Publications by Ivan Lizarazo
How to get raster soil data from ISRIC
1. Introduction SoilGrids is a system for global digital soil mapping that makes use of global soil profile information and covariate data to model the spatial distribution of soil properties across the globe. SoilGrids is a collections of soil property maps for the world produced using machine learning at 250 m resolution. SoilGrids can be accesse...
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Elevation data processing and analysis in R
1. Why this notebook? This notebook illustrates several functionalities to obtain, process and visualize digital elevation models (DEMs) in R. It aims to help Geomatica Basica students at Universidad Nacional to get acquainted with DEMs and geomorphometric variables. A few tips for writing your own notebook: Write and run every chunk step-by-step ...
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Spatial Interpolation
1. Introduction This notebook illustrates how to conduct spatial interpolation in R using precipitation data as example. This notebook is written to help Geomatica Basica students at Universidad Nacional de Colombia to become familiar with geospatial functionalities provided by the R software environment. Please note that this notebook explores g...
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Land Cover Change Metrics [2]
1. Introduction This notebook illustrates land cover change in Montes de Maria from 2000 to 2018. Land cover categories are represented by two raster datasets extracted from the global land cover (LC) products released by the European Space Agency (ESA) within the climate change initiative (CCI). ESA LandCover CCI supplies global maps of land cov...
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Land Cover Change Metrics
1. Introduction This notebook illustrates land cover change in Montes de Maria from 2001 to 2017. Land cover categories are represented by two raster datasets extracted from the Collection 6 MODIS Land Cover MCD12Q1 product. MCD12Q1 supplies global maps of land cover at annual time steps and 500-m spatial resolution for 2001-present. The product ...
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Get Soil Moisture Data from R
Why this notebook? This notebook outlines a basic use workflow for the smapr library. It illustrates how to acquire and process NASA (Soil Moisture Active-Passive) SMAP data, crop the data to match the extent of the area of interest, save the output, and generate some simple visualizations. This notebook aims to help Geomatica Basica students at ...
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Getting Landsat 8 data from R
1. Introduction Getting satellite image datasets for the study area is a first task in several research projects. It is usually conducted throught a myriad of web applications set up by the data providers. This means that, many times, such a task is conducted independently of the remaining research processes. This notebook tests functionalities o...
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Thematic cartography in R
1. Why this notebook? This is an R Markdown Notebook illustrating thematic cartography for a Departament in Colombia. It has been created, compiled and published from RStudio Cloud. This notebook aims to help Geomatica Basica students at Universidad Nacional to learn how to make thematic maps in R. Every student should replicate this notebook BUT...
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Exploring and mapping agricultural statistics
1. Why this notebook? This is an R Markdown Notebook illustrating estadisticas agricolas for the Antioquia departamento in Colombia. It has been created, compiled and published from RStudio Cloud. You are advised to use your own RStudio local installation, if you have one. Otherwise, do it on the cloud. This notebook aims to help Geomatica Basica...
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Getting, processing and visualizing elevation data
1. Why this notebook? This is an R Notebook created using R Studio Cloud. It illustrates several functionalities to obtain, process and visualize digital elevation models in R. It aims to help Geomatica Basica students at Universidad Nacional with their home activities during this time of social distancing. Everybody should publish a similar note...
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