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IBM Environmental Intelligence

This repository contains sample applications of IBM Environmental Intelligence.

General Notes

If you like to contribute, please read CONTRIBUTING.md first. A list of maintainers is recorded in MAINTAINERS.md.

Geospatial APIs

For documentation and tutorials regarding how to use the ibmpairs SDK for Geospatial APIs, please consult the official documentation.

Refer to the samples below for various industry use cases of Geospatial APIs.

Example Description Industry
Normalized Difference Vegetation Index (NDVI) Normalized Difference Vegetation Index (NDVI) is used to quantify vegetation greenness and is useful in understanding vegetation density and assessing changes in plant health. Agriculture
Water and Moisture Detection Normalized Difference Moisture Index (NDMI) and Modified Normalized Difference Water Index (mNDWI) provides a relative indication of the wetness or dryness of an area, helping to identify potential water stress or drought conditions or combustibility levels in fire-prone areas. Agriculture, Disaster Events
Sea Rise Risk Prediction Geospatial APIs can help determine the possible regions that come under the threat of rise in sea levels Climate Change, Disaster Events

Geospatial APIs Above Ground Biomass (AGB)

To know the basics of Geospatial APIs Above Ground Biomass (AGB) Dataset, start with the AGB Catalogue sample.

To get an understanding of the Geospatial APIs Above Ground Biomass (AGB) Species Agnostic usage refer to AGB Species Agnostic sample.

To get an understanding of the Geospatial APIs Above Ground Biomass (AGB) Species Specific usage refer to AGB Species Specific sample.

Refer to the samples below for various industry use cases of Geospatial APIs Above Ground Biomass (AGB)

Example Description Industry
Historical Difference AGB Above Ground Biomass (AGB) can be used to find out how much the AGB cover has changed over the years for various use case like measuring deforestation, wildfires etc. Disaster Events

Historical Weather On Demand

Refer to the samples for:

Historical Weather On Demand - Direct API

Historical Weather On Demand - HDAT API

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