## Recently Published

##### Charting forest gain and loss

As it reads.

##### Making SDG thematic maps

An R notebook illustrating map making code for the MP164 course.

##### Geometric functions for simple features

This notebook illustrates several geometric functions provided by the *simple features for R* package.

##### Again EVA

How to read and subset xlsx data.

##### Spatial interpolation of soil organic carbon

This notebook illustrates spatial interpolation using IDW and Ordinary Kriging techniques.

##### How to get raster soil data from ISRIC

A notebook illustrating how to use the gdalUtils library and the WebDAV protocol to get soil raster data from a given geographic area.

##### Elevation data processing and analysis in R

This notebook illustrates several functionalities for obtaining morphometric variables from digital elevation models.

##### Spatial interpolation of climate data

This notebook illustrates how to conduct spatial interpolation of point data using the stars, geostat and automap libraries.

##### Get monthly climate normals using ClimateR

A simple notebook for GB2022 students.

##### Crop production dynamics

This notebook illustrates analysis of multi-year agricultural stats.

##### How to make thematic maps - V2

This notebook illustrates how to make thematic maps showing production for two important crops in a department.

##### GB2022 - Notebook2

It describes how to make thematic maps showing major crops in a given department.

##### GB2022 - Notebook1

It descibes how to select crops with largest production from the 2020 EVA dataset.

##### Exploring random forest based regression of soil moisture

A notebook to guide image analysis tasks in the HERMES project.

##### Looking again at spatial interpolation

Testing the gstat & stars alliance.

##### Spatial Interpolation revisited

This update aims to fix a problem originated from the shift from PROJ4 to PROJ6 in the recent versions of the rgdal. In this notebook I use the WKT format instead of the PROJ4 to get the CRS.

##### Healthcare accessibility and population

Another proof-of-concept.

##### Water ocurrence change intensity

A proof-of-concept.

##### Getting climate data from R

This notebook illustrates how to obtain and visualize global climate data in R.

##### A tutorial on pixel-based land cover classification using random forests

This notebook illustrates land cover classification from multispectral imagery using the package ranger which is a fast implementation of random forests.

##### Accuracy assessment of land cover classification

This notebook illustrates how to assess thematic accuracy of pixel-based land cover classification using different metrics.

##### My fifth notebook: elevation data

This R Notebook illustrates several functionalities to obtain, process and visualize digital elevation models in R.

##### CART-based land cover classification

This notebook illustrates how to conduct land cover classification from multispectral imagery using the terra library.

##### Joining attributes to spatial features

This is the fourth notebook that GB students need to write to get started with R geospatial capabilities.

##### Evaluaciones Agropecuarias Municipales

This is the third notebook that Geomática Básica students have to write to get started with R & RStudio.

##### Image statistics of a Landsat 8 image

This notebook illustrates how to calculate uni-band and multi-band statistics of remote sensing images using the raster library.

##### Satellite image contrast enhancement with R

This notebook illustrates how to improve image visualization of remote sensing images (when traditional contrast stretch techniques are not good enough).

##### Landsat image exploration with terra

This notebook illustrates how to read, visualize and explore Landsat satellite images using the terra package.

##### Kriging made simple

This notebook illustrates kriging interpolation using code written by Barry Boessenkool.

##### Sentinel-2 in R

This notebook illustrates how to read, subset and process Sentinel-2 data in R.

##### Access global soil data from R

This is an R Markdown Notebook which illustrates how to access SoilGrids using the webDAV protocol.

##### Aggregating Earth Surface data using GEE and R

Author: Francesco Pirotti <francesco.pirotti@unipd.it>
#Summer Webinar Series — Sept. 29, 2020

##### Accessing elevation data from R

This notebook illustrates how to use the elevatr package for getting raster elevation data.

##### Leaflet mapping using simplified geometries

This notebook illustrates how to simplify simple features geometries in order to produce lightweight files, and thus, be able to publish leaflet maps in RPubs.

##### Getting started with Leaflet maps

This is a workaround to "publish" maps when uploading the html to RPubs is not possible.

##### Leaflet - Part1

This notebook creates a leaflet map from a table of points

##### Fixed Rank Kriging

A quick exploration of FRK.

##### Spatial Interpolation

This notebook illustrates spatial interpolation using precipitation data as example.

##### Land Cover Change Metrics [2]

A notebook to explore land cover change using the ESA CCI Land Cover Product

##### Land Cover Change Metrics

A notebook to explore land cover change using the MODIS Land Cover Product

##### Get Soil Moisture Data from R

Illustration of functionalities provided by the R library smapr.

##### Thematic cartography in R

This notebook illustrates functionalities provided by the cartography package

##### Exploring and mapping agricultural statistics

An R notebook to illustrate geomatic concepts useful in agronomy.

##### Getting, processing and visualizing elevation data

This is an illustrative R notebook aimed to help GB students at UNAL with their home activities during this social distancing's time.

##### Landsat Image Exploration

This is an R Notebook based on the tutorial Remote Sensing Image Analysis with R written by Aniruddha Ghosh and Robert J. Hijmans. It covers the exploration section.

##### Texture Metrics 2

This notebook explores principal component analysis of textural metrics

##### Texture Metrics 1

This notebook explores texture metrics.

##### Illustration of an animated cartogram

This notebook uses a 1993-2015 time series with the undernourished population percentage by country and population data for producing cartograms showing number of people severely affected by food insecurity.

##### Useful geometric operations

Illustration of a meaningful set of convex hull, alpha hull and buffer operations.

##### Women in the world - No. 1

A proof-of_concept on women and gender inequality

##### Mapping World Development Indicators

A guide for mapping development indicators using World Bank data.

##### Reading and plotting GPX with R

There are several options to read, transform, and display point and track data stored in GPS Exchange (GPX) format using R. This notebook shows one of them.

##### G4D - Assignment No. 1

Here you find detailed instructions to write your own notebook.

##### Geospatial data in R

A synthesis based on rspatial.org

##### Making basic graphics in R

As said.

##### Procesamiento de la base de datos global armonizada de suelos (HWSD) usando R

Esta nota explica cómo acceder y consultar la base de datos global armonizada de suelos (HWSD) [3] usando R, el programa estadístico de software libre [7].

##### Soil Moisture Accuracy Assessment

This document evaluates accuracy of soil moisture estimated from remotely sensed data. A SMAP Level 3 dataset is used as reference.

##### SMAP data

This document describes how to search and download NASA SMAP data.

##### Surface Soil Moisture from Remotely Sensed Data

Proof of concept to estimate surface soil moisture from topographic and multispectral índices.

##### Accessing NASA data

A brief overview of the nasadata package functionalities

##### Testing GSIF and RQGIS packages

This is a simple test of a few geospatial functionalities