Welcome to Open Science
Contact Us
Home Books Journals Submission Open Science Join Us News Unsubscribe Page
Estimation of Acacia senegal Tree Biomass Using Allometric Equation and Remote Sensing, North Kordofan State, Sudan
Current Issue
Volume 3, 2015
Issue 6 (December)
Pages: 222-226   |   Vol. 3, No. 6, December 2015   |   Follow on         
Paper in PDF Downloads: 72   Since Oct. 24, 2015 Views: 1120   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
Ballal, M. E. (2002), “Yield Trends of Gum Arabic from Acacia senegal as related to some Environmental and Managerial Factors”. PhD Thesis, University of Khartoum, Sudan, pp 105.
Brown, S. (1997), “Estimating Biomass and Biomass Change of Tropical Forests”: A primer FAO For. Pap. 134. Rome: Food and Agriculture Organization of the United Nations. 55 p. [Online publication].
Brown, S.; Gillespie, A. J. R.; Lugo, A. E. (1989), “Biomass Estimation Methods for Tropical Forests with Applications to Forest Inventory Data”. Forest Science, Vol. 35, No. 4, pp. 881-902.
De Gier, A.(2003), “A new approach to woody biomass assessment in woodlands and shrublands”. In: P. Roy (Ed), Geoinformatics for Tropical Ecosystems, India, pp. 161-198.
FAO, Food and Agriculture Organization of the United Nations (1997), “Estimating Biomass and Biomass Change of Tropical Forests”. Forestry Paper 134. Rome, Italy.
Franklin, S. E. (2001), “Remote Sensing for Sustainable Forest Management”. Book page 57-69, Chapter 4. Lewis Publishers. Boca Raton. Island Press, Washington DC.
Hoover, Coeli; Rebain, M. and Stephanie, A. (2011), “Forest Carbon Estimation Using the Forest Vegetation Simulator”: Seven Things You Need to Know. Published by: USDA Forest Service, 11 Campus BLVD., Suite 200, Newtown. Square, PA 19073-3294.
Kasischke, E. S., Melack, J. M. and Craig Dobson, M., 1997. The use of imaging radars for ecological applications--A review. Remote Sensing of Environment, 59(2): 141-156.
Köhl, M., Magnussen, S. M. and Marchetti, M. (2006), “Sampling Methods, Remote Sensing and GIS Multi-resources Forest Inventory”. Springer-Verlag Berlin Heidelberg, Germany.
Longley, H. G.; Tang, G Li, X. and Heilig, G. K. (2007), “Socio-economic Driving Forces of the Land Use Change in Kunshan, the Yangtze River Delta Economic Area of the China”. Journal of Environmental Management, 83 (3): 351-364.
Losi, C. J.; Siccama, T. G.; Condit, R. and Morales, J. E. (2003), “Analysis of Alternative Methods for Estimating Carbon Stock in Young Tropical Plantations”. Forest Ecology and Management, 184 (1-3): 355-368.
Lu, D., (2006). The potential and challenge of remote sensing-based biomass estimation. International Journal of Remote Sensing, 27(7-10), 1297-1328.
MacDicken, K. (1997), “A Guide to Monitoring Carbon Storage in Forestry and Agroforestry Projects”. Book pages 13-14. Winrock International Institute for Agricultural Development, Arlington, USA.
Murali, K.S. and Bhat, D. M. (2005), Biomass Estimation Equations for Tropical Deciduous and Evergreen Forests. Int. J. Agricultural Resources, Governance and Ecology, Vol. 4, No. 1, pp. 81-92.
Nelson, B.W.; Mesquita, R.; Pereira, J.L.G.; de Souza, S.G.A.; Batista, G. T.; Couto, L. B. (1999), Allometric Regressions for Improved Estimate of Secondary Forest Biomass in the Central Amazon. For Ecol Manage 117: 149-167.
Parresol, R. (1999), “Assessing Tree and Stand Biomass: A Review with Examples and Critical Comparisons”. Forest Science, 45: 573-593. Cited from: Samalca, Irvin K, 2007. Estimation of forest biomass and its error, A case in Kalimantan, Indonesia, MSc. Thesis submitted to International Institute for Geo-Information Science and Earth Observation, Enschede, The Netherlands.
Sahni, K. C. (1968), “Important Trees of the Northern Sudan, pp. 1-7”. UNDP and FAO of the United Nations. Forestry Research and Education Centre, Khartoum, Sudan.
Vogt, K. (1995), “A Field Workers Guide to the Identification, Propagation and Uses of Common Trees and Shrubs of Dry Land Sudan”. SOS Sahel International, London. Khartoum, Sudan.
Webb, D. B; Smith, J. P. and Henman, G. Sian (1984), “Tropical Forestry Papers No. 15 2nd edition”, revised: A Guide to Species Selection for Tropical and Sub- Tropical Plantations.
Zheng, Daolan; Rademache, John; Chen, Jiquan; Crow, Thomas; Bresee, Mary; Moine, James Le; and Ryu, Soung-Ryoul (2004), “Estimating Aboveground Biomass using Landsat 7 ETM+ Data across Managed Landscape in northern Wisconsin, USA”. Cited from: Samalca, Irvin K, 2007. Estimation of Forest Biomass and its Error, A case in Kalimantan, Indonesia, MSc. Thesis submitted to International Institute for Geo-Information Science and Earth Observation, Enscheda, the Netherlands.
Open Science Scholarly Journals
Open Science is a peer-reviewed platform, the journals of which cover a wide range of academic disciplines and serve the world's research and scholarly communities. Upon acceptance, Open Science Journals will be immediately and permanently free for everyone to read and download.
Office Address:
228 Park Ave., S#45956, New York, NY 10003
Phone: +(001)(347)535 0661
Copyright © 2013-, Open Science Publishers - All Rights Reserved