Biomass estimation in a boreal forest from TanDEM-X data, lidar DTM, and the interferometric water cloud model

Artikel i vetenskaplig tidskrift, 2017

The semi-empirical Interferometric Water Cloud Model, IWCM, is used to estimate above ground forest biomass, AGB, in northern Sweden, Krycklan (64 degrees N 20 degrees E). The results are based on separate analysis of 14 TanDEM-X ac-quisitions from 2011 to 2014 and a Lidar digital terrain model (DTM). 29 stands covering 272 ha and with AGB < 183 Mg/ha, and 619 stands with area > 1 ha covering 3166 ha and with AGB < 291Mg/ ha have been analyzed. In situ and airborne lidar scanning, ALS, data from the BioSAR 2008 experiment are used as reference. AGB and forest height are estimated using a new optimization method for determining IWCM parameters. Allometric equations are used to describe the inter-dependency between forest height, biomass, area-fill factor, and stem volume. No local training data from the investigated area are used to determine model parameters. For the 29 stands, the relative RMSE for biomass estimated using the proposed method varied between 15.8% and 21.2% (r(2) between 0.82 and 0.88) and between 9.9% and 16.0% for height (r(2) between 0.84 and 0.89). Dependence of model parameters on temperature and precipitation as well as height of ambiguity are investigated. A method based on look-up table for biomass estimation from phase height is proposed. The method is used over an area of 68 km(2) for one TanDEM-X acquisition from 2011-06-04 and the results are compared with an ALS biomass map from August 2008. Good agreement is observed, as well as high potential for clear-cut detection. (C) 2017 The Authors. Published by Elsevier Inc.