David bio photo

David
García-León

Marie Skłodowska-Curie Research Fellow (Ca' Foscari University and Euro-Mediterranean Center on Climate Change, Venice).


Curriculum Vitae
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Coding tools and resources

Convert remote sensing images to time series

To perform time series and regression analysis, satellite imagery first needs to be transformed into a suitable format. I highlight next four different methods to convert satellite observation (typically in .HDF or .NetCDF format) to .csv or .Rda files.

  • ENVI-IDL: Proprietary remote-sensing software that provides hyperspectral image analysis, image enhancement and feature extraction. Usually served with IDL, a programming software used for data analysis, visualization and cross-platform application development. [link]

  • MODIStsp: R package devoted to automatizing the creation of time series of raster images derived from MODIS Land Products data. [link]

  • Google Earth Engine - javascript console: A multi-petabyte catalogue of satellite imagery and geospatial datasets with planetary-scale analysis capabilities that makes it available for scientists, researchers, and developers to detect changes, map trends, and quantify differences on the Earth’s surface. [link]

  • Google Earth Engine - Command line (Requires Google Earth Engine Python API) [link]

Other code snippets

  • vwIRF: R function to build visually weighted time paths [link] [Description of the code]

  • DGL02_shiny: Interactive R-Shiny app that displays interactive graphs [link]

  • Thesis template: Doctoral thesis LaTeX template files. Thanks to Enrique Moral-Benito (Bank of Spain), who provided original version [link]