Author
Listed:
- Omolere OS
- Alaga AT
- Mohammed SO
- Gajere EN
Abstract
This paper examined the causes and extent of desertification in Sokoto state of Nigeria from 1986 to 2015 and also make prediction of how the land use and Landcover of the area will look like in next twenty years (20 years). The data used for examining the extent of desertification were downloaded from USGS. The main objective of this research work is to examine the extent of desertification and determine the primary agent of desertification and to predict how the land use and land cover of the area will look like in the nearest feature. A well-structured questionnaire was used to collect data in order to know the resources being mined in the study area. The result of the questionnaire was analyze in SPSS using regression analysis in order to know the relationship between the local population and the resources being harvested. LandSat images for 1986, 2000 and 2015 were used to examine the extent of desertification. The classified images for 1986 and 2015 were used to predict the land use and land cover in the next 20years. The paper suggests for massive tree plantings in the study area and Nigeria in general. The Federal and State Departments of Forestry need to be empowered with adequate revenue for massive reforestation programme. Regulation to discourage dependence on wood for local energy should be put in place, while other sources of energy such as kerosene should be adequately provided. Grazing land should also be created for the Fulani headmen to avoid the destruction of farmland and environment.
Suggested Citation
Omolere OS & Alaga AT & Mohammed SO & Gajere EN, 2016.
"Geospatial Assessment of Desertification and Predictive Modeling in North West Nigeria - A Case Study of Sokoto,"
International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 1(3), pages 41-46, December.
Handle:
RePEc:jbh:ijsrcs:v1:y2016:i3:id:hcseit16138
Note: Article URL: https://ijsrcseit.com/CSEIT16138
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