The main aim of this research is to highlight the environment change indicators during the last 20 years in a representative area of the southern part of Iraq (Basrah Province was taken as a case) to understand the main causes which led to widespread environment degradation phenomena using a 1:250000 mapping scale. Remote sensing and GIS's software were used to classify Landsat TM in 1990 and Landsat ETM+ in 2003 imagery into five land use and land cover (LULC) classes: vegetation land, sand land, urban area, unused land, and water bodies. Supervised classification and Normalized Difference Vegetation Index (NDVI), Normalized Difference Build-up Index (NDBI), Normalized Difference Water Index (NDWI), Normalized Difference Salinity Index (NDSI), and Topsoil Grain Size Index (GSI) were adopted in this research and used respectively to retrieve its class boundary.The results showed a clear deterioration in vegetative cover (514.9 km 2 ) and an increase of sand dune accumulations (438.6 km 2 ), accounting for 10.1, and 10.6 percent, respectively, of the total study area. In addition, a decrease in the water bodies' area was detected (228.9 km 2 ). Sand area accumulations had increased in the total study area, with an annual increasing expansion rate of (33.7 km 2 • yr −1 ) during the thirteen years covered by the study. It is therefore imperative that Iraqi government undertake a series of prudent actions now that will enable to be in the best possible position when the current environmental crisis ultimately passes.

This research integrated selected land degradation indicators (vegetation cover, proportion of drifting sand area, desertification rate, and population pressure) with geo-information techniques (remote sensing, geographic information system and global positioning system) to assess the severity of land degradation risk. The northern part of Shaanxi province in China was taken as a case study. A computerized land degradation severity assessment was implemented, and ERmapper ver.6.2 and ARC/INFO GIS ver.8.3 environments were used to manage and manipulate thematic data, and to process satellite images and tabular data. Two Landsat TM images in October 1987 and October 1999 were used to produce land use/cover maps of the study area based on the maximum likelihood classification method. These maps were then used to generate land use, land cover change, vegetation degradation and land degradation maps for the study area during the study period, and their corresponding data were integrated into a systematic analysis. Results showed that the overall severity of land degradation in the study area worsened during the study period from 1987 to 1999 with severely, highly and moderately degraded land accounting for 73·8 per cent of the total area. While the area affected by desertification has increased, the rate of desertification has also accelerated to reach 41·5 km 2 a − − − − −1 . Risk of land degradation in the study area has increased, on average, by 39·4 per cent since 1987. Incorporation of both natural and anthropogenic factors in the analysis provided realistic assessment of the risk of desertification. The study area, in general, is exposed to a high risk of land degradation.