Mapping of Floristic and Faunistic Habitat Characteristics, Spatiotemporal Interactions and Biodiversity Factors
The project NaTec – KRH aims to develop remote sensing based methods and algorithms for he monitoring of species and habitats in nature conservation areas. In different ecological scales (from satellite sensors to field spectroscopy) it will be examined how habitat management practice influences spatial patterns of biodiversity indicators.
The collaborative project aims at the utilization of global satellite and model data for regional water resources management and seasonal forecasts. Main target areas are dryland regions in Brazil, Iran and Sudan. The project is funded by the Federal Ministry of Education and Research (BMBF) in the frame of the research initiative Global Resource Water (GROW).
We provide game-changing, remote exploration which allows you to determine the resource potential in a focussed, precise and timely manner. By using available data from satellite systems utilizing automated patent registered processing routines, we provide high-performance, large spatial surface analysis for risk-reduced remote prospection.
The project EORAP (Earth Observation for the retrieval of agronomical parameters) focusses since 2014 on the analysis of plant pattern / heterogeneities in agricultural crops. This can be based on temporary ( nutrients , disease , bad weather , among others ) and permanent ( soil type , relief , failure management ) causes and effects directly the local yield potential. The recognition and classification of plants occurring patterns can help to optimize fertilizers and farm management strategies of each crop adapted to the structures and thus contribute to sustainable and resource efficient management.
In the frame of the REEMAP project a modular multi-sensor processing chain for modern imaging spectrometers shall be created that enables direct (using absorption features) or indirect (using mineral assemblages) spatially extensive, rapid and robust detection and semiquantification of Rare Earth Elements also by technical staff in order to fulfill the actual demand for cost-efficient, fast and reliable exploration and ressource potential assessment.
In the GTS² project, Sentinel-2 surface reflectance data is processed and provided to users via a simple to use web application programming interface (API). The GTS² project is developed in collaboration with AgriCircle, an agriculture start-up based in Switzerland.
Our aim is to serve a variety of users and applications such as agricultural monitoring services or surveillance of hazards such as floods or landslides.
The Environmental Mapping and Analysis Program (EnMAP) is a German hyperspectral mission, still in the planning phase. The primary goal of EnMAP is to offer accurate, diagnostic information on the state and evolution of terrestrial ecosystems on a timely and frequent basis, and to allow for a detailed analysis of surface parameters with regard to the characterization of vegetation canopies, rock/soil targets and coastal waters on a global scale. EnMAP is designed to record bio-physical, bio-chemical and geo-chemical variables to increase our understanding of biospheric /geospheric processes and to ensure the sustainability of our resources.
EUFAR works to coordinate the operation of instrumented aircraft and hyperspectral imaging sensors, exploiting the skills of experts in airborne measurements in the fields of environmental and geo-sciences, in order to provide researchers with the infrastructure best suited to their needs. EUFAR in FP7 joined with the HYRESSA (EU-FP6) hyperspectral community.
The BMBF co-operative project GeoArchives is part of the FONA - "Forschung für Nachhaltige Entwicklung" program and within the international research program SPACES - "Science Partnerships for the Assessment of Complex Earth System Processes". In this study we intend to examine the connections between earth-surface processes on slopes such as sheet wash, colluvial sediment transport, and eolian movements and their links to the fluvial system via three major geomorphic forms as terrestrial geoarchives: slopes, fans, and terraces.
Desertification surveillance is required for making one-off and periodic assessments of desertification status, for forecasting possible trajectories (early warning), and for evaluating the performance of management programmes. However, assessment procedures have so far been largely empirical and focused on the symptoms of desertification (land degradation) rather than on the underlying human-environment interactions and processes.
Continued growth of the world’s population, the resulting intensified exploitation of our planet and its resources, and the increasing susceptibility of society to natural disasters all call for sustained and internationally agreed activity to preserve our living environment. Earth is a dynamic planet subject to constant change caused by a variety of endogenous and exogenous forces and processes and characterized by interactions and exchanges among the geosphere, hydrosphere, cryosphere, atmosphere and biosphere. In order to comprehend this space in which we live, we have to consider Earth as a system and analyze its functioning globally as well as regionally. It is also necessary to evaluate the effects of human activity and interference with the natural equilibria and processes of this highly complex system.
Significant advances in Earth system understanding will only be achieved through better integration of data and knowledge from the different Earth science disciplines and earth compartments.Improvement in this field strongly depends on our capabilities of dealing with fast growing multi-parameter data and on our effort employing Data Science methods, adapting new algorithms and developing digital workflows tailored to specific scientific needs.With Digital Earth we will address these challenges within and between the Helmholtz partners.
Funded by: Initiative and Networking Fund by Helmholtz Association
Funding period: 01.06.2018 - 31.05.2021
The objective of ENAP project is the utilization of information that is provided by volunteers in social media (volunteered geographic information – VGI) for geoscientific questions. We develop novel methods in the two computer science fields of computer vision and visual analytics to find relevant VGI quickly and to assess their value in relation to other information.
Funded by: German Research Foundation
Funding period: 01.08.2016 - 31.10.2019