Section 1.4: Remote Sensing and Geoinformatics

The research aims of the Remote Sensing and Geoinformatics Section at GFZ are to establish remote sensing as a core method in geosciences. In particular, we aim to increase awareness of the considerable value of remotely sensed data for knowledge generation about Earth’s surface properties and processes, which arises from its ability to provide complete coverage over large spatial scales. Our research and method development covers the entire range of the remote sensing processing chain. We examine bio, geophysical, and geochemical processes in soil, geology, vegetation, and the atmosphere which are triggered by landscape and vegetation development, climate change, natural disasters, and human land use.

Our work on monitoring bio and geophysical surface parameters includes developing sensors for mapping change from satellite, aircraft, and drone imagery. We also develop methods for simulation, calibration, and fusion of data from multiple (optical and radar) sensors via spectral modeling. We investigate the connection between bio and geophysical processes and spectral imagery by combining spectral measurements in the laboratory, in the field, and from air and spaceborne systems with the physical and chemical properties of real surfaces, which we sample using field surveys. Our image analysis methods and software extract information about changes from time series data, enabling users to identify the underlying bio and geophysical processes. This work in particular involves the use and adaptation of big data analytics and data science approaches.

What makes our section exceptional is our multifaceted expertise in remote sensing. This allows us to first observe changes in imagery, and then to understand the underlying process responsible and to observe this process continuously through long-term monitoring.

An unprecedented amount of imagery and remotely sensed data is available today, and this information could benefit many people who are not experts in remote sensing. We therefore founded the “FERN.Lab”, to ensure that our scientific work is translated into practical applications that benefit society.

We hold the role of science principal investigator for the German hyperspectral satellite mission EnMAP. Our diverse expertise covering the entire remote sensing chain (from sensor to application) is pooled together in the development of this mission.

Neuigkeiten

On July 18th, together with all partners, we are finally kicking off our Open-Earth-Monitor project! This project embraces the use of open-source environmental data (remotely sensed and in-situ) and the development of methods and tools to enhance monitoring and assessments in critical regions on Earth. An open-source cyber-infrastructure will be built to significantly accelerate the uptake of environmental information, and to help build user communities at European and global levels. Thus, this project directly supports the open science goals of the GFZ.

To mark the project launch, a first public workshop with interactive debates, feedback rounds and demo sessions will take place on 19th July. Prominent representatives from the fields of Earth observation, data policy, business and science will be present. Please register here to attend the digital workshop for free: https://bit.ly/3ArlA9y

The Open-Earth-Monitor project is coordinated by the OpenGeoHub Foundation, an independent non-profit research foundation promoting Open Source and Open Data solutions.

Context

In recent decades, the world has experienced rapid growth in Earth Observation technology, which is considered by many to be one of the key tools to tackle environmental and climatic crises across borders. But this has come at a cost: Massive and inconsistent data volumes produced by EO sensors and ground monitoring networks are now overwhelming research networks; environmental information is often heavily under-used because it requires a high level of expertise and computing capacity. Therefore the targeted use of environmental data and other digital solutions is still rare among landholders, farmers, ecosystem regeneration practitioners, institutions and policy-makers, amongst other.

Expected impacts:

The Open-Earth-Monitor consortium consists of 23 partner organizations within and outside of Europe. The main goals of the consortium are to:

  • Produce an inventory of user needs, data and knowledge that will be used to develop a framework for increasing uptake and accessibility of environmental observation information;
  • Achieve permanent improvement in access to existing European and global environmental observation data for European stakeholders and make information more pertinent by reducing data complexity and increasing accessibility;
  • Develop a suite of intuitive tools to enable targeted end-users to monitor the status of natural resources at European and global scales, and production of environmental Business-2-Business solutions;
  • Built a comprehensive and systematic platform to enhance the FAIRness (Findability, Accessibility, Interoperability and Reusability) of environmental data by implementing the values of the European AI act and European GDPR Act;

Run an operational solution for processing and serving Earth Observation data, in-situ environmental data, Artificial Intelligence, Machine Learning and HPC models (OEMC-computing-engine).

Role of the GFZ

GFZ has a number of key roles in the Open-Earth-Monitor project:

  • The GFZ is co-leading the work on user-driven system design and FAIR data workflows and has an important role in the assessment of stakeholder engagement and user needs.
  • Another major task is to develop biomass estimation tools and to compile and process existing biomass data at European and global levels. Contained therein are the assessment and processing of available biomass datasets (space-based, in-situ) and the implementation of an open source tool to combine forest biomass estimates from different EO and ground-based data sources.
  • Furthermore, the GFZ will be leading the combination of different data sources for the development of a global forest GHG emissions monitor that can also be linked to different commodities and land use systemsrelated to oil palm, tropical timber, soy, beef and cacao.

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