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. Its main features include support of GIS capabilities on the digital map of an area with the FAO-SYS framework model with some necessary modifications to suit the local environmental conditions for land evaluation, and the support of expert knowledge through on spatial tools to derive criteria weights with their relative importance. A dynamic program for calculation of eigenvalues and eigenvectors of a weighting matrix is provided. Expertise and knowledge help ensure that ALSE databases represent realistic, practicable and functional systems. It is useful for decision makers to determine the quality of land for agricultural uses and is intended as a decision and planning support. Responsibility for any decisions based partly or wholly on the output of ALSE rests with the decision maker. ALSE ensures that the results are interpreted correctly within the relevant context, and contributes by maximizing land-use planning and decision support

Compact cities are recognized as sustainable urban forms rather than sprawl developments. Such cities are characterized by high density, land use diversity, accessibility, and efficient public transportation. However, few studies investigate how and how much these parameters affect and relate to compact cities. For instance, although mixed land use is the main key planning principle of compact development, no standard method exists for quantifying, measuring, and evaluating this parameter. This study performs a compact development analysis of Kajang City (Malaysia) with emphasis on evaluating and discussing the importance of mixed land use development. First, the land use diversity of Kajang City was measured. Second, the probability map of mixed land use developments was predicted using a weights-of-evidence (WoE) model. Finally, the importance of mixed land use for compact cities was evaluated using multicriteria decision analysis (MCDA). The created mixed land use probability map was validated using the receiver operating characteristic (ROC) technique. In addition, the 75% similarity between mixed land use and compact development suitability maps highlighted the importance of mixed land use development for compact cities. Results can be used as preliminary guidelines for local governments and planners regarding compact development and management to achieve sustainable urban forms.

Spatial relations often are desired answers that a geographic information system (GIS) should generate in response to a user's query. Current GIS's provide only rudimentary support for processing and interpreting natural-language-like spatial relations, because their models and representations are primarily quantitative, while natural-language spatial relations are usually dominated by qualitative properties. Studies of the use of spatial relations in natural language showed that topology accounts for a significant portion of the geometric properties. This article develops a formal model that captures metric details for the description of natural-language spatial relations. The metric details are expressed as refinements of the categories identified by the 9-intersection, a model for topological spatial relations, and provide a more precise measure than does topology alone as to whether a geometric configuration matches with a spatial term or not. Similarly, these measures help in identifying the spatial term that describes a particular configuration. Two groups of metric details are derived: splitting ratios as the normalized values of lengths and areas of intersections; and closeness measures as the normalized distances between disjoint object parts. The resulting model of topological and metric properties was calibrated for 64 spatial terms in English, providing values for the best fit as well as value ranges for the significant parameters of each term. Three examples demonstrate how the framework and its calibrated values are used to determine the best spatial term for a relationship between two geometric objects.