QuickBird image

Funding

  1. Programa Operativo de Cooperacao Transfronteirico Espanha - Portugal (POCTEP)
  2. Altercexa - Medidas de Adaptacion y Mitigacion del Cambio Climatico a Traves del Impulso de las Energias Alternativas en Centro, Alentejo y Extremadura [0317_Altercexa_I_4_E, 0406_ALTERCEXA_II_4_E]
  3. FEDER Funds through the Operational Program for Competitiveness Factors - COMPETE and National Funds through FCT - Foundation for Science and Technology [PEst-OE/AGR/UI0115/2014]

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Forest biomass has had a growing importance in the world economy as a global strategic reserve, due to applications in bioenergy, bioproduct development and issues related to reducing greenhouse gas emissions. Current techniques used for forest inventory are usually time consuming and expensive. Thus, there is an urgent need to develop reliable, low cost methods that can be used for forest biomass estimation and monitoring. This study uses new techniques to process high spatial resolution satellite images (0.70 m) in order to assess and monitor forest biomass. Multi-resolution segmentation method and object oriented classification are used to obtain the area of tree canopy horizontal projection for Quercus rotundifolia. Forest inventory allows for calculation of tree and canopy horizontal projection and biomass, the latter with allometric functions. The two data sets are used to develop linear functions to assess above ground biomass, with crown horizontal projection as an independent variable. The functions for the cumulative values, both for inventory and satellite data, for a prediction error equal or smaller than the Portuguese national forest inventory (7%), correspond to stand areas of 0.5 ha, which include most of the Q. rotundifolia stands. (C) 2014 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.

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