Abstract
Red spicy pepper is traditionally considered as the fundamental ingredient for multiple authentic products of Eastern Croatia. The objectives of this study were to: (1) evaluate the optimal interpolation method necessary for modeling of criteria layers; (2) calculate the sustainability and vulnerability of red spicy pepper cultivation using hybrid Geographic Information System (GIS)-based multicriteria analysis with the analytical hierarchy process (AHP) method; (3) determine the suitability classes for red spicy pepper cultivation using K-means unsupervised classification. The inverse distance weighted interpolation method was selected as optimal as it produced higher accuracies than ordinary kriging and natural neighbour. Sustainability and vulnerability represented the positive and negative influences on red spicy pepper production. These values served as the input in the K-means unsupervised classification of four classes. Classes were ranked by the average of mean class sustainability and vulnerability values. Top two ranked classes, highest suitability and moderate-high suitability, produced suitability values of 3.618 and 3.477 out of a possible 4.000, respectively. These classes were considered as the most suitable for red spicy pepper cultivation, covering an area of 2167.5 ha (6.9% of the total study area). A suitability map for red spicy pepper cultivation was created as a basis for the establishment of red spicy pepper plantations.
Highlights
Land use planning and ecological land evaluation are considered the most important tools and factors of sustainable agricultural production [1]
The proposed methodology was based on the hybridization of multicriteria analysis and unsupervised classification for the calculation of red spicy pepper cultivation suitability
It was observed that the inverse distance weighted (IDW) method performed best out of the three tested interpolation methods, contrary to most cases where ordinary kriging (OK) had an advantage over deterministic methods
Summary
Land use planning and ecological land evaluation are considered the most important tools and factors of sustainable agricultural production [1]. Multicriteria analysis provides information on the optimal utilization of available resources, allowing sustainable crop management [3]. In addition to crop requirements, it is necessary to have spatial information of the farmland soil, climate and land cover properties [4,5]. The upgrade of such analysis with a spatial component of GIS allows effective planning and its realization in the field [6,7]. The GIS-based multicriteria analysis was applied successfully for crop management down to the county or municipality area [8,9]. Among the multicriteria analysis methods, AHP has become increasingly popular since it allows the integration of a large quantity of heterogeneous data, making the process of criteria weight determination straightforward, even for a large number of criteria [10]
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