Chapter 13: Raster-Vector Integration Patterns¶
Part II — Geographic Data Science
Learning Objectives¶
By the end of this chapter you will be able to:
- Choose the right substrate for each operation
- Convert between vector and raster without losing precision
- Build proximity drivers using distance transforms
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# Standard imports
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import geopandas as gpd
import rasterio
from scipy import ndimage
# Standard imports
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import geopandas as gpd
import rasterio
from scipy import ndimage
13.1 When to Use Which Substrate¶
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# Code for section: When to Use Which Substrate
# Code for section: When to Use Which Substrate
13.2 Vector to Raster: rasterio.features.rasterize()¶
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# Code for section: Vector to Raster: rasterio.features.rasterize()
# Code for section: Vector to Raster: rasterio.features.rasterize()
13.3 Raster to Vector: rasterio.features.shapes()¶
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# Code for section: Raster to Vector: rasterio.features.shapes()
# Code for section: Raster to Vector: rasterio.features.shapes()
13.4 Zonal Statistics with rasterstats¶
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# Code for section: Zonal Statistics with rasterstats
# Code for section: Zonal Statistics with rasterstats
13.5 Distance Transforms: Vector to Proximity Driver¶
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# Code for section: Distance Transforms: Vector to Proximity Driver
# Code for section: Distance Transforms: Vector to Proximity Driver
13.6 Performance Patterns for Integration¶
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# Code for section: Performance Patterns for Integration
# Code for section: Performance Patterns for Integration
Exercises¶
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# Code for section: Exercises
# Code for section: Exercises
Further Reading¶
- TODO: add references.