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GEE Zonal

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This python package provides a wrapper function to request temporal and zonal statistics from Google Earth Engine (GEE) datasets.

Summary

A zonal statistics function was created to ease the process of working with the GEE API. The function can work with any raster data loaded to EE (ee.ImageCollections or ee.Image) and vector features (geopandas.GeoDataFrame or ee.FeatureCollection), and returns tabular data.

Statistics can be requested at various temporal resolutions (original frequency, monthly, or annual). The workflow conducts pixel-by-pixel temporal aggregations, before summarizing statistics over target features.

Additionaly, the package provides functionality to quickly search the GEE Catalog.

Installation

The required dependencies are earthengine-api, geopandas, geojson, and notebook. The package (and dependencies) can be installed via pip:

pip install gee_zonal

Setup

The Earth Engine Python API needs to be authenticated with a Google account. First, sign up to Google Earth Engine here.

Launch a jupyter notebook, and authenticate your account with the ee library.

import ee
ee.Authenticate()

You can check that this worked by running ee.Initialize(), then import and run the library:

from gee_zonal import ZonalStats, Catalog

If the pip installation is not working, you can recreate the environment before and install the package from source:

conda create -n ee
conda activate ee
conda install -c conda-forge earthengine-api geopandas notebook ipykernel​
git clone https://github.com/worldbank/GEE_Zonal.git
python setup.py build
python setup.py install
python -m ipykernel install --user --name ee --display-name "Earth Engine"

Usage

ZonalStats()

Main class to calculate temporal and zonal statistics using the GEE backend. The object can be initialized with parameters specifying data inputs and the type of aggregation.

import ee
from gee_zonal import ZonalStats
AOIs = ee.FeatureCollection('<id of ee.FeatureCollection>')
AOIs = '<path to shapefile>'
zs = ZonalStats(
  collection_id = 'LANDSAT/LC08/C01/T1_8DAY_NDVI',
  target_features = AOIs,
  statistic_type = "all", # all includes min, max, mean, and stddev
  frequency = "annual",
  temporal_stat = "mean"
)

See docstring for more details on the input parameters for ZonalStats() and the example notebook.

The output statistics can be retrieved directly in the notebook (as a DataFrame):

res = zs.runZonalStats()

Or retrieved from Google Drive as a csv table if an output_name and output_dir were specified.

Catalog()

Inventory of Earth Engine datasets with some functions to search catalog by tags, title, and year / time period

from gee_zonal import Catalog
cat = Catalog()

The catalog object contains a datasets variable, a DataFrame containing a copy of the Earth Engine data catalog, retrieved from Earth-Engine-Datasets-List.

cat.datasets

Search functions

results = cat.search_tags("ndvi")
results = results.search_by_period(1985, 2021)
results = results.search_title("landsat")
print(results)

Additional Resources

License

World Bank Master Community License Agreement.