Linking Remote Sensing and Ecological Modelling

Canopy photo and LiDAR scene
Photograph of a flight campaign and a LiDAR scene across the Hainich National Park. Photo: Stephan Getzin

The target of this research topic is the development of new methods for the calculation of vegetation attributes by using remote sensing systems. The outcome should contribute to continuous coverage mapping of aboveground carbon stocks and other attributes in vegetation and their dynamics. The most important goal is gaining a better understanding of the following scientific questions:

  • How can we obtain important forest attributes (aboveground biomass, leaf area, productivity, mortality, carbon fluxes) from remote sensing?
  • How can we use forest parameters derived from remote sensing to quantify disturbance type and disturbance intensity in forests?
  • Is it possible to derive relationships which relate forest structure parameters as derived by remote sensing to local tree species richness?
  • How can we couple local dynamic forest models and forest models with satellite data and how can we use satellite data to parameterise forest models?

Forest growth simulations serve as an important tool to explore these questions. With forest models like FORMIND (www.formind.org) large datasets of virtual forest inventories can be generated, which thereafter can be systematically screened for the above mentioned research questions.

LiDAR model
Visualization of the remote sensing simulation model (here LiDAR) developed in the department for ecological modelling. a) Visualization of a simulated forest stand by the forest model FORMIND b) voxel representation of the same forest stand with colors indicating the probability to contain a LiDAR return, depending on the count of tree voxels above each voxel c) simulated LiDAR point cloud with colors indicating height above ground.

We work with different types of remote sensing data (such as opitcal data, LiDAR and Radar) in different projects. Three examples:

  • The large Helmholtz project “3D-ABC - Global carbon budget for vegetation and soils belongs” belongs to the Helmholtz Foundation Model Initiative (start June 2024, four Helmholtz Centres). It aims to derive novel maps for forest biomass, soil carbon and forest productivity using advanced AI techniques by combining different types of remote sensing measurements (e.g. Tandem-X, Sentinel 1 and 2, GEDI, airborne Lidar).Especially the project aims to integrate and use forest structure parameters derived from radar remote sensing techniques (Tandem-X).
    drone
    Scanning grasslands and forests with an unmanned aerial vehicle.
  • Another project investigates the applicability of unmanned aerial vehicles in the field of ecology. The unmanned aerial vehicle of the OESA department is a quadcopter. This drone has four different sensors: a 24-megapixel RGB camera, a multispectral and a thermal camera, as well as a LiDAR that can be used for 3D-laserscanning of vegetation or other objects. With these sensors, the drone can be used for e.g. acquiring high-resolution images of forests, measuring tree heights based on LiDAR or extracting the NDVI index for the forest canopy.
Brazilian Forest Fragments
Forest fragments of the Brazilian Atlantic Forest in the North-East of Brazil, surround by sugar cane plantations. Photo: Mateus de Dantas de Paula

We also use satellite images to analyze forest fragmentation for whole continents (at high spatial resolution, e.g. for the tropics). Because of deforestation in the Amazonl, significantly more carbon has been lost than was previously assumed. To estimate additional carbon emissions at the forest edges, we developed a new approach that integrates results from remote sensing, ecology and forest modelling. The effect of degradation has been underestimated in fragmented forest areas, since it was not possible before to calculate the loss of biomass at forest edges and the higher emission of carbon dioxide.

Selected Publications

  • Köhler, P., Huth, A., (2010):
    Towards ground-truthing of spaceborne estimates of above-ground life biomass and leaf area index in tropical rain forests
    Biogeosciences 7 (8), 2531 - 2543
    Volltext (PDF)
  • Pütz, S., Groeneveld, J., Henle, K., Knogge, C., Martensen, A.C., Metz, M., Metzger, J.P., Ribeiro, M.C., Dantas de Paula, M., Huth, A., (2014):
    Long-term carbon loss in fragmented Neotropical forests
    Nat. Commun. 5 , art. 5037
    Volltext (PDF)
  • Shugart, H.H., Asner, G.P., Fischer, R., Huth, A., Knapp, N., Le Toan, T., Shuman, J.K., (2015):
    Computer and remote-sensing infrastructure to enhance large-scale testing of individual-based forest models
    Front. Ecol. Environ. 13 (9), 503 - 511
    Volltext (PDF)

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