Land & Carbon Lab: An Unprecedented Land Monitoring System, Powered By Resource Watch

On Monday November 1, 2021  World Resources Institute, alongside founding partners, funders, and collaborators, launched the Land & Carbon Lab, a comprehensive global land monitoring system to address the global land squeeze. The monitoring system will offer new cutting-edge global data at unprecedented resolution, thereby advancing goals across areas such as restoration, nature-based solutions and land use planning. Resource Watch is providing critical data support by presenting, processing, and visualizing the data produced as part of the Land & Carbon Lab initiative. 

The Land & Carbon Lab initiative seeks to address the challenge of the “Land Squeeze” and to support solutions for climate, biodiversity, and humanitarian crises. Land resources are finite and communities rely on land to produce food, feed, fiber, and fuel growing world population and expanding middle class is projected to make this challenge bigger in the futureAgricultural land is predicted to expand by over 600 million hectares by 2050 if the current trend remains. 

Figure : Land & Carbon Lab As A Global Monitoring System

Unprecedented High-Resolution Data

Land & Carbon Lab partners are leveraging open satellite imagery such as Landsat (NASA/USGS) and Sentinel (ESA) to monitor land and its nature-based carbon at a global scale. The new datasets will enable stakeholders to take on the challenges from the global land-squeeze, combat climate change, protect biodiversity, and improve people’s lives. This is achieved by monitoring the world’s land and its nature-based carbon, so data can turn into, and generate insights for collective accountability.

As a Founding Partner, Resource Watch contributes by presenting, processing, and visualizing key datasets of the Land & Carbon Lab initiative on the Resource Watch platform. The datasets will also be freely available from the open Resource Watch API. Here are some of the new preliminary datasets of the Land & Carbon Lab initiative:

1. Trees in Mosaic Landscapes

Local communities, investors and donors need information about where trees grow. Until now dataset on tree cover has primarily focused on forests, but users also need detection of trees more accurately in mosaic landscapes and identify which areas could be restored.

The new Trees in Mosaic Landscapes dataset provides millions of hectares of trees outside of forests. The dataset uncovers trees not previously available in existing tree cover databases. Developed by WRI’s Restoration Initiative the dataset detects billions of trees, focusing on Sub-Saharan Africa and Latin America, an area 40% larger than the whole United States.

Explore the Trees in Mosaic Landscapes on Resource Watch here.

2. Global Land Cover Change

Land & Carbon Lab is partnering with the Global Land Analysis & Discovery (GLAD) lab at the University of Maryland to produce the first-ever high-resolution map of global land cover change over the last 20 years. The map will distinguish eight general land cover classes: Forest, Cropland, Built-Up Area, Water, Bare Ground, Short Vegetation, Snow/Ice, and Wetlands. Preliminary data for several of these classes can now be explored in Resource Watch, but are not yet available for download. The final data, which will include annual change detection, are expected in the first half of 2022 and will be available on Resource Watch.

Explore Cropland Expansion in Resource Watch.
Source: Global Land Cover Change (University of Maryland).
Beta version. Data still under review and subject to change.

Explore Expanding Built-Up Areas in Resource Watch.
Source: Global Land Cover Change (University of Maryland).
Beta version. Data still under review and subject to change.

Explore Forest Height Change in Resource Watch.
Source: Global Land Cover Change (University of Maryland).
Beta version. Data still under review and subject to change.

3. Forest Carbon Fluxes

Forest Carbon Flux data quantifies emissions, removals and net carbon fluxes consistently over any area of forest land. This data enables users to view forest-related carbon dynamics at any scale, providing a detailed understanding of how various forested areas are contributing to global emissions and removals.

Explore Forest Carbon Fluxes on Global Forest Watch here.

4. Seasonal Global Land Cover

Land & Carbon Lab, is partnering with Google and the National Geographic Society, on a project to leverage advanced artificial intelligence methods and large training datasets to develop a global land cover dataset at an unprecedented 10-meter resolution. The dataset, which is still in preparation, will cover nine land cover classes and is based on Sentinel-2 satellite imagery. With a dataset of such high-resolution, community organizations, governments and researchers will be able to better understand seasonal and intra-annual seasonal land cover changes.

The dataset will become available on Resource Watch.

Animation: Monthly land cover over the Okavango Delta, Botswana, from the forthcoming Seasonal Global Land Cover dataset

Driving impact

Land & Carbon Lab is working with a diverse group of partners, connecting the people who are at the vanguard of land monitoring with those at the frontlines of land use decisions– from corporate leaders and policymakers to Indigenous Peoples and farmers. In order to achieve the intended impact and get the tool in the hands of decision-makers, Land & Carbon Lab is looking for collaborations around the world to advance 6 main goals.

  1. Unlocking Finance for Nature
  2. Restoring Degraded Land
  3. Greening Commodity Markets
  4. Empowering Indigenous Peoples and Local Communities
  5. Combating Deforestation
  6. Strengthening Land Use Policy and Planning

All six targets are deeply interconnected, but each requires dedicated efforts on the ground in order to advance. If you’d like to know how land and carbon monitoring data can serve you or if you’d like to propose a partnership that targets one or more of these goals, please reach out!

Check out our catalog of trusted and timely data

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