A discrete simulation approach to spatial allocation of commodity production for revenue optimisation over a local region

Experiments in Optimal Spatial Segmentation of Local Regions Using Categorical and Quantitative Data

“…In the simulation, each neighbourhood cell had its commodity type and land suitability value selected probabilistically (Benke et al 2011). This eliminated the problem of treatment of ties for land suitability for competing crops within each cell, where each may have had the same land suitability at that geographical location (i.e the LUT for each cell had eight land suitabilities from eight crops).…”

“…Recent experiments have clarified the potential of a probabilistic-based methodology, with actual implementation using the original software platform used for the genetic algorithm used by Wyatt (2006), extending and modifying it appropriately, and including a different search strategy (Benke et al 2011). The optimal allocation software tool used was converted into a multiple choice procedureoffering a deterministic approach based on a genetic algorithm or an iterative probabilistic approach.…”

“…The software package developed for this project is referred to as ©CropOptimizer 2.0 and is under continuing development. The original version was developed in Visual Basic by Wyatt (2006 and then later extended to include added optimisation options (Benke et al 2011). Its current features include land spatial allocation by probabilistic optimisation or genetic programming, with provision of full maps and output tables for further implementation in economic models.…”

Use of the McHargian LUSA in agricultural research and decision-making in the age of non-stationarity and big earth observation data

“…Criteria commonly used in the weighted sum analysis included: soil fertility characteristics, topography (elevation, slope, aspect), and climate variables, as is suggested by LUSA methods recommended by the FAO (1976) and USDA (1961). Acknowledging that economic viability of agricultural land use requires markets for products to be sold and infrastructure in transportation and production processes, several studies also consider socioeconomic conditions, infrastructure, and legal frameworks (Cardín-Pedrosa and Alvarez-López 2012, Benke et al (2011) p. 89; Pourebrahim et al 2011, p. 87;Ullah and Mansourian 2016, p. 20;Memarbashi et al 2017, p. 4;Humphries et al 2010, p. 229). Studies that included socioeconomic conditions were more likely to include suitability analyses for conservation land uses alongside agriculture land uses.…”

Usages des modèles spatiaux pour la prospective

“…Pour ce faire, il s'agit de coupler des méthodes d'optimisation avec un process-based modèle : les méthodes d'optimisation permettent d'atteindre une situation prédéfinie (à l'équilibre, désirée ou non) à partir d'une somme de processus spatio-temporels (par exemple, les changements d'occupation des sols tels que des rotations culturales en milieu agricole). Ce type de modèle est beaucoup plus rare (Benke et al, 2011 ;.…”