How to extract exact values from a raster file (TIFF) using a shapefile, using xarray to open the raster

Diving into Raster Data: How to Snag Exact Values with Shapefiles and Xarray

Ever needed to pull specific data points from a raster image based on geographical boundaries? It’s a common task in fields like environmental science, city planning, and even agriculture. Think of it as pinpointing information within a digital map using custom-drawn shapes. This guide will walk you through extracting those exact values from a TIFF raster file using a shapefile, all thanks to the magic of the xarray library in Python.

The Lay of the Land: Key Ingredients

Before we get our hands dirty with code, let’s quickly break down what we’re dealing with:

• Raster Data (TIFF): Imagine a digital image, but instead of colors, each pixel holds a value – maybe elevation, temperature, or rainfall. TIFF is a popular format for storing these kinds of images.
• Shapefile: This is like a digital drawing of shapes – could be property lines, forest patches, or city districts. Shapefiles define the areas we want to extract data from.
• Xarray: Xarray is a super-cool Python library that helps us work with these raster images. It’s like NumPy, but with labels, making it way easier to keep track of what’s what.

Gearing Up: Installing the Essentials

First things first, make sure you have these Python libraries installed. Think of it as gathering your tools before starting a project:

• xarray: The star of the show!
• rioxarray: Xarray’s geospatial sidekick, handling the reading and writing of raster data.
• geopandas: For playing with shapefiles like a pro.
• rasterio: The engine under the hood for rioxarray, dealing with the nitty-gritty of raster files.
• shapely: For doing cool things with shapes, like figuring out if they overlap.

Install them all with a simple pip command:

bash