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Estimation of Acacia senegal Tree Biomass Using Allometric Equation and Remote Sensing, North Kordofan State, Sudan
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Volume 3, 2015
Issue 6 (December)
Pages: 222-226   |   Vol. 3, No. 6, December 2015   |   Follow on         
Paper in PDF Downloads: 78   Since Oct. 24, 2015 Views: 2110   Since Oct. 24, 2015
Hatim Mohamed Ahmed Elamin, Institute of Gum Arabic Research and Desertification Studies, University of Kordofan, Elobeid, Sudan.
Hassan Elnour Adam, Department of Forestry and Range Sciences, Faculty of Natural Resources and Environmental Studies, University of Kordofan, Elobeid, Sudan.
Mohamed El Nour Taha, Department of Forestry and Range Sciences, Faculty of Natural Resources and Environmental Studies, University of Kordofan, Elobeid, Sudan.
Elmar Csaplovics, Institute of Photogrammetry and Remote Sensing (IPF), Technical University of Dresden, Dresden, Germany.
The current study was conducted in Um Habila Reserved Forest (2.7 square Kilometres) which is located in El Rahad Locality in North Kordofan State, Sudan.It dealt principally with the estimation of woody biomass of Acacia senegal trees by applying allometric equations for ground data combined with satellite data sets.Primary data were obtained by the application of random sampling techniques, counting a total of 27 trees. The tree coordinates and diameters were recorded. Remote sensing data were acquired from SPOT-5 (08.11.2009) earth observation satellite and integrated with the in-situ data. The study findings revealed that the mean diameter of Acacia senegal tree was 7.31 cm ± 1.68 cm. The tree above ground biomass (TAGB), tree below ground biomass (TBGB) and total tree biomass (TTB) of Acacia senegal were found to be 15.15± 9.01 kg, 3.03 ±1.80 kg, and 18.18±10.81 kg, respectively. Remotely sensed data were integrated with the terrestrial method for creating and correlating the relationship between them, resulting in development of the power model based on spectral reflectance (IR) with adjusted R2 of 0.504. The application of allometric equations is useful as non-destructive method for local biomass estimations and the application of remote sensing is recommended for biomass estimation in wide coverage areas.
Tree Biomass, Acacia senegal, Tree Coordinates, Remote Sensing, Satellite Data Sets, North Kordofan
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