georeader-spaceml 1.0.0

Lightweight reader for raster files

georeader

Read data from rasters: very few dependencies, reads from cloud storage and lazy loading.

Install

# Install with minimal requirements (only rasterio, numpy as shapely)
pip install git+https://github.com/spaceml-org/georeader#egg=georeader

# Install with Google dependencies (to read objects from Google Cloud Storage or Google Earth Engine)
pip install git+https://github.com/spaceml-org/georeader#egg=georeader[google]

# Install with Planetary Computer requirements
pip install git+https://github.com/spaceml-org/georeader#egg=georeader[microsoftplanetary]

Getting started

# This snippet requires:
# pip install fsspec gcsfs google-cloud-storage
import os
os.environ["GS_NO_SIGN_REQUEST"] = "YES"

from georeader.readers import S2_SAFE_reader
from georeader import read

cords_read = (-104.394, 32.026) # long, lat
crs_cords = "EPSG:4326"
s2_safe_path = S2_SAFE_reader.s2_public_bucket_path("S2B_MSIL1C_20191008T173219_N0208_R055_T13SER_20191008T204555.SAFE")
s2obj = S2_SAFE_reader.s2loader(s2_safe_path, 
                                out_res=10, bands=["B04","B03","B02"])

# copy to local avoids http errors specially when not using a Google project.
# This will only copy the bands set up above B04, B03 and B02
s2obj = s2obj.cache_product_to_local_dir(".")

# See also read.read_from_bounds, read.read_from_polygon for different ways of croping an image
data = read.read_from_center_coords(s2obj,cords_read, shape=(2040, 4040),
                                    crs_center_coords=crs_cords)

data_memory = data.load() # this loads the data to memory

data_memory # GeoTensor object

>>  Transform: | 10.00, 0.00, 537020.00|
| 0.00,-10.00, 3553680.00|
| 0.00, 0.00, 1.00|
         Shape: (3, 2040, 4040)
         Resolution: (10.0, 10.0)
         Bounds: (537020.0, 3533280.0, 577420.0, 3553680.0)
         CRS: EPSG:32613
         fill_value_default: 0

In the .values attribute we have the plain numpy array that we can plot with show:

from rasterio.plot import show
show(data_memory.values/3500, transform=data_memory.transform)

Saving the GeoTensor as a COG GeoTIFF:

from georeader.save import save_cog

# Supports writing in bucket location (e.g. gs://bucket-name/s2_crop.tif)
save_cog(data_memory, "s2_crop.tif", descriptions=s2obj.bands)

Tutorials

Sentinel-2:

• Reading Sentinel-2 images from the public Google bucket
• Explore metadata of Sentinel-2 object
• Query Sentinel-2 images over a location and time span, mosaic and plot them

Other:

• Tutorial to read overlapping tiles from a GeoTIFF and a Sentinel-2 image
• Example of reading a Proba-V image overlapping with Sentinel-2 forcing same resolution
• Work with EMIT images

Citation

If you find this code useful please cite:

@software{georeader,
  author = {Mateo-García, Gonzalo},
  month = {11},
  title = {{georeader}},
  url = {https://github.com/spaceml-org/georeader},
  version = {0.0.1},
  year = {2022}
}