Agroecological zoning of Nicaragua through multiple factor analysis and cluster analysis

Aguilar, A.; Dorado, H.; Siles, P.; Gonzalez, G.; Peng, Y.C.; Rivera-Palacio, J.C.; Huang, S.D.; Kuo, C.C., 2020 Agroecological zoning of Nicaragua through multiple factor analysis and cluster analysis, https://doi.org/10.7910/DVN/UP0JKM, Harvard Dataverse, V1

This dataset contains the final product of an agroecological zone classification for Nicaragua. The classification was created using data layers from worldclim, soilgrid and INETER (Instituto Nicaragüense de Estudios Territoriales). The unsupervised method used was k-means and its inputs were variables obtained from a dimensionality reduction achieved through Multiple Factor Analysis. Finally, 17 clusters were pointed out, by a statistical metric and expert knowledge, as the best number of groups to describe the agroecological conditions for the country.