Habitat conservation and monitoring

The Group on Earth Observations (GEO) BioModelos project was created by scientists from the Humboldt Institute, who formed to generate the knowledge necessary to assess the state of biodiversity in Colombia, seeking to ensure that sustainable decisions can be made about future development. Biomodelos is a free digital tool that enables experts to validate and publish Species Distribution Models (SDMs), which are crucial to the measurement of habitat suitability for species. 

In 2020, BioModelos was awarded grant funding and a support package through the GEO-GEE program run by Google, GEO and EO Data Science. The EO Data Science team is providing essential Google Earth Engine (GEE) training, support and billing capabilities to the BioModelos team to help integrate GEE into their platform and achieve their project outcomes. 

As the landscape in Colombia, and other parts of the world is increasingly at risk of being degraded by businesses or governments looking to repurpose land for profit - the BioModelos team seeks to preserve habitats for local plant and animal species. Essential biodiversity variables are a measurement for studying and managing biodiversity change according to the GEO Biodiversity Observation Network (GEO BON). SDMs are one part of measuring habitat suitability, however there are some significant challenges in the modelling. 

Future-proofing biodiversity

To counteract the demanding capacity and processing requirements; Humboldt Institute Scientists have generated the SDMs required for modelling in GEE—allowing for near real-time habitat loss notifications. This allows for machine learning algorithms that generate dynamic distribution models with the capability to evaluate loss or gain of species habitats from landscape transformations. Further, precision has been improved with the ability to run species distribution maps at a regional scale. 

Funding to accelerate environmental modelling

Funding provided by the GEO-GEE program, and training provided by the EO Data Science team, has allowed BioModelos to supply decision makers in the community with more timely and comprehensive information to produce national reports for monitoring and management, conservation and improved monitoring indicators of biodiversity. Whatsmore, GEE has played a crucial role in supporting BioModelos with infrastructure and data. 

How BioModelos will contribute to global sustainability targets

The BioModelos team aims to begin with developing and predicting dynamic SDMs for birds in Colombia, with the vision to over time, scale the solution for any biological group and region on the planet. The group also hopes to improve progress monitoring indicators within national reports, using predictive modelling from GEE. With this, they will be able to address several Aichi Biodiversity Targets, namely from Strategic Goals B and C -  

  • Reducing direct pressures on biodiversity, promoting sustainable use of the environment and; 
  • Improve the status of biodiversity by safeguarding ecosystems, species and genetic diversity 

Backed by our team of experts and the power of GEE, the BioModelos team are making impactful contributions to preserving biodiversity and habitats for the future. 

Perhaps the most encouraging outcome of the GEE funding is the ability for the team to increase their GEE capacities through the support and training supplied from the EO Data Science team. Thus, allowing for SDMs to continue to be generated for decision-making in Colombia at local, regional and national scales. 

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 in July 2020. Across 22 countries, 32 projects were selected for the program which offers $3 million USD towards product licenses and $1 million USD in technical support from EO Data Science to help operationalise their science as they strive to tackle the world’s biggest sustainable development challenges. So far EO Data Science has: 

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Conducted 38 Google Earth Engine training courses attended by 680 program participants

Resolved over 105 support tickets with a live support desk

Organised five virtual meetups for projects across the world to exchange knowledge and network with one another

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