vendor-utils

Exploring Other Functions from rasterio and rio-xarray

Description: This example demonstrates how to use the rio-xarray and rasterio libraries to perform common geospatial operations on raster data. It includes reprojecting the coordinate reference system, clipping the raster to a bounding box, and resampling the raster resolution.

• Input:
  • ras1: Input raster in an initial coordinate reference system.
  • tif_file: Path to a TIFF file used for resampling.
  • bbox: Bounding box coordinates (minx, miny, maxx, maxy) for clipping the raster.
• Expected Output:
  • ras1_lonlat: Raster reprojected to the EPSG:4326 coordinate reference system.
  • clipped: Raster clipped to the specified bounding box.
  • Resampled raster saved as resampled_raster.tif in the specified directory.

Code Snippet:

```python

Reprojection

data_array_lonlat = data_array.rio.reproject(“EPSG:4326”) print(data_array_lonlat)

Clip the raster

from shapely.geometry import box

minx, miny, maxx, maxy = -90.32, 31.33, -89.90, 31.15 bbox = box(minx, miny, maxx, maxy) clipped = data_array_lonlat.rio.clip([bbox], crs=”EPSG:4326”)

Resample

from rasterio.enums import Resampling

scale_factor = 0.75 with rasterio.open(tif_file) as src: data = src.read( out_shape=( src.count, int(src.height * scale_factor), int(src.width * scale_factor) ), resampling=Resampling.bilinear )

profile = src.profile
profile.update(
    width=data.shape[2],
    height=data.shape[1]
)

with rasterio.open("VendorUtil_Planet/NewData/resampled_raster.tif", "w", **profile) as dst:
    dst.write(data)

print(“Success: Resample saved”)