A cost effective and operational methodology for wall to wall Above Ground Biomass (AGB) and carbon stocks estimation and mapping: Nepal REDD+

Abstract:

Nepal is a landlocked country with 39% forest cover of the total land area (147,181 km²). Under the Forest Carbon Partnership Facility (FCPF) and implemented by the World Bank (WB), Nepal chosen as one of four countries best suitable for results-based payment system for Reducing Emissions from Deforestation and Forest Degradation (REDD and REDD+) scheme. At the national level Landsat based, from 1990 to 2000 the forest area has declined by 2%, i.e. by 1467 km², whereas from 2000 to 2010 it has declined only by 0.12% i.e. 176 km². A cost effective monitoring and evaluation system for REDD+ requires a balanced approach of remote sensing and ground measurements.

This paper provides, for Nepal a cost effective and operational 30 m Above Ground Biomass (AGB) estimation and mapping methodology using freely available satellite data integrated with field inventory. Leaf Area Index (LAI) generated based on propose methodology by Ganguly et al. (2012) using Landsat-8 the OLI cloud free images. To generate tree canopy height map, a density scatter graph between the Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud, and Land Elevation Satellite (ICESat) estimated maximum height and Landsat LAI nearest to the center coordinates of the GLAS shots show a moderate but significant exponential correlation (31.211*LAI^0.4593, R²= 0.33, RMSE=13.25 m). From the field well distributed circular (750m² and 500m²), 1124 field plots (0.001% representation of forest cover) measured which were used for estimation AGB (ton/ha) using Sharma et al. (1990) proposed equations for all tree species of Nepal. A satisfactory linear relationship (AGB = 8.7018*H_max-101.24, R²=0.67, RMSE=7.2 ton/ha) achieved between maximum canopy height (H_max) and AGB (ton/ha). This cost effective and operational methodology is replicable, over 5-10 years with minimum ground samples through integration of satellite images. Developed AGB used to produce optimum fuel wood scenarios using population and road accessibility datasets.