Crop discrimination using remote sensing data in a region of high marginalization

This work was realized in the state of Guerrero, Mexico considered a high marginalization region in the country. The aim of this work was to generate the agricultural frontier and to determine the spatial distribution of maize and beans from satellite images using two classification algorithms. Of the entire state area (6,357, 781 hectares), 15.6% is occupied by agriculture. Of this, 244,585 hectares are occupied with corn and 18,034 with beans. The kappa coefficient indicates that the classification performed for Maxlike and MinDist is 91% and 89 % respectively. The results can support the design of strategies to address climate change concerns in the producing areas of corn and beans, with new varieties adaptable to current weather conditions for the benefit of farmers, particularly those located in areas of high marginality and vulnerability.