Prior to the launch of the EnMAP mission and on behalf of the Federal Ministry of Economic Affairs and Energy, DLR Space Administration has set up a research funding program to prepare data exploitation and applications development for the mission. It recognizes that EnMAP will deliver a new and heretofore unreached quality of spaceborne imaging spectroscopy data. The program includes:
- algorithm development for essential ecosystem parameters
- application development for a wide range of applications
- summer schools for young scientists and,
- airborne campaigns to acquire test data for EnMAP image simulations.
Since 2010 several calls for proposals within the EnMAP scientific program have been announced by DLR Space Administration. An overview of projects included in the program framework is given below:
EnMAP Core Science Team (ECST; 2010-2019)Preparations for the scientific use of the EnMAP data in the pre-launch phase of the EnMAP mission | ||
| Topic | Institute | Title |
|---|---|---|
| Forests and Natural Ecosystems | Uni Trier | Analysis of forest ecosystem processes and mapping of biotic stress |
| Mission support / Geology and Soils | GFZ | Scientific preparation of the EnMAP imaging spectroscopy mission |
| Agriculture | LMU | Developing the EnMAP managed vegetation scientific processor |
| Coastal and inland waters | HZG | Developing remote sensing algorithms for determining ingredients of water in coastal and inland waters for the EnMAP mission |
| Coastal and inland waters | AWI | Developing atmospheric correction for hyperspectral ocean colour remote sensing in application to the EnMAP mission |
| Natural Ecosystems and Ecosystem Transitions | HU Berlin | Monitoring Vegetation under Global Change |
| Vegetation Function | MPI | Modelling Responses of Dehesas with Hyperspectral Remote Sensing |
Second EnMAP PhD Program (2014 - 2017)Topic: Development of new methods and applications for the EnMAP mission considering synergies with ESA’s Sentinel fleet and national missions (TerraSAR-X, Tandem-X and RapidEye) | ||
| Project | Institute | Title |
| EnFusionMap | RU Bochum, FU Berlin, DLR | Development of methods for mapping urban surfaces based on EnMAP and multisensoral data |
| EnviMetal | Martin-Luther-University Halle-Wittenberg | EnviMetal – vegetation stress as bio-indicator of soil contamination in floodplains |
| DryLand | University of Trier, University of Osnabrueck, Julius Kühn Institute | Use of hyperspectral remote sensing to monitor agricultural areas with a particular focus on drought stress |
| KESLaWa | FU Berlin | Atmospheric correction and retrieval of geophysical parameters from EnMAP and Sentinel-3 data collected over water |
| habitat and vegetation monitoring | Karlsruhe Institute of Technology (KIT) | Combination of empirically and physically based modeling approaches for habitat- and vegetationmonitoring |
| KelpMap 2.0 | University Kiel, DLR | Atmospheric correction of EnMAP and Sentinel-2 coastal area data, and monitoring submersed marine macrophytes |
| Hy-ARK-VEG II | AWI | Hy-ARC-VEG Arctic Vegetation Phenology and Structure |
First EnMAP PhD Program (2011 - 2013)Topic: Development of advanced methods and algorithms for EnMAP data analysis with the focus of spatial scales | ||
| Project | Institute | Title |
| Hyland | JKI and University of Heidelberg | Use of Hyperspectral Remote Sensing for the Retrieval of Agricultural Soil and Crop Parameters for Precision Agriculture and Yield Estimation (HyLand) |
| KlimaErosion | University of Potsdam | Nonlinear Analysis of hyperspectral remote sensing data to quantify climate driven erosion processes |
| KelpMAP | University Kiel | Development of an EnMAP-Routine to Map and Monitor Submersed Marine Macrophytes - KelpMAP |
| BMP | University of Bonn | Developing remote sensing methods to retrieve the biomethanpotential of agricutural areas with special focus of the upcoming EnMAP mission |
| hy-ARC-VEG | AWI | Hyperspectral method development for ARCtic VEGetation biomes |
| ForestHype | University of Freiburg | Assessment of forest damages and estimation of aboveground biomass |
| ForestHype | TU Berlin | ForestHype – Project Part "Biodiversity" |
| ForestHype | Georg-August-University Göttingen | Hyperspektrale Satellitendaten für fortsbetriebliche Bestandsinventuren |
| Oekosystem | UFZ | Methods for deriving functional relationships of ecosystem processes based on hyperspectral data of different spatial resolutions |
| Futterwert | University of Bonn | Assessment of grassland forage quality using hyperspectral remote sensing |
| BMP | University Trier | Developing remote sensing methods to retrieve the biomethanepotential of agricultural areas with special focus of the upcoming EnMAP mission |