ESTIMATION OF ABOVE GROUND FOREST BIOMASS USING ULTRA HIGH RESOLUTION UAV IMAGES: A CASE STUDY FROM BARANDABHAR FOREST, NEPAL
- 1Department of Geomatics Engineering, School of Engineering, Kathmandu University, Nepal
- 2International Maize and Wheat Improvement Center (CIMMYT), Nepal
Keywords: Forest Biomass, UAV, Image Segmentation, Visible-NIR Sensor
Abstract. Forest biomass is the sum of above ground living organic material contained in trees which is expressed as dry weight per unit area. Forest biomass acts as substantial terrestrial carbon sinks, they are estimated to absorb 2.7 Petagrams of carbon per year, as such accurate estimation of forest carbon stock is very important. The estimation of biomass is also important because of its application in commercial exploitation as well as in global carbon cycle. Particularly in the latter context, the estimation of the total above-ground biomass (TAGB) with sufficient accuracy is vital in reporting the spatial and temporal state of forest under the United Nations Framework Convention on Climate Change (UNFCCC), Reducing Emissions from Deforestation in Developing Countries (REDD). In this research, tree height, DBH and crown cover were measured using field instruments. Individual ultra-high-resolution UAV images acquired using customized Visible-NIR, were georeferenced and tree crown were extracted using multi-resolution segmentation. A regression equation between field measured biomass and Crown Projection Area (CPA) was developed. The paper presents results from Barandabhar Forest of Chitwan District, Nepal. RMSE of ortho-mosaic was found to be 18 cm. While R2 value of 89% was obtained for relationship between DBH and biomass, that of 61% was attained for relationship between CPA and biomass.