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Modeling aboveground biomass in dense tropical submontane rainforest using airborne laser scanner data

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dc.creator Hansen, Endre Hofstad
dc.creator Gobakken, Terje
dc.creator Bollandsås, Ole Martin
dc.creator Zahabu, Eliakimu
dc.creator Næsset, Erik
dc.date 2022-06-08T09:08:29Z
dc.date 2022-06-08T09:08:29Z
dc.date 2015-01-14
dc.date.accessioned 2022-10-25T08:53:32Z
dc.date.available 2022-10-25T08:53:32Z
dc.identifier 2072-4292
dc.identifier https://www.suaire.sua.ac.tz/handle/123456789/4218
dc.identifier.uri http://hdl.handle.net/123456789/93849
dc.description Successful implementation of projects under the REDD+ mechanism, securing payment for storing forest carbon as an ecosystem service, requires quantification of biomass. Airborne laser scanning (ALS) is a relevant technology to enhance estimates of biomass in tropical forests. We present the analysis and results of modeling aboveground biomass (AGB) in a Tanzanian rainforest utilizing data from a small-footprint ALS system and 153 field plots with an area of 0.06–0.12 ha located on a systematic grid. The study area is dominated by steep terrain, a heterogeneous forest structure and large variation in AGB densities with values ranging from 43 to 1147 Mg·ha −1 , which goes beyond the range that has been reported in existing literature on biomass modeling with ALS data in the tropics. Root mean square errors from a 10-fold cross-validation of estimated values were about 33% of a mean value of 462 Mg·ha −1 . Texture variables derived from a canopy surface model did not result in improved models. Analyses showed that (1) variables derived from echoes in the lower parts of the canopy and (2) canopy density variables explained more of the AGB density than variables representing the height of the canopy.
dc.format application/pdf
dc.language en
dc.publisher MDPI [Commercial Publisher]
dc.relation Remote Sens.;doi:10.3390/rs70100788
dc.subject aboveground biomass;
dc.subject airborne laser scanning;
dc.subject nopy surface;
dc.subject LiDAR;
dc.subject texture variables;
dc.subject tropical rainforest
dc.title Modeling aboveground biomass in dense tropical submontane rainforest using airborne laser scanner data
dc.type Article


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