1 June, 2021

GEO-GEE: Ecological Integrity Index

For our final GEO-GEE project blog, we look at the Ecological Integrity Index being developed by a team at Northern Arizona University. The index will offer a way to prioritise actions intended to conserve high quality habitats in Colombia and around the world. This project is one of 32 selected as part of the Group on Earth Observations (GEO) - Google Earth Engine (GEE) Program that provides funding to tackle environmental and social challenges using open Earth Observation (EO) data.

We spoke with Ivan Gonzalez, project Principal Investigator and a native of Bogotá, Colombia—to learn more about the Ecological Integrity Index and how his team will be using GEE to help describe temporal and spatial dynamics in each ecosystem in Colombia, identifying natural trends. 

Ivan, can you provide us with an overview of your project?

Our team is working to generate a spatio-temporal index that we call the "Ecological Integrity Index" using remotely sensed data in an attempt to evaluate how ecosystems have changed over the years, in comparison with well conserved areas in Colombia as a reference.

We understand that some variations in the values of remotely sensed data are a response to natural dynamics, but also human activities. Our efforts are focused on identifying which remote sensing indices are the most appropriate to assess different ecosystems and transitions. We also hope to quantify both natural and human-induced variations to create an integrated index that will benefit decision makers working on the ground.

What is the challenge that you want to tackle?

Many ecosystems have been affected by human activities, and one of our key challenges is identifying where negative impacts are occurring. A few current approaches focus on forested ecosystems, where changes are more notorious than in natural savannas.

Remote sensing data that is currently available has historic records that can uncover trajectories in remote sensing indices, such as the Normalised Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), among others. By comparing a long time series with training data, we can provide a monitoring tool for several ecosystems. Research, management and restoration priorities can be defined using this quantitative approximation, especially in poorly studied ecosystems.

How will the Ecological Integrity Index help your community?

The Index can be used by local organisations in Colombia that are collaborating on our project. The target ecosystems we focus our research on are areas without extensive monitoring instruments or long-term data collection. 

This remote sensing approach is a low-cost mechanism to monitor isolated ecosystems and protected areas. Once we deliver our first results, we hope to provide a better understanding of ecosystem dynamics and how remote sensing can measure ecosystem integrity. 

How does Google Earth Engine help you achieve your project-related goals?

GEE provides powerful analytics capabilities and comprehensive datasets that allow temporal and spatial understanding of ecosystem changes. The proposed Index is not a complex calculation, but requires a considerable amount of data capable of characterising the patterns and dynamics of natural and transformed areas. 

The GEE data catalogue also includes several datasets with complete spatial coverage of many ecosystems and countries. Also, GEE allows us to run several calculations in a reasonable amount of time, based on the prototype analysis we have developed. Running this on another platform would require more storage, processing and time to carry out our project. 

How will the GEO-GEE funding help your project? 

This GEO-GEE funding will allow us to test the index and cooperate with the Humboldt Institute, National Parks office, Conservation International, and The Nature Conservancy in Colombia which are seeking solutions to environmental challenges related to sustainable land and water use in a changing climate.

The training EO Data Science has provided, has guided us in understanding and exploring more utilities from the platform. Another benefit for our project was getting to know other projects’ goals and interests. During the virtual meetup, speakers from other projects explained their interests, datasets, and methodological approaches which have been useful for discussions about our current methodology.

What does success look like to you?

A robust GEE App where the index can be customisable in terms of variables, time and spatial extent is one of the successful results we are pursuing. To ensure this is possible, the methodology behind the index should be responsive and informative for the different ecosystems we are analysing. We hope to have not only a final result but the possibility to apply the methodology as users require, even in areas outside of Colombia. Lastly, we hope to provide an informative application and method for local authorities and researchers in Colombia. 


EO Data Science’s role in the GEO-GEE Program

EO Data Science partnered with Google Earth Engine and the Group on Earth Observations to launch the GEO-GEE Program, which supports GEO member countries to operationalise their science as they strive to tackle the world’s biggest sustainable development challenges.

In July 2020, 32 projects across 22 countries were selected for the program which offers $3 million USD towards product licenses and $1 million USD in technical support from EO Data Science. This funding and support will help these projects tackle global challenges using open Earth data. Read the announcement and list of winners here.

Follow us on TwitterLinkedIn or Facebook to hear about more GEO-GEE winning projects.

Feature image: References NDVI curves from Amazonia in three different time scales (long-term, yearly, monthly)

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