Digital Earth Africa's Continental Standardised NDVI Anomalies

Background

Standardised NDVI Anomalies provide a measure of vegetation health relative to long term average conditions by measuring the departure, in units of standard devaiations, away from the long-term average. These indices can be used to monitor areas where vegetation may be stressed, and as a proxy to detect potential drought. Negative values represent a reduction from normal NDVI, while positive values represent an increase from normal.

Description

The Standardized NDVI Anomaly will have the following specifications:

• NDVI climatologies are developed using harmonized Landsat 5,7,and 8 satellite imagery from the years 1984 to 2020
• Anomalies will have monthly temporal frequency and include images from Landsat 8, Landsat 9, and Sentinel-2
• All datasets will have a native spatial resolution of 30 metres

Updating the pip requirements

Fix any requirement versions in docker/fixed-requirements.txt

Install pip-tools and then run pip-compile --output-file=docker/requirements.txt production/ndvi_tools/setup.py docker/fixed-requirements.txt.

Testing notes

Using the dev Sandbox, so that we have a full index of datasets, clone the NDVI repo and then install using pip pip install --editable ndvi-anomalies/production/ndvi_tools.

Dump out a DB for a single month:

odc-stats save-tasks --temporal-range=2021-08--P1M --grid=africa_30 --usgs-collection-category=T1 ls8_sr-ls9_sr-s2_l2a --tiles=160:171,80:91

or a subset:

odc-stats save-tasks --temporal-range=2021-08--P1M --grid=africa_30 --usgs-collection-category=T1 ls8_sr-ls9_sr-s2_l2a --tiles 170:181,80:91

Run one tile:

odc-stats run --config=production/ndvi_tools/config/ndvi_anomaly.yaml --location=file:///home/jovyan/ndvi ls8_sr-ls9_sr-s2_l2a_2021-08--P1M.db 2021-08--P1M/178/088

Additional information

License: The code in this notebook is licensed under the Apache License, Version 2.0. Digital Earth Africa data is licensed under the Creative Commons by Attribution 4.0 license.

Contact: If you need assistance, please post a question on the Open Data Cube Slack channel or on the GIS Stack Exchange using the open-data-cube tag (you can view previously asked questions here). If you would like to report an issue with this notebook, you can file one on Github.