Assessment of Spatio-Temporal Vegetation Greenings using NDVI in North Kordofan State, Sudan

Land degradation has been a serious environmental problem in Sudan Sahel Zone and information about vegetation greenness cover distributions is more essential for several vegetation resource changes and the management of sustainable growth of vegetation cover. The study combines various approaches which include statististical trend analysis of satellite derived Normalized Difference Vegetation Index(NDVI) residuals to identifying the thematic mapping crating for spatial greenness seasons. The objective of this study is to assess the spatial heterogeneity and the dynamics of the vegetation greenness and land cover change using different multi-spectral images derived from AVHRR instrument. The NDVI is used as one of the geosciences adapted methods that depends on the satellite images to calculate the vegetation greenness applying mathematical function. For this project seven landsat TM-images have been selected which were taken from 1972 to 2005.The results show that there is a remarkable correlation between vegetation cover greenness and the rainfall among the studied seasons. The greenness of positive high values showed there were 5 seasons that depicted high NDVI values, while 2 of the seasons showed less NDVI values (1984 and1990). This suggests that more indepth study of this kind of projects has to be taken by integrating the spatial data with climatological and mathematical functions. 1Introduction: Environmental problems that relate to the natural resources are affected by earths’ resources that increasingly emerged. All problems are typically distributed in Spatio-temporal manner. Concern of attribute value such as environmental degradation, is of high interest for its spatial and time measurement in problems analysis. Vegetation is the backbone of rural economy, contributed by all herders and nomads as well as sedentary rural people. So, for a primary economic country like Sudan, timely information on the types of grass grown and their intensity is required. Vegetation cover greenness and grass growth conditions are essential for strengthening rural areas income and distribution system. Remote sensing techniques have been used to map the land cover consumption including vegetation greenness within different ecosystems. Reliance on meteorological and agricultural data alone is not sufficient to assess change in vegetation cover that needs help with more accuracy techniques. So, the recent satellite images data used effectively with weather data to depict the change of vegetation conditions spatially. Satellite data at global scales and resolutions that are adequate for monitoring changes related to rainfall have now become widely available (Eensham et al; 1999; Volcani et al ; 2005). The application of Remote Sensing (RS) and Geographical Information System (GIS) in fields of natural resources management and environmental degradation assessment has highly increased and upgraded successfully. NDVI was used to assess and calculate changes in vegetation cover in relation to rainfall characteristics. The development of remote sensing techniques in the late 1970s resulted from the need for methodological methods to evaluate the vegetational conditions in their local and global extent. Priority was given to applicability and accountability of vegetation using NDVI that explains its intensity and carrying capacity and assessing in such ways water moisture content for agricultural studies. Changing trends in ecosystem productivity can be quantified using satellite observations of Normalized Difference Vegetation Index (NDVI), the estimation of trends from NDVI time series differs substantially depending on analyzed satellite dataset (Matthias et al; 2013 and Lucht, 2006). NDVI technique is used in many studies as a parameter for assessing drought occurrence due to less rainfall and less vegetation cover greenings. There is a correlation between NDVI and climatological variables mainly rainfall and temperature. The accurate assessment of rangeland vegetation cover, in terms of their productivity, their vulnerability to drought and their magnitude of degradation, requires information about the dominant vegetation types including their spatial variations in coverage (LeHouerou ,1996). NDVI is used for different purposes to monitor agricultural production, assist in predicting hazards and to monitor agricultural drought. Drought and rainfall variability during the last three decades are the major International Journal of Latest Research in Humanities and Social Science (IJLRHSS) Volume 02 Issue 09, 2019 www.ijlrhss. com || PP. 58-68 59 | Page www.ijlrhss. com physical challenges to vegetation in North Kordofan. Change was assessed depending on the overall NDVI values (negative or positive) for the entire study area between the selected images during 1972, 1984, 1987, 1990, 1992, 2000, and 2005. The current images of the vegetation greenness compared with selected seasons give also a good indication of rainfall change. A variety of procedures for change assessment, based on comparison of multi-temproal remote sensing data, have been developed (Ashbindu, 1989). NDVI is more powerful as it is used for assessing the vegetation greenness and healthiness. The frequency of new assessments takes short periods and recently researchers work on biweekly NDVI were its composite image is updated every week. A new biweekly image is produced each week; by dropping the oldest weeks data and adding the newest weeks data (Burdan et al; 1993). NDVI has also considerable importance as developed by some authors. Francesco et al (2014) stated that NDVI importance comes from the fact that it gives information about a primary production (vegetation) over time. 2Statement of the Problem: Significant changes in the vegetation cover and seasonal plants productivity manifest rapid environmental degradation . As in rural areas, trees at the vicinity of settlements are effected by the human interferences such as overcutting and over grazing. Although the cutting rates are spatially not equal or the same, the overall cutting rate gives a danger level of environmental degradation over both provinces, Shiekan and Bara of the study area. Tree clearance has become a serious top environmental problem, especially in arid and semi-arid ecosystems. Since 1980s, the total land forest was continuously degrading, and the loss was estimated to be over hundredth million hectares. Based on this fact, this research idea had been in reality to assess the problem of vegetation cover. The severe drop in production observed in 1984 (one of the worst droughts in Sudan) during the 20 th century had its own impacts that were highly associated with the less vegetation cover for herders. About (5.800.000) persons displaced, thousands of animals died and approximately (50.695) km 2 (12.650.410 feddans) of land were degraded as reported by the Agricultural Statistic Office (ElObeid ,1990). 3Objectives: The main aim of this research is to use Remote sensing data and techniques to assess the vegetation cover conditions using Spatio-temporal time series approach. Minor objectives are: 1. Interpret the relationship between NDVI and rainfall. 2. Show the efficiency of the NDVI in assessing vegetation conditions. 4Significance of this paper: Vegetation change is one of the most indicative signs of environmental degradation that the semipermanent green areas in the proximity of forest, water depressions and Khors, which are environmental sensitive areas, should be protected. Hence the environmental diagnosis is a need to assess the degraded areas using vegetation indices such as NDVI. 5Conceptual Framework: 51 Methodology Materials and procedures for this research include many aspects of concerns: 5-1-1 Site of the study area: Sudan depends almost exclusively on the natural land for rural livelihoods, animals and agriculture. Rainfall variability and exploitation of land without strategy or socio-economic planning created huge change recently over the land cover of the rural natural ecosystem. The area selected for the study was an approximately 637.000 km 2 in west Sudan which consists of two localities (Shiekan and Bara ). The study area is located between 13 0 N to 16 0 N latitudes, and 29 0 E to 31 0 longitudes( Fig 1). North Kordofan is part of the dry region of the western Sudan. The annual average rainfall rarely exceeds 380 mm/y. Its dry climate encourages the expansion of shifting cultivation at the expense of forest lands that decreases the healthiness of vegetation cover. Crop cultivation during the rainy season enhances the greenness cover and depends on the amount, intensity and distribution of the rainfall. Generally,it is characterized by arid and semi-arid ecosystems and share in a large extent same ecological characteristics. Features distributed naturally are uneven terrain, dunes and sand creeping, khors surface water courses, shallow water bodies and vegetation cover with distinct variations. The study area ,as part of North Kordofan State, is ecologically classified as a drought vulnerable area. International Journal of Latest Research in Humanities and Social Science (IJLRHSS) Volume 02 Issue 09, 2019 www.ijlrhss. com || PP. 58-68 60 | Page www.ijlrhss. com Fig (1): Site of the Study Area 5-1-2 Data capturing: Generally speaking, scientific research is most heavily limited by the quality of the data, and remote sensing of satellite imagery is no exception. Spatial resolution problem still constitute the big obstacles for doing a very high quality research using remote sensing satellite data such as a very high resolution for distinguishing vegetation by its types (grass, herbs – trees and shrubs). Different states of the land surface can be measured by satellite-derived biophysical parameters (Coppin, 2004). The remote sensing community has used AVHRR data to develop a NDVI (Goword, 1990) that is sensitive to the quantity of actively photosynthesing biomass. N