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.

The dry rangelands of West Asia and North Africa are fragile and severely degraded due to low rainfall and mismanagement of natural resources. Rainwater harvesting (RWH) interventions are used to increase soil moisture content, vegetation cover, and productivity. However, adoption of rainwater harvesting by communities is slow. To understand adoption constraints and to develop options for sustainable integration of rainwater harvesting, a benchmark watershed was established in the dry rangelands of Jordan.

Site selection is a key factor in any aquaculture operation, affecting both success and sustainability as well as solving conflicts between different activities and making rational use of the land. The study was conducted to identify appropriate site for the farming of giant prawn, Macrobrachium rosenbergii, in Companigonj of Noakhali, Bangladesh using GIS-based multi-criteria evaluation taking 20 base layers of water quality, soil characteristics and infrastructure facilities.

Wind farm siting can be considered as Multi Criteria Decision Making (MCDM) problem that consists of set of alternative locations and set of selection criteria. This study applied multi-criteria decision making approach using Analytical Hierarchy Process with Ordered Weigh Averaging AHP-OWA aggregation function to derive wind farm land suitability index and classification under Geographical Information System (GIS) environment. Linguistic quantifier’s version of AHP-OWA aggregation function was used to classify lands based on their suitability for wind farm installation.

New developments in geographic information science and technology are changing the way we apply GIS to developing-world agriculture, creating new opportunities to utilize the technology to address problems of disaster management, climate change, land use change, land degradation, crop analysis and impact assessment.GIS allows data and demographic information to be presented graphically, primarily in maps, but also in business tools such as charts, graphs and other reports.