Forest Carbon: Reliable, Scalable Carbon Estimates | Planet

Forest Carbon: Reliable, Scalable Carbon Estimates | Planet  planet.com

sdgtalks sdgtalks
Nov 7, 2023 - 23:00
0 30
Forest Carbon: Reliable, Scalable Carbon Estimates | Planet




HOW IT WORKS

Calibrated and evaluated with high quality airborne and spaceborne laser measurements

Drawing on cutting-edge scientific methods, we utilize deep learning models trained and validated on a massive global library of airborne LiDAR totalling more than 14 million square kilometers to produce estimates of forest height and cover. We leverage NASA’s Global Ecosystem Dynamics Investigation (GEDI) spaceborne LiDAR to convert these estimates into wall-to-wall, GEDI-like, forest carbon data. Each metric relies on novel cloud masking, pixel selection, multi-sensor fusion, and temporal harmonization techniques developed to minimize year-over-year measurement variability. The result is a unique, high-quality data feed which can capture nearly tree-scale forest change globally and provide actionable monitoring of carbon stocks.

Planet’s Forest Carbon Diligence estimated aboveground live carbon (left) over a region in the Congo Basin of Central Africa. Spaceborne LiDAR measurements from the GEDI mission (center) shown as a series of sparse points across the landscape. Scatterplot with associated validation metrics comparing the observed GEDI measured carbon to Planet’s predicted carbon estimates at 1 sq km resolution (right).

Planet’s Forest Carbon Diligence estimated aboveground live carbon (Top left) over a region in the Congo Basin of Central Africa. Spaceborne LiDAR measurements from the GEDI mission (Top Right) shown as a series of sparse points across the landscape. Scatterplot with associated validation metrics comparing the observed GEDI measured carbon to Planet’s predicted carbon estimates at 1 sq km resolution (Bottom).


SDGs, Targets, and Indicators

  1. SDG 13: Climate Action

    • Target 13.2: Integrate climate change measures into national policies, strategies, and planning.
    • Target 13.3: Improve education, awareness-raising, and human and institutional capacity on climate change mitigation, adaptation, impact reduction, and early warning.
    • Indicator: The article discusses the use of deep learning models and scientific methods to estimate forest height and cover, which can contribute to understanding and monitoring climate change impacts on forests.

  2. SDG 15: Life on Land

    • Target 15.2: Promote the implementation of sustainable management of all types of forests.
    • Target 15.3: Combat desertification, restore degraded land, and strive to achieve a land degradation-neutral world.
    • Indicator: The article mentions the estimation of aboveground live carbon in forests, which can be used as an indicator of forest health and ecosystem resilience.

Table: SDGs, Targets, and Indicators

SDGs Targets Indicators
SDG 13: Climate Action Target 13.2: Integrate climate change measures into national policies, strategies, and planning. The use of deep learning models and scientific methods to estimate forest height and cover can contribute to understanding and monitoring climate change impacts on forests.
SDG 13: Climate Action Target 13.3: Improve education, awareness-raising, and human and institutional capacity on climate change mitigation, adaptation, impact reduction, and early warning. The article highlights the utilization of advanced techniques to minimize year-over-year measurement variability, which can enhance climate change mitigation and adaptation efforts.
SDG 15: Life on Land Target 15.2: Promote the implementation of sustainable management of all types of forests. The estimation of aboveground live carbon in forests can serve as an indicator of sustainable forest management practices.
SDG 15: Life on Land Target 15.3: Combat desertification, restore degraded land, and strive to achieve a land degradation-neutral world. The assessment of forest carbon data can contribute to efforts in restoring degraded land and achieving land degradation neutrality.

Behold! This splendid article springs forth from the wellspring of knowledge, shaped by a wondrous proprietary AI technology that delved into a vast ocean of data, illuminating the path towards the Sustainable Development Goals. Remember that all rights are reserved by SDG Investors LLC, empowering us to champion progress together.

Source: planet.com

 

Join us, as fellow seekers of change, on a transformative journey at https://sdgtalks.ai/welcome, where you can become a member and actively contribute to shaping a brighter future.