This paper presents some preliminary results from a research study conducted on solar energy resource assessment in Oman. GIS-based spatial multi-criteria evaluation approach, in terms of the FLOWA module was used to assess the land suitability for large PV farms implementation in Oman. The tool used applies fuzzy quantifiers within ArcGIS environment allowing the integration of a multi-criteria decision analysis. Land suitability analysis for large PV farms implementation was carried out for the case study of Oman.

An area suitability assessment for crop production requires a considerable effort, which can provide necessary information for optimum land use. Agricultural land use has benefited significantly from the use of suitability systems in recent years.

The forest transition (FT) hypothesis implies that changes in a region's forest cover follow a determinable pattern of decline and later re-expansion over time, which is supposed to be similar across regions and countries. Such a uniform pattern – if empirically proven and quantified – might help in establishing REDD+ baselines (i.e., references against which reductions in the emissions from deforestation and forest degradation of developing countries could be measured, and subsequently be rewarded).

Determining the feasibility of a large-scale afforestation program is one approach being investigated by the Government of Canada to increase Canada's potential to sequester carbon from the atmosphere. Large-scale afforestation, however, requires knowledge of where it is suitable to establish and grow trees. Spatial models based on Boolean logic and/or statistical models within a geographic information system may be used for this purpose, but empirical environmental data are often lacking, and the association of these data to land suitability is most often a subjective process.

In this study, Land Capability Classification (LCC) and Suitability Classification for Irrigated Agriculture (SCIC) were conducted for Aksu-Mand�rlar Research and Application Area (Antalya) that belong to Akdeniz University.

Bu �al��mada, Akdeniz �niversitesi Aksu-Mand�rlar Ara�t�rma ve Uygulama Arazilerinin ideal kullan�mlar�n�n sa�lanmas� i�in Arazi Yetenek S�n�flamas� (AYS) ile Sulu Tar�ma Uygunluk S�n�flamas� (STUS) yap�lm��t�r.

The present study describes an innovative methodology to rank suitable sites for irrigation with TWW using fuzzy-AHP based on GIS where the Nabeul-Hammamet aquifer catchment (Tunisia) is selected as the target area. The model is relatively simple and is extendable worldwide. Several influential parameters are identified considering simultaneously technical, social, economical and environmental aspects. They are grouped in five main criteria, namely land suitability for irrigation, resources conflicts, cost effectiveness, social acceptance and environmental impact.

Modeling the suitability of land to support specific land uses is an important and common GIS application. Three classic models, specifically pass/fail screening, graduated screening and weighted linear combination, are examined within a more general framework defined by fuzzy logic theory. The rationale underlying each model is explained using the concepts of fuzzy intersections, fuzzy unions and fuzzy averaging operations. These fuzzy implementations of the three classic models are then operationalized and used to analyze the distribution of kudzu in the conterminous United States.

Land evaluation is a critical step in land‐use planning. Although many methods have been developed since the formulation of the FAO framework for land evaluation, several of the more traditional approaches still remain in widespread use but have not been adequately evaluated. Contrary to more recent land evaluation systems, which need considerable data, these systems only require basic soil and landscape information to provide a general view of land suitability for major types of land use.

Land evaluation is the act of predicting the use potential of land on the basis of its attributes. The objective of this study was to evaluate qualitative and quantitative land suitability for the north-west of Iran on the basis of a FAO model for sunflower and maize crops. Growing cycle was determined using the CDBm (Monthly Climate Database) model and soils were classified in two orders of Mollisols and Vertisols, which consisted of seven soil families based on soil data and Keys to Soil Taxonomy 2010.

The inference rules relating land characteristics to suitability class are crucial to the estimation of agricultural land suitability. In fuzzy logic modeling for agricultural land evaluation, the fuzzy inference, based on membership functions and rule aggregation, is constructed with predetermined evaluation criteria, including value ranges for fuzzy linguistic terms, and weights of land variables. However, most existing evaluation criteria systems are built on the basis of expert knowledge and can be highly subjective and contain uncertainty.

A land suitability study covering an area of 56,655 square kilometers was carried out for the cultivation of a halophytic bioenergy crop, Salicornia bigelovii, in the Emirate of Abu Dhabi using data collected from an extensive soil survey (scale of 1:100,000). Two simple limitation methods (referred to in the paper as the conservative and weighted methods) were used to interpolate soil map unit data for qualitative evaluation of the land.