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Showing 1–5 of 5 results
Advanced filters: Author: Fabian Gieseke Clear advanced filters

  • The authors conduct a national inventory on individual tree carbon stocks in Rwanda using aerial imagery and deep learning. Most mapped trees are located in farmlands; new methods allow partitioning to any landscape categories, effective planning and optimization of carbon sequestration and the economic benefits of trees.

    • Maurice Mugabowindekwe
    • Martin Brandt
    • Rasmus Fensholt
    ResearchOpen Access
    Nature Climate Change
    Volume: 13, P: 91-97

  • The authors develop a machine learning-based approach to derive abrupt shift probability in dryland ecosystem functioning in the Sudano–Sahel. They highlight areas with high probabilities of abrupt shifts in the near future (2025), which are linked to long-term rainfall trends.

    • Paulo N. Bernardino
    • Wanda De Keersmaecker
    • Ben Somers
    Research
    Nature Climate Change
    Volume: 15, P: 86-91

  • Deep learning was used to map the crown sizes of each tree in the West African Sahara, Sahel and sub-humid zone using submetre-resolution satellite imagery, revealing a relatively high density of trees in arid areas.

    • Martin Brandt
    • Compton J. Tucker
    • Rasmus Fensholt
    Research
    Nature
    Volume: 587, P: 78-82

  • Trees are crucial for Earth’s ecosystems, aiding in carbon absorption, climate regulation and biodiversity support. High-resolution satellite sensors and artificial intelligence enable detailed tree monitoring at national and continental levels, simplifying biomass assessment, national reporting and climate change mitigation efforts.

    • Martin Brandt
    • Jerome Chave
    • Christian Igel
    Reviews
    Nature Reviews Electrical Engineering
    Volume: 2, P: 13-26