The hyper-arid conditions, low inherent soil fertility, water scarcity, and marginal water quality collectively constrain the local agriculture production in Abu Dhabi, UAE. To achieve this, an integrated suitability assessment was conducted considering soil resources, relief/slope, and water resources and forms the focus of the present study. The soils were classified using Soil Taxonomy (ST).

Agricultural land suitability evaluation for crop production is a process that requires specialized geo-environmental information and the expertise of a computer scientist to analyze and interpret the information. This paper presents ALSE, an intelligent system for assessing land suitability for different types of crops in tropical and subtropical regions (e.g. mango, banana, papaya, citrus, and guava) based on geo-environmental factors that automates the process of evaluation and illustrates the results on an attribute table.

Suitability evaluation of urban construction land based on geo-environmental factors is the process of determining the fitness of a given tract of land for construction. This process involves a consideration of the geomorphology, geology, engineering geology, geological hazards, and other geological factors and is the basis of urban construction land planning and management.

Recently, solar PV technologies witnessed a commercial vigor due to their tremendously decreasing prices. However, these technologies are vulnerable to dust and temperature which can significantly degrade their efficiency. Taking into account, the effect of dust and temperature during the site assessment for large PV power plant will reduce their vulnerability and optimize their operation efficiency. Most of the site assessment for large PV power plants does not take into consideration spatio-temporal variability of dust and temperature effects due to their measurement complexity.

Due to constant decrease in farmlands, it is important to identify the best lands useful for sustainable agriculture (productive and profitable agriculture that protects the environment and that is socially equitable). This requirement has resulted in the development of land suitability maps for agriculture by combining several factors of various natures and of differing importance.

Recent advances in ecological modeling have focused on novel methods for characterizing the environment that use presence-only data and machine-learning algorithms to predict the likelihood of species occurrence. These novel methods may have great potential for land suitability applications in the developing world where detailed land cover information is often unavailable or incomplete.

A geoinformatics-based land suitability assessment approach was used to examine the prospects for precision farming in the Savanna River basin in Nigeria. The procedure involved the overlay analysis of land use, land cover characteristics interpreted on Landsat Thematic Mapper (TM) imagery and physico-chemical soil properties and nutrient attributes in line with FAO suitability guidelines and models. The empirical analysis revealed areas of high, moderate and marginal suitability for the cultivation of maize, yam, cassava and oil palm in the basin.

Land suitability evaluation in water scarce agricultural watersheds consists of assessment of land potential for various crops as well as surface water potential to identify the scope for supplementary irrigation. A large amount of information related to the crop land suitability can be conveyed through linguistic terms. Capability of fuzzy sets in modeling involving uncertainty and vagueness is made use of in fuzzy rule-based systems, where various decision making criteria in linguistic terms are expressed as fuzzy rules.

There is increasing interest in Zimbabwe in developing a biofuels industry based on the production of biodiesel using Jatropha as the main feedstock. This has led to the introduction of Jatropha as a commercial energy crop in the country. There are plans to grow 1220 km2 of Jatropha which will supply about 365,000 t of seed. This will provide about 110 dam3 of biodiesel required to achieve a blending level of 10% with petro-diesel.

Site selection is a key factor in any aquaculture operation, because it affects both success and sustainability. It can, moreover, solve conflicts between different activities, making rational use of the land. This study was conducted to identify suitable sites for development of Nile tilapia (Oreochromis niloticus) farming in Sitakunda Upazila (sub-district), Bangladesh, using GIS-based multi-criteria evaluation of water and soil quality, topography, infrastructure and socio-economic factors.

The study area chosen is Damghan Plain, in Iran and covers an area of 5400 hectares.The methodology used for the physical land suitability analysis is a multi-criteria evaluation based on FAO land evaluation framework. The methodology consists of matching soil/land qualities against barley needs and assigning suitability rating to each land characteristic. The results show that 15.88% of the area is S2 (moderately suitable) and 26.55% S3 (marginally suitable) and 57.57% and N (Not Suitable) for Barley crop.

The availability of spatially continuous data layers can have a strong impact on selection of land units for conservation purposes. The suitability of ecological conditions for sustaining the targets of conservation is an important consideration in evaluating candidate conservation sites. We constructed two fuzzy logic-based knowledge bases to determine the conservation suitability of land units in the interior Columbia River basin using NetWeaver software in the Ecosystem Management Decision Support application framework.