Urban sprawl is one of the main problems that threaten the limited highly fertile land in the Nile Delta of Egypt. In this research, satellite images of Landsat Thematic Mapper (TM) 1992, Landsat Enhanced Thematic Mapper (ETM+) 2001 and Egypt Sat-1 2009 have been used to study the urban sprawl and its impact on agricultural land in Qalubiya Governorate. Maximum likelihood supervised classification and post-classification change detection techniques were applied for monitoring the urban sprawl in this study area. Ground truth collected during several field trips conducted in 2009 and a topographic map from 1992 were used to assess the accuracy of the classification results. Using ancillary data, visual interpretation and expert knowledge of this area through GIS further refined the classification results. Post-classification change detection technique was used to produce change image through cross-tabulation. Combining the soil and land capability maps, on one hand, and the urban thematic layers, on the other hand, using GIS, made it possible to point out the risk of urban expansion on the expense of the highly capability class. During the (1992–2009) period, the high capable soils (Class I) decreased from 683.2 km² to 618.5 km². The moderate capable soils decreased from 100.5 km² to 93.8 km² whereas the marginally capable soils decreased from 209.1 km² to 198.3 km², during the same period. The urban encroachment over the non-capable soils was very limited during the 1992–2001 period. The pattern of urban sprawl changed during the 2001–2009 period whereas most of the urban expansion was on the expense of the non-capable soils.

Desertification is defined in the first art of the convention to combat desertification as "land degradation in arid, semiarid and dry sub-humid areas resulting from climatic variations and human activities". Its consequence include a set of important processes which are active in arid and semi arid environment, where water is the main limiting factor of land use performance in such ecosystem . Desertification indicators or the groups of associated indicators should be focused on a single process. They should be based on available reliable information sources, including remotely sensed images, topographic data (maps or DEM'S), climate, soils and geological data. The current work aims to map the Environmental Sensitivity Areas (ESA's) to desertification in whole territory of Egypt at a scale of 1:1 000 000. ETM satellite images, geologic and soil maps were used as main sources for calculating the index of Environmental Sensitivity Areas (ESAI) for desertification. The algorism is adopted from MEDALLUS methodology as follows; ESAI = (SQI * CQI * VQI)^1/3 Where SQI is the soil quality index, CQI is the climate quality index and VQI is the vegetation quality index. The SQI is based on rating the parent material, slope, soil texture, and soil depth. The VQI is computed on bases of rating three categories (i.e. erosion protection, drought resistance and plant cover). The CQI is based on the aridity index, derived from values of annual rainfall and potential evapotranspiration. Arc-GIS 9 software was used for the computation and sensitivity maps production. The results show that the soil of the Nile Valley are characterized by a moderate SQI, however the those in the interference zone are low soil quality indexed. The dense vegetation of the valley has raised its VQI to be good, however coastal areas are average and interference zones are low. The maps of ESA's for desertification show that 86.1% of Egyptian territory is classified as very sensitive areas, while 4.3% as Moderately sensitive, and 9.6% as sensitive. It can be concluded that implementing the maps of sensitivity to desertification is rather useful in the arid and semi arid areas as they give more likely quantitative trend for frequency of sensitive areas. The integration of different factors contributing to desertification sensitivity may lead to plan a successful combating. The usage of space data and GIS proved to be suitable tools to rely estimation and to fulfill the needed large computational requirements. They are also useful in visualizing the sensitivity situation of different desertification parameters.

Earth observation and monitoring of soil quality, long term changes of soil characteristics and deterioration processes such as degradation or desertification are among the most important objectives of remote sensing. The georeferenciation of such information contributes to the development and progress of the Digital Earth project in the framework of the information globalization process. Earth observation and soil quality monitoring via remote sensing are mostly based on the use of satellite spectral data. Advanced techniques are available to predict the soil or land use/cover categories from satellite imagery data. Artificial Neural Networks (ANNs) are among the most widely used tools for modeling and prediction purposes in various fields of science. The assessment of satellite image quality and suitability for analysing the soil conditions (e.g., soil classification, land use/cover estimation, etc.) is fundamental. In this paper, methodology for data screening and subsequent application of ANNs in remote sensing is presented. The first stage is achieved via: (i) elimination of outliers, (ii) data pre-processing and (iii) the determination of the number of distinguishable soil “classes” via Eigenvalues Analysis (EA) and Principal Components Analysis (PCA). The next stage of ANNs use consists of: (i) building the training database, (ii) optimization of ANN architecture and database cleaning, and (iii) training and verification of the network. Application of the proposed methodology is shown.

El Fayoum and Wadi El Natrun are typical examples of desert depressions, differ in nature; El Fayoum is connected with the Nile Valley by a major irrigation network, while Wadi El Natrun is inserted in the Eaolian desert landscape. Remote sensing and GIS spatial analysis were employed to assess the magnitude and geographical distribution of land resource and environmental hazard susceptibility, in addition to create and develop different thematic layers to evaluate potentiality for sustainable development in the studied depressions. The land resources database shows that the soils associated with recent alluvial terraces dominate the depressions. Multi-temporal satellite images revealed that urbanization mainly occurred on the account of most fertile soils of El Fayoum depression, hence shrinking the high and moderate capable soils. Wadi El Natrun depression and its expansion are potential areas for agricultural purposes. Land use/ cover maps clearly show that the El Natrun depression does not undergo significant hazards, as the expansion of urban and agricultural areas occur on the count of bare land. It could be concluded that desert depressions represent promising areas for sustainable development. The depressions connected to active river systems, such as El Fayoum, may support integrated sustainable development. The establishment of basic infrastructure in isolated depression areas, such as Wadi El Natroun, encourages sustainability in areas located at the open deserts.