Multimodal Vision Research Laboratory

MVRL

Research Area: Forestry and Forest Disturbance

How can we monitor forest structure, mortality, and disturbance at scale from satellite time series? We build methods for tree mortality mapping, deforestation detection, and forest typing from Sentinel-2, LiDAR, and related earth observation. Recent work includes sub-pixel mapping of disturbance and tree mortality from global Sentinel-2 time series (deadtrees.earth), conifer/deciduous classification from airborne LiDAR, and spatio-temporal deep learning for rainforest deforestation mapping. Forestry applications extend our ecology and remote sensing portfolio toward operational forest health and carbon-relevant monitoring.

All Publications

  1. Mosig C, Kattenborn T, Vanja-Jehle J, Montero D, Brandt J, Bozzini A, Cheng Y, Esquivel Muelbert A, Ganz K, Gora E, Grüning BA, Jacobs N, Hartmann H, Hempel J, Horion S, Junttila S, Khanal S, Korznikov K, Kraemer G, McGregor I, Mönks M, Muller-Landau H, Nardi D, Neumeier P, Schmid J, Schwartz M, Beloui Schwenke M, Soltani S, Therese-Schmehl M, Veitch-Michaelis J, Xing E, Mahecha MD. 2026. deadtrees.earth Maps: Tree Mortality and Disturbance Mapping from Sentinel-2 Timeseries Across The Globe. In: EGU General Assembly 2026. Vienna, Austria: Copernicus Meetings, DOI: 10.5194/egusphere-egu26-18072.
  2. Mosig C, Kattenborn T, Montero Loaiza D, Vanja-Jehle J, Brandt J, Jacobs N, Khanal S, Xing E, Schwartz M, Muller-Landau HC, Beloiu M, Bozzini A, Cheng Y, Ganz K, Grüning B, Hartmann H, Hempel J, Horion S, Junttila S, Korznikov K, Kraemer G, Mönks M, Nardi D, Neumeier P, Schmid J, Soltani S, Therese-Schmehl M, Veitch-Michaelis J, Mahecha M. 2026. Sub-pixel mapping of disturbance and tree mortality dynamics from Sentinel-2 time series around the globe. Eartharxiv. DOI: 10.31223/X5B18W.
  3. Thumbnail for Spatio-Temporal Deep Learning Approach to Map Deforestation in Amazon Rainforest
    Maretto RV, Fonseca LMG, Jacobs NB, Körting TS, Bendini HN, Parente LL. 2020. Spatio-Temporal Deep Learning Approach to Map Deforestation in Amazon Rainforest. IEEE Geoscience and Remote Sensing Letters 18:771–775. DOI: 10.1109/LGRS.2020.2986407.
  4. Thumbnail for Deep Learning for Conifer/Deciduous Classification of
                Airborne LiDAR 3D Point Clouds Representing Individual Trees
    Hamraz H, Jacobs NB, Contreras MA, Clark CH. 2019. Deep Learning for Conifer/Deciduous Classification of Airborne LiDAR 3D Point Clouds Representing Individual Trees. ISPRS Journal of Photogrammetry and Remote Sensing 158:219–230. DOI: 10.1016/j.isprsjprs.2019.10.011.