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Notebooks to learn basic raster manipulation in Python using data from the NAIP program.

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carmengg/rasters_intro_SB_NAIP

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INTRO TO RASTERS!

To run the notebook just click on the Binder link below, no need to install anything:

Binder

In this notebook we will learn to do a some basic raster manipulation:

  1. Open a .tif raster file and look at some of their basic information
  2. Open a shapefile and look at some of its basic info
  3. Clip rasters using the shapefile
  4. Do some raster arithmetic by computing the Normalized Difference Vegetation Index (NDVI)
  5. Save our NDVI raster as a .tif file

REFERENCES:

Data

The images used in this repo come from the US National Agriculture Imagery Program (NAIP). This program provides high-resolution aerial images with four spectral bands: Red, Green, Blue and Near-Infrared. To prepare the rasters for this workshop I accessed the NAIP Dataset on Microsoft's Planetary Computer, where I also did the data pre-processing.

To learn more about how these images were collected, check out this short video: Mapping the Invisible: Introduction to Spectral Remote Sensing - NEON Science

Code

Some of the content in this project is based on the workshop Introduction to Geospatial Raster and Vector Data with Python from the The Carpentries Incubator. This is a great resource to go deeper into working with geospatial data with Python!

NDVI IN R

Some of the users running this notebook might be more familiar with the R programming language. Here you can see an example of doing a similar workflow in R. The repository for this project is available here https://github.com/carmengg/mexico_rasters.

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Notebooks to learn basic raster manipulation in Python using data from the NAIP program.

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