Remote Sensing and Ecological Modelling
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 (biomass, leaf area, productivity) 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 global vegetation 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.
We work with different types of remote sensing data (such as opitcal data, LiDAR and Radar) in different projects:
- The large Helmholtz Alliance “Remote Sensing and Earth System Dynamics” (19 research institutes) aims at the development and evaluation of novel products derived from data acquired by a new generation of remote sensing satellites; and their integration in Earth system models for improving understanding and modelling ability of global environmental processes and ecosystem change. Especially we aim to integrate and use forest structure parameters derived from radar remote sensing techniques in monitoring the state and the properties of global forests with a particular focus on biological properties.
- 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.
We also use satellite images to analyze how tropical rainforests in the Amazon region and coastal tropical forests are spatially distributed – affected by forest fragmentation. Because of deforestation of tropical rainforests in Brazil, 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. In a nutshell, ecological modelling can play an important role for remote sensing in various ways.
- 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