Examination of the amount of GEDI data required to characterize central Africa tropical forest aboveground biomass at REDD+ project scale in Mai Ndombe province

Abstract

The Global Ecosystem Dynamics Investigation (GEDI) is the first spaceborne LiDAR designed to improve quantification of vegetation structure and forest aboveground biomass (AGB) including in the tropics where forest AGB inventory data are limited. GEDI is a sampling instrument on the International Space Station (ISS) and does not provide data on a regular, systematic basis. Reducing Emissions from Deforestation and Degradation and enhancement of carbon stocks (REDD+) projects require forest AGB inventories to quantify avoided carbon emissions achieved by conserving forest biomass. Although there is high confidence that GEDI can retrieve measurements that allow estimation of AGB at scale, less is known about how well its operational deployment performs for measurement of AGB to support REDD+ projects. This includes an understanding of the appropriate time period required to collect sufficient GEDI observations for reliable forest AGB assessment. This paper describes the first study to examine the amount of GEDI data needed to characterize tropical forest AGB at REDD+ project scale. In tropical Africa, the average REDD+ project size documented by the Center for International Forestry Research is equivalent to a square area of approximately 50 × 50 km (250,000 ha). Recently available good quality GEDI footprint-level AGB product data acquired over a 31 month period over Mai Ndombe province in the west of the Democratic Republic of the Congo were considered. A global 30 m percent tree cover product, updated with contemporary mapped forest cover loss, was used to map the intact forest across the province. Fifteen 50 × 50 km test sites, representing example REDD+ project areas with >80% forest cover and good quality AGB forest footprint data distributed across each site, were selected. The sites were selected from five AGB stratum defined from the GEDI data, and with three sites selected per stratum that had low, medium and high semivariogram sill values that reflect increasing within-site AGB spatial variation. The overall mean GEDI AGB (OMGA) was derived from all the good quality forest GEDI footprint AGB values acquired over the 31 months of GEDI operation at each site. The expected minimum number of GEDI orbits ($n_{orbits}^p$) required to characterize the OMGA to within p = ±5%, ±10%, and ±20% was derived by considering different combinations of GEDI orbits randomly selected from the 31 months of GEDI data. The expected minimum number of days ($n_{days}^p$) required to characterize the AGB over each site was derived by multiplying the site $n_{orbits}^p$ values with a scalar coefficient of 13.03 days. The scalar coefficient was found by counting the temporal intervals between successive GEDI orbits containing good quality forest AGB data and is equivalent to the average number of days required to obtain a GEDI orbit containing good quality forest AGB data at 50 × 50 km scale. Among the 15 sites, observation periods ranging from 65 to 221 days (0.18 – 0.61 years), 143 – 534 days (0.39 – 1.46 years), and 390 – 742 days (1.07 – 2.03 years) were required to characterize the AGB to within ±20%, ±10%, and ±5% of the site OMGA, respectively. The Intergovernmental Panel on Climate Change (IPCC) recommended accuracy requirement for forest AGB estimates is 10%. Thus, to meet this accuracy requirement the findings of this study indicate that at least 534 days (1.46 years) would be required for REDD+ site monitoring using GEDI in Mai Ndombe province. In other central African tropical forest localities these observations periods may be different depending on the forest AGB and spatial variation, cloud cover, ephemeral surface water presence, and GEDI AGB retrieval sensitivity to the forest conditions.