Campero Taboada, Milton J.Luquin Oroz, Eduardo AdriánMontesino San Martín, ManuelGonzález de Audícana Amenábar, MaríaCampo-Bescós, Miguel2023-01-122023-01-122022Campero-Taboada, M. J., Luquin, E., Montesino-SanMartin, M., González-Audícana, M., & Campo-Bescós, M. A. (2022). Evaluation of R Tools for Downloading MODIS Images and Their Use in Urban Growth Analysis of the City of Tarija (Bolivia). Remote Sensing, 14(14), 3404. https://doi.org/10.3390/rs141434042072-429210.3390/rs14143404https://academica-e.unavarra.es/handle/2454/44558The aim of this study was to compare the available tools in R for downloading and processing Moderate Resolution Imaging Spectroradiometer (MODIS) data, specifically the Enhanced Vegetation Index (EVI) product. The R tools evaluated were the MODIS package, RGISTools, MODISTools, R Google Earth Engine (RGEE) package, MODIStsp, and the Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) application. Each tool was used to download the same product (EVI) corresponding to the same day (3 December 2015), and downloaded data were used to analyze the urban growth of Tarija (Bolivia) as an interesting application. The following features were analyzed: download time and memory used during the download, additional postprocessing time, local memory occupied on the computer, and downloaded file formats. Results showed that the most efficient R tools were those that work directly in the “cloud” or use text queries (RGEE and AppEEARS, respectively) and provide, as a final product, a cropped.tif image according to the area of interest.application/pdfapplication/zipeng© 2022 by the authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) licenseEVIMODISRUrban growthVegetation indexArtículo / Artikulua2023-01-12Acceso abierto / Sarbide irekiainfo:eu-repo/semantics/openAccess