To map at a fine spatial scale, the risk of malaria incidence for the important endemic region is Urabá-Bajo Cauca and Alto Sinú, NW Colombia, using a new modelling framework based on GIS and remotely sensed environmental data.The association between environmental and topographic variables obtained from remote sensors and the annual parasite incidence (API) for the years 2013-2015 was calculated using multiple regression analysis; subsequently, a model was constructed to estimate the API and to project it to the entire endemic region in order to design the risk map. The model was validated by relating the obtained API values with the presence of the three main Colombian malaria vectors, Anopheles darlingi, Anopheles albimanus and Anopheles nuneztovari.Temperature and Normalized Difference Water Index (NDWI) showed a significant correlation with the observed API. The risk map of malaria incidence showed that the zones at higher risk in the Urabá-Bajo Cauca and Alto Sinú region were located south-east of the region, while the northern area presented the lowest malaria risk. A method was generated to estimate the API for small urban centres, instead of the used reports at the municipality level.These results provide evidence of the utility of risk maps to identify environmentally vulnerable areas at a fine spatial resolution in the Urabá-Bajo Cauca and Alto Sinú region. This information contributes to the implementation of vector control interventions at the microgeographic scale at areas of high malaria risk.