Estimation of Aboveground Biomass of Acacia senegal (Willd) Stands in Sheikan Reserved Forest, North Kordofan State, Sudan Using Remote Sensing, Dr Hassan Adam, Prof. Udo Schickhoff, FathAlrahman Mohamed
Dr Hassan Elnour Adam
Center for Earth System Research and Sustainability (CEN)
University of Hamburg, Hamburg, Germany
Faculty of Natural Resources and Environmental Studies
University of Kordofan
Elobeid
Sudan
ORCID: 0000-0003-4451-8517
Professor Udo Schickhoff
Center for Earth System Research and Sustainability (CEN)
University of Hamburg
Hamburg
Germany
ORCID: 0000-0003-1502-936X
FathAlrahman Ahmed Mohamed
National Forest Corporation (FNC), South Kordofan State
Kaduglei
Sudan
Purpose: The aim is to estimate the aboveground biomass of Acacia senegal (Willd) stands using terrestrial inventory and remote sensing data. Moreover, to investigate the relationship between aboveground biomass and growth parameters of Acacia senegal trees.
Methodology: In a ground inventory, 40 square sample plots (0.09 ha for each) were systematically distributed with a spacing of 750x1500 m. The coordinates of each plot center, diameter at breast height, tree height, and tree crown diameters were registered. The values of Normalized Difference Vegetation Index (NDVI) were extracted from the Landsat 8 (OLI) image (2015). Remote sensing data were processed by ERDAS 10.3 software, while ground measurement data were analyzed by Excel software 2007 and SPSS 18. Nine regression models for Acacia senegal biomass on the stand level were developed and validated.
Findings: Showed a highly significant difference (P-value = 0.02) between the NDVI value and the above-ground biomass of Acacia senegal stands. The linear regression model (R² = 0.70) based on NDVI was selected for estimating the aboveground biomass of Acacia senegal stands in the Sheikan Reserved Forest. The linear relationship between above-ground biomass and tree volume and number of trees/ha was found with R2 values of 0.8 and 0.9, respectively. The study also estimated the tree volume (1.3 m3/ha), maximum above-ground biomass (8.22 t/ha), and total maximum biomass (10.53 t/ha).
Practical Implications: The study developed a linear regression model based on NDVI for the estimation of above-ground biomass of Acacia senegal stands in Sheikan locality, Sudan.
Keywords: Acacia Senegal, Biomass, Kordofan, Modelling, Remote Sensing.