Remote Sensing for Agricultural Land Use Changes and Sustainability Monitoring in Sudan

• Main Author: Olagunju, Emmanuel Gbenga
• Format: Others
• Language: English
• Published: Linköpings universitet, Institutionen för datavetenskap 2008
• Subjects: Agriculture; GDP; irrigation; population remote sensing; sustainable development; GIS; NDVI; environmental sustainability and biodiversity; Computer Sciences; Datavetenskap (datalogi)
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-15279

The remote sensing technology is increasingly being used to study land use and vegetation cover changes and identify changes that has occur through different land use activities which may have negative impact on the sustainability of the environment, biodiversity protection and conservation. With increase in population growth rate in Sudan, there has been an increase for food crop production with agriculture playing a prominent role in livelihood security for the increasing population.   The increase use of irrigation and mechanisation has brought about an increase in demand for agricultural land use in Sudan with the conversion of other land use types and vegetation for agricultural land use. This does have effect and impact on the vegetation and environment with the country highly exposed to the incidence of environmental and social hazards and disasters including drought and desertification, deforestations, floods, loss of biodiversity, ethnic conflicts and poverty.   The research study work focused on agricultural land use changes in the country with the aim of investigating the agricultural land use changes that has occurred in the country from 1986 to 2002 using the remote sensing technique. This is important for agricultural land use planning and sustainability monitoring to reduce the negative impact of agricultural land use for crop production and increase long term resource use and environmental sustainability. Two remote sensing methods were used for the classification analysis to identify the land use changes namely the NDVI and the parallelepiped classification techniques. The NDVI method was used to identify the changes in the agricultural land use vegetation cover classes and determine the magnitude of changes in land area use that has occurred from 1986 to 2002 when the former and latter remote sensing images were acquired. The parallelepiped classification technique was however used to identify the aggregate agricultural land use changes in the area of study and conversion to and from other categories of land use. A qualitative analytic technique was also used to identify the possible causes of the changes that have occurred in Sudan in the study period using empirical materials.   The research study result gives information on the role the remote sensing technology can play in analyzing land use cover changes for agricultural land use sustainability monitoring.