Application of GIS and RS in Rangeland Management

This study uses Landsat data and Tasseled Cap Transformation green vegetation index (GVI) technique to assess the condition of rangeland resources in the Sahel region of West Africa. Three representative zones in the sahelian region of Mali, Burkina Faso and Niger were selected for this study. Satellite data covering fifteen years period was used to assess the extent to which rangeland resources have degraded on a country by country basis between 1984 and 1999. The study results show all three countries in the study area experienced vegetation decline. However, loss of vegetation cover was most pronounced in the northern part of the study area than in the south. This decline could be attributed to changing temperature and rainfall gradients.

This article investigates and analyzes land use/land cover change in Ghubaysh area-Western Sudan during the period 1973-2010. The main objective of the article is to detect and identify land cover changes that have occurred during the last four decades. Multi-temporal satellites images (MSS, TM and ETM+) of 1973, 1987 and 2006 were used for data collection. The EARDAS Imagine classifier tool 9.2 and ArcGIS 10.2 have been used in the data analysis. Cultivated area, Wadis, shrubs, grass and forest were the most dynamic parameters used in land cover classification. Results showed high level of accuracy (98.2%, 96.3 and 89.6%) for the selected images for the years 1973, 1987 and 2006, respectively. The results also showed that the study area was once very rich in vegetation cover consisted of grass shrubs and forest which covered 86.7% of the study area. A prolonged and unsystematic change in land cover was reported. The agricultural area increased by a rate of +1.8% and shrubs increased by a rate of +0.67 per year during the last four decades. A decrease in land cover by a rate of -1.4, -0.37 and -0.08 was accounted for grass area, forest and Wadies, respectively. A remarkable change has taken place in agricultural area from 9.8% in the year 1973 to 41.4% in the year 2010. This expansion is at the expense of the area covered by grass, forest and Wadis.

This study uses Landsat data and Tasseled Cap Transformation green vegetation index (GVI) technique to assess the condition of rangeland resources in the Sahel region of West Africa. Three representative zones in the sahelian region of Mali, Burkina Faso and Niger were selected for this study. Satellite data covering fifteen years period was used to assess the extent to which rangeland resources have degraded on a country by country basis between 1984 and 1999. The study results show all three countries in the study area experienced vegetation decline. However, loss of vegetation cover was most pronounced in the northern part of the study area than in the south. This decline could be attributed to changing temperature and rainfall gradients.

This article investigates and analyzes land use/land cover change in Ghubaysh area-Western Sudan during the period 1973-2010. The main objective of the article is to detect and identify land cover changes that have occurred during the last four decades. Multi-temporal satellites images (MSS, TM and ETM+) of 1973, 1987 and 2006 were used for data collection. The EARDAS Imagine classifier tool 9.2 and ArcGIS 10.2 have been used in the data analysis. Cultivated area, Wadis, shrubs, grass and forest were the most dynamic parameters used in land cover classification. Results showed high level of accuracy (98.2%, 96.3 and 89.6%) for the selected images for the years 1973, 1987 and 2006, respectively. The results also showed that the study area was once very rich in vegetation cover consisted of grass shrubs and forest which covered 86.7% of the study area. A prolonged and unsystematic change in land cover was reported. The agricultural area increased by a rate of +1.8% and shrubs increase...

This study uses Landsat data and Tasseled Cap Transformation green vegetation index (GVI) technique to assess the condition of rangeland resources in the Sahel region of West Africa. Three representative zones in the sahelian region of Mali, Burkina Faso and Niger were selected for this study. Satellite data covering fifteen years period was used to assess the extent to which rangeland resources have degraded on a country by country basis between 1984 and 1999. The study results show all three countries in the study area experienced vegetation decline. However, loss of vegetation cover was most pronounced in the northern part of the study area than in the south. This decline could be attributed to changing temperature and rainfall gradients.

This study uses Landsat data and Tasseled Cap Transformation green vegetation index (GVI) technique to assess the condition of rangeland resources in the Sahel region of West Africa. Three representative zones in the sahelian region of Mali, Burkina Faso and Niger were selected for this study. Satellite data covering fifteen years period was used to assess the extent to which rangeland resources have degraded on a country by country basis between 1984 and 1999. The study results show all three countries in the study area experienced vegetation decline. However, loss of vegetation cover was most pronounced in the northern part of the study area than in the south. This decline could be attributed to changing temperature and rainfall gradients.

ABSTRACT Woody biomass production is a critical indicator in evaluation of land use management and the dynamics of the global carbon cycle (sequestration/emission) in terrestrial ecosystems. The objective of the present study was to develop, through a case study in Sudan, an operational multiscale remote-sensing-based methodology for large-scale estimation of woody biomass in tropical savannahs. Woody biomass estimation models obtained by different authors from destructive field measurements in different tropical savannah ecosystems were expressed as functions of tree canopy cover (CC).The field-measured CC data were used for developing regression equations with atmospherically corrected and reflectance-based vegetation indices derived from Landsat ETM+ (Enhanced Thematic Mapper Plus) imagery. Among a set of vegetation indices, the normalized difference vegetation index (NDVI) provided the best correlation with CC (R2 = 0.91) and was hence selected for woodland woody biomass estimation. After validation of the CC-NDVI model and its applicability to Moderate Resolution Imaging Spectroradiometer (MODIS) data, time-series MODIS NDVI data (MOD13Q1) were used to partition the woody component from the herbaceous component for sparse woodlands, woodlands and forests defined by the Food and Agriculture Organization (FAO) of the United Nations Land Cover Map. Following the weighting of the estimation models based on the dominant woody species in each vegetation community, NDVI-based woody biomass models were applied according to their weighted ratios to the decomposed summer and autumn woody NDVI images in all vegetation communities in the whole of Sudan taking the year 2007, for example. The results were found to be in good agreement with those from other authors obtained by either field measurements or other remote sensing methods using MODIS and lidar data. It is concluded that the proposed approach is operational and can be applied for a reliable large-scale assessment of woody biomass at a ground resolution of 250 m in tropical savannah woodlands of any month or season.