This study was carried out in Abu Hamra Area, south Darfur State (Latitude 12˚26ʹ to 13˚10ʹ E and longitude<br />24˚24ʹ to 25˚56ʹ N and), Sudan where the area falls in semi-arid climate. The study aimed to evaluate the<br />land suitability for rainfed agriculture and to scan crop suitability. Through the analysis of satellite image<br />and direct field observations, the study area was divided into non-cracking clay soil (unit A) classified as<br />Sodic Haplocambid, alluvial soil (unit B) classified as Ustic Torrifluvent and loamy sand soil (unit C)<br />classified as Typic Torripsamments. 46 soil samples were collected from 12 auger holes and 3 representative<br />profiles, then analyzed for some physical and chemical properties which were matched with climatic factors<br />and topographic features to define the requirements of rainfed crops, particularly Sorghum, Millet, Maize,<br />Sesame, Groundnuts, Watermelon and Tomato. Duncan Multiple Range Test was used to determine<br />significance of differences in soil properties within and among the three units. Results showed that the soils<br />were non-saline, non-sodic (except unit A), calcareous to slightly calcareous and low in fertility. Results also<br />indicated no significant differences among soil properties except for texture, salinity and sodicity. The soils<br />were found to be marginally suitable (S3) for rainfed agriculture because of presence of fertility, drainage,<br />organic matter, texture and sodicity limitations and unit B proved to be the best soils of the three units. For<br />crop suitability, the soils of the three units had same suitability for some crops and differ for others.

This study focused on evaluating the concepts of risk assessment associated with unsafe acts according to hazard identification at Gaili Area, Khartoum North, Sudan. Approaches used in this study; Research tools: Interviews, definite questionnaire &amp; computer program for descriptive statistics – statistical package for social science (SSPS/version 22 – 2014). The study of risk assessment is conducted for workers in fuel terminals at Gaili area and analyzed using environmental health and safety concepts for eight jobs. Risk is associated with Job (driver, electrician, pump attendant, etc.), after hazards to be identified (natural, environmental, technological, biochemical, etc.). Fuel truck drivers at Gaili area showed the most highly risk job. The result showed that 60% of the incidents were caused by the hydrocarbon fuel transport drivers at the study area as the most highly risk job, followed by the electricians being the most affected job by electrical shocks during working hours followed by the pump attendants then welders followed by mechanics; including fatalities, restricted work activities, injuries, first aid and property damage. The study recommended to formulate of temporary committees such as autumn committee is not efficient in solving the problem, HSE steering committee should be a permanent committee to direct the emergency planning according to risk based assessment for identified hazards.

Soil moisture is the key factor that controls plant biological processes and indicates the environmental status.  Recently, the application of remote sensing techniques in soil moisture monitoring has been widely used. In this study soil moisture was monitored during pre-autumn in March, autumn in September and post-autumn in December (2002), in order to identify the signature of different types of moist soils, which can be useful to interpret images. Supervised classification technique was adopted to determine the dominant land use/land cover classes in the area so that they can be vital indicators for the area and its suitability for many life styles. Monitoring moisture statuses can be used for general evaluation of land suitability for agriculture. The assessment of moisture statuses was performed in landsat ETM+ images using band 5 (MIR) as it is known as a sensitive band for moisture status and band 6 (Thermal) as a sensitive band to temperature variation as indicator of moisture status. The study revealed that band 5 and band 6 can be used to monitor soil moisture status during the different seasons in semi-arid areas, however, band 6 is less sensitive to variations in moisture. Therefore, this study recommends the use of Band 5 for monitoring soil moisture in semi-arid regions, and does not recommend the use of band 6 alone but with some supporting bands.

The study area lies to the east of the Nile (Sharg Elneel), Khartoum State (latitudes 15 o 25̎ 1̍ and 16° 19̎ 1̍ N and longitudes 33° 19̎ 8̍ and 33°02̎ 9̍ E). Using remote sensing techniques and geographic information system (GIS), the changes in land cover/land use have been estimated using two methods: supervised and unsupervised classification. the images were those of the years 1973, 2001, and 2015 1973-2001 and 1973-2015 INTRODUCTIONLand is one of the most important natural resource, since life and development activities are based on it. Land is one of our most precious assets, it provides food, filters and stores water; and it is the basis for urban and industrial development, leisure, and wide range of social and economic activities. Land is a production factor because of the vegetation and crops that can be grown on it. The Land is threatened by degradation and desertification, mainly as a result of human activities and climate changes. This will, eventually, lead to some changes in the land use/ land cover. Digital change detection is the process that helps in determining the changes associated with land use and land cover properties with reference to geo-registered multi temporal remote sensing data. Land use refers to the type of utilization to which man has put the land. It also refers to evaluation of the land with respect to various natural characteristics. But land cover describes the vegetal attributes of land. The term land cover originally referred to the kind and state of vegetation, such as forest or grass cover, but it has broadened in subsequent usage to include human structures such as building or pavement and other features of natural environment, such as soil type, biodiversity, and surface and groundwater (Meyer, 1995). Digital change detection is the process that helps in determining the changes associated with land use land cover properties with reference to geo-registered multi temporal remote sensing data. Change detection is the process of differences in the state of an object or phenomenon by observing it at different times (singh, 1989). Change detection is an important process in monitoring and managing natural resources and urban development because it provides quantitative analysis of the spatial distribution of the population of interest. Change detection is useful in such diverse applications as land use change analysis, monitoring, shifting, cultivation, assessment of deforestation and desertification , study of change in vegetation phonology, seasonal changes in pasture production, damage assessment, crop stress detection, disaster monitoring, day/night analysis of thermal characteristics as well as other environmental changes (singh, 1989). Land use/land cover (LULC) changes play a major role in the study of global change. Land cover changes and human natural modification have largely resulted in deforestation, biodiversity loss, global warming and increase of natural disaster.