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Land suitability analysis to assess the potential of public open spaces for urban agriculture activities
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Orientador(es)
Resumo(s)
In a world increasingly dominated by cities and an accelerated urban sprawl, urban agriculture emerges as an alternative for the continuous stock and food supply that urban population demands. This thesis aimed to identify and evaluate potential available areas in public locations for implementing urban agriculture practices within the urban perimeter of the city of Bogota in Colombia. The methodology was conducted using variables reflecting the physical, environmental and socioeconomic components of the area. Two approaches were implemented to evaluate a land suitability analysis for urban agriculture to alleviate urban poverty by increasing food security and nutrition in the study area. The first approach was based on expert knowledge combining GIS with multicriteria decision making analysis (MCDM) using analytical hierarchical process (AHP) method, estimating that 21% of the study area presents highly suitability conditions for implementing urban agriculture activities. The second approach was developed using supervised machine learning algorithms for classification models based on historical data of the current sites, where urban agriculture activities were being implemented in the city, showing that 18% of the study area is in high suitability conditions for the implementation of urban agriculture activities. Both approaches indicated that the areas of excellent suitability are located in the South and Southwestern parts of the study area, emphasizing its congruence with the areas with the lowest socioeconomic levels in the city.
It was found that approximately 2% of the study area has available spaces in public locations with a significant potential for urban agriculture practices. Three projected scenarios were simulated where 10%, 30% and in the most utopic case 50% of these spaces would be used for urban agriculture activities and the vegetable productivity in tons of five of the most popular crops grown was estimated.
Descrição
Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial Technologies
Palavras-chave
Analytic Hierarchy process K-Nearest Neighbors Machine Learning Multicriteria Decision Analysis Random Forest Sensitivity Analysis Support Vector Machine Urban Agriculture