The project MoDEV (Model-Data fusion for understanding Environmental Variability) investigates the interplay between carbon and water cycles for three biomes: forest, grassland and agriculture with special focus on the impacts of extreme hydrologic and climatic events as well their long-term trends.
Establishing a national forest monitor to assess and visualise vegetation condition for a better risk-management of German forests.
We present a novel approach for detailed crop type and tree species classification exploiting high spatio-temporal resolution Sentinel-2A data. Here, we address the challenge of frequent cloud coverage in satellite observations by defining, purely …
Landscapes are meaningful ecological units that strongly depend on the environmental conditions. Such dependencies between landscapes and the environment have been noted since the beginning of Earth sciences and cast into conceptual models describing …
Imaging and non-imaging spectroscopy employed in the field and from aircraft is frequently used to assess biochemical, structural, and functional plant traits, as well as their dynamics in an environmental matrix. With the increasing availability of …
Considering the trajectories of pulses from terrestrial laser scanners (TLS) can provide refined models of occlusion and improve the assessment of observation quality in forests and other ecosystems. By considering the space traversed by light …
Extreme drought or wet conditions have now been found to strongly influence the vegetative development of ecosystems. Semi-arid regions are most affected - raising concerns about their vulnerability to long-term drought in the future. © 2015 …
The main objective of the current paper is to evaluate and explain differences between computed green-up dates of vegetated land surface derived from satellite observations and budburst dates from ground observational networks. Landscapes dominated …