dynamic-world 0.0.0

Land-use land-cover analysis using Dynamic World App from Earth Engine

dynamic-world 🛰️

Wrapper package around Google's Dynamic World App [^1], to easily monitor forests and calculate their co2 storage on a near-real time.

[^1]: This dataset is produced for the Dynamic World Project by Google in partnership with National Geographic Society and the World Resources Institute.

Install

pip install dynamic-world

Usage

Given a Forest (defined as a directory with some configuration files, see bellow), this package retrieves statistics and images of it. See Jupyter tutorial for a usage example.

Forests

Each forest (or "proyect") is defined inside a directory with a given name and 2 files:

1. A forest_config.yml (name is mandatory) which looks like this:

# Name of the forest/proyect
name: Sample

# Locations of the geojson file
geojson: './sample.geojson'

# Co2 factor: how many tons of CO2 are stored on average per hectare
co2_factor: {
    'trees': 591.85,
    'grass': 6,
    'bare': 6,
    'crops': 11.5,
    'flooded_vegetation': 6,
    'other': 0,
    'factor_pixel': 100, # Indicates how many pixels are (on average) inside a hectare
  }

# Date in which the reforestation started, in format YYYY-mm-dd
start_date: '2022-01-01'

2. A valid geojson file see (named as defined in forest_config.yml) that defines the area

Internally, forests are stored as a ForestConfig instance (see dynamic_world.configurations for more details).

Available calculations

Given a forest and a pair of dates, we download the forest's landcover image, landcover statistics and total CO2 calculation. In other words, we mean the amount of CO2 (measured in tons) that a forest stores (and therefore is not released into the atmosphere if it was burned :D)

The forest image is stored as a Cloud Optimized Geotiff file. The expression used for the file-name is the following:

f"{forest.name.replace(' ', '_')}_{start_date}_{end_date}.cog.tif"

For reductions we use the Mode (polling). If a very large time interval is specified, recent changes in the forest will be masked by old pixel values. It is encouraged to use the smallest possible time intervals (at least a week is required or there may not be data). However, depending on some factors (such as the amount of clouds), specifying a small time interval may result in many NA (see mrv.calculations documentation for further info on how NA are treated when calculating the co2 factor).

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Development notes

We encourage developers to open the repository using VSCode remote container functionality.

How to run tests locally

• to test run 'pytest' in the root directory of the proyect
• to run coverage use 'pytest --cov mrv --cov-branch --cov-report term-missing --disable-warnings'

How to run tests in docker

# Build test docker
docker build --tag dw --file Dockerfile --target dev .

# Run lint and tests
docker run dw /bin/bash -c "flake8 && pytest"