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Computación y Sistemas

versão On-line ISSN 2007-9737versão impressa ISSN 1405-5546

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MENDOZA URIBE, Indalecio; CONTRERAS TEREZA, Víctor Kevin; MEJIA ESTRADA, Pamela Iskra  e  RODRIGUEZ LOPEZ, Olivia. Methodology for the Classification of Types of Land Use in the Metropolitan Area of the Valley of Mexico based on the Spectral Signature of Satellite Images and its Effect on the Rainfall Simulation with the WRF Model. Comp. y Sist. [online]. 2023, vol.27, n.2, pp.435-447.  Epub 18-Set-2023. ISSN 2007-9737.  https://doi.org/10.13053/cys-27-2-4625.

In numerical models of the atmosphere, data on land use are considered as initialization data, therefore a current classification at the simulation date will allow the model an appropriate representation of the processes related to the radiation balance and the hydrological cycle of the study área. In the particular case of the Weather Research and Forecasting model, the default database uses a classification of 21 categories of land use type, based on MODIS satellite images between the years 2001-2005 with a spatial resolution of 500 meters, therefore these data are not considered current or applicable to recent events. This paper proposes a methodology to update the classification of types of land use in the Metropolitan Area of the Valley of Mexico based on the analysis of the spectral signature of Landsat 8 satellite images and derived indices, as well as the statistical validation of its effect in the numerical simulation of rainfall with the WRF model.

Palavras-chave : Scientific computing; remote sensing; weather forecasting; model validation; urban areas.

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