Updated Oct 27, 2020

Radiant Earth Foundation

https://www.radiant.earth/

Louisa Diggs

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An open Library for Earth Observations Machine Learning that allows data scientists to search for and register geospatial training data and ML models on Radiant MLHub to address the world’s most critical international development challenges.

The R.E.F platform differentiated itself by first identifying and resolving the rate-limiting factors that obstruct efforts to discover, access and use data to guide climate-positive practices. Government organizations like NASA and UK Space Agency have similar, though less user-centric, platforms and, as they are obligated for domestic applications first, these data remain invisible to NGOs an...
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The R.E.F platform differentiated itself by first identifying and resolving the rate-limiting factors that obstruct efforts to discover, access and use data to guide climate-positive practices. Government organizations like NASA and UK Space Agency have similar, though less user-centric, platforms and, as they are obligated for domestic applications first, these data remain invisible to NGOs and climate researchers to whom it offers significant value. Technology factors also “strand” these data, inhibiting their efficient collection, curation, transfer, analysis & use by end-users. Policies that fail to facilitate efficient knowledge-management silo them further. We have changed this status quo by supporting the development of three open standards for EO data and tools: STAC (spatio-temporal asset catalogue); COG (cloud-optimized geoTIFF); and ARD (analysis ready data). These innovations have already catalyzed efforts to make imagery ready-for-use in cloud-based environments, interoperable between providers and platforms, and machine-learning ready. To date, users have contended with heterogenous metadata and challenging download conditions for manipulation and analysis (a near impossibility with internet speeds in some LMICs). Our innovation also comprises assets (open labelled image libraries) and tools for machine learning analysis of remotely sensed data, central to evaluating climate-induced risk and developing mitigation strategies.
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Stage 4: Transition to Scale

Radiant MLHub launched in 2019 as a resource for a community of practice, giving data scientists benchmarks they can use to train and validate their models and improve its performance. In Oct 2020, we have 14 training datasets and 1,255 subscribers.
Registered in United States as Non-Profitin United States as Non-Profit

Focus Areas:

Climate Change and Resilience, AI, Agriculture and 5 MoreSEE ALL

Climate Change and Resilience, AI, Agriculture, Data/Analytics, Other, Natural Resources, Evidence & Impact and Data Collection/Needs AssessmentsSEE LESS

Implemented In:

United Kingdom, Brazil, Japan and 6 MoreSEE ALL

United Kingdom, Brazil, Japan, India, Slovenia, Senegal, Solomon Islands, Vanuatu and FijiSEE LESS

9
Key Partners
9
Countries Implemented In
1,255
Customers
4
Employees
$6,000,000
Funds Raised to Date

Problem

Earth observation (EO) data from satellites, planes & UAVs are essential to climate change action, however the volume, velocity & variety of EO data inhibit its discovery, which also requires time and expertise. There is no central repository for open EO data & tools; most are proprietary & costly. Internet speed, software, storage, analytic capabilities, human resource limitations, & cost pose additional barriers to utilizing these ostensibly “free” data.

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Solution

The platform simplifies discovery and use of geospatial data to strengthen climate change research. Essential data (weather, soil composition, crop suitability, population, and hydrology) is updated daily and weekly from orbiting instruments. Users benefit from open-source machine-learning tools that facilitate rapid data analysis (e.g., land-cover changes, climate disasters). These data are fundamental to climate risk mitigation planning, and required for Green Climate Fund applications

Target Beneficiaries

We serve institutional users (non-profits, NGOs, intergovernmental, multilateral and regional government agencies), individuals (academics, students) and entrepreneurs (developers & start-ups) who deploy our data & technologies to create meaningful solutions and spark innovation in the global development tech sector. The beneficiaries of their work are global, number in the millions, and span many sectors including and beyond climate change.

Mission and Vision

Radiant Earth Foundation's mission is to connect people globally to Earth imagery, geospatial data, tools, knowledge, and solutions to meet the world’s most critical challenges. This is encompassed by our vision of "open geospatial data for positive global impact."

Competitive Advantage

We are differentiated from similar, but commercial start-ups that focus on insurance/futures markets and provide monitoring indices at global scale as a commercial toolbox. In contrast, as a non-profit, we designed the platform agnostic of specific projects, and useful for every earth observation (EO) application, offering unique innovations like industry data standards that optimize imagery for cloud-computing, & the first open training-data library for global land cover classification. We offer multiple tools for climate action: monitoring of atmospheric conditions & weather; agricultural features that determine soil suitability & contribute to improved seed stock selection; data for disaster planning; deforestation measurement & monitoring; fire detection and tracking. We lead machine learning innovation with training data libraries of African crops in climate-vulnerable areas and enable climate-focused EO solutions to small-island developing-states.

Planned Goals and Milestones

In 2019-20 we will continue to build our image libraries & training data sets to facilitate analysis of earth observation data at scale. Our goal is to scale our climate work with small island developing states in the Pacific to the Caribbean and potentially Micronesia thru nascent partnerships. We will also expand our capacity building work through our our relationship with the University of Twente and others, as well as through Radiant-led training activities and resources (e.g.Learning Hub).
Funding Goal3,000,000

The Team Behind the Innovation

Executive Director and Chief Data Scientist Hamed Alemohammad has extensive expertise in remote sensing and imagery techniques particularly in developing new algorithms for multi-spectral satellite and airborne-based observations. Marketing and Communications Manager Louisa Nakanuku-Diggs is a science and technology communications specialist. Business Development Manager Amber Myers is an experienced nonprofit fundraiser and strategist.

EXECUTIVE TEAM INCLUDES WOMEN

Milestone

Mar 2019
In The News
ORGANIZATIONGovernment of Fiji
Mar 2019
Key Partnership
Implementation
ORGANIZATIONAfrica Centers for Disease Control (ACDC)
Mar 2019
New Country Implemented In
Fiji
Sep 2017
Key Partnership
ORGANIZATIONGovernment of Australia
Feb 2017
Created

Supporting Materials

2019-Annual-Report-orientation-null.pdf