By multi-temporal analysis of multispectral RapidEye data sets visible spectrally defined spatial units are distinguished within an agricultural field in stable soil pattern (due to differences in soil properties influenced) and temporary pattern (created by management, vegetation and weather). Identified patterns are analyzed with respect to their soil characteristics and assessed their spatial and temporal stability. The aim is to develop functional maps based on spatially and temporally stable soil patterns for a more economical and more sustainable land management. In order to cover the entire geomorphological, pedological and topographical range of the project area, on several reference areas in total 731 in-situ surface soil samples are taken and were analyzed in the laboratory with regard to their physiochemical soil properties.
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.
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
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.
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 contribution of the Remote Sensing and Geoinformatics section of the GFZ within GeoArchives project is to study the states and responses and spatial scales of fluvial, lacustrine and aeolian sediment archives for landscape dynamic and evolution in the South African region based on hyperspectral and multispectral remote sensing data.
The goal of the Big Data system GeoMultiSens is to enable scientists to study changes of the Earth’s surface on high-resolution scenes. Therefore we develop an integrated processing pipeline supporting the analysis of petabyte data.
Funded by: Federal Ministry of Education and Research
Funding period: 01.09.2014 - 31.12.2017
Das GlobFluo Projekt (globale Bewertung der vegetationsbedingten Photosynthese durch die Fernerkundung von Chlorophyllfluoreszenz aus dem Weltraum) wird durch das Emmy Noether Programm der Deutschen Forschungsgemeinschaft gefördert. Das Ziel des Projekts ist es eine Nachwuchsforschergruppe aufzustellen, die den wissenschaftlichen Schwerpunkt auf die Fernerkundung der Chlorophyllfluoreszenz (von solarer Strahlung induziert und von der Vegetation emittiert) aus dem Weltraum legt. Unsere Arbeit beinhaltet dabei den technischen Aspekt, d.h. die Ableitung der Chlorophyllfluoreszenz aus satellitengestützten Messungen, sowie die Auswertung und Interpretation der gewonnenen Daten in Bezug auf photosynthetische Prozesse auf der globalen Skala.
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 HGF Alliance “Remote Sensing and Earth System Dynamics” aims at the development and evaluation of novel bio/geo-physical information 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. The Earth system comprises a multitude of processes that are intimately meshed through complex interactions. In work package (WP) H7:”the use of hyperspectral optical and L-band radar data for retrieving surface soil moisture at the field scale” is investigated.
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.
HYRESSA is a 2-year project investigating the user needs of the European hyperspectral remote sensing research community with respect to access to and accuracy, quality and conformity of hyperspectral images, especially with the advent of next-generation European hyperspectral sensors like ARES and APEX in 2007-2008.
LUCA - Land Use, Ecosystem Services and Human Welfare in Central Asia - is a postgraduate program for young scientists from Central Asia. Starting from 2010 it is building a platform for joint analysis of land use conditions in Central Asia in relation to causing factors involving participants from different countries of Central Asia and scientific partners in Germany.
Soil moisture is one of the most important parameters for the monitoring of landscape water processes. Remote Sensing enables the detailed and laminar gathering of soil moisture in the upper soil layers. To estimate influence of varying soil moisture on the different remote sensing data the signals are modeled using complex 3D virtual canopies.
MOMS, acronym for Modular Optoelectronic Multispectral/Stereo Scanner, is an Earth sensing CCD-instrument using the "pushbroom" scan principle. The newly designed sensor provides multispectral coverage in 4 wavebands including the visible and near-infrared range. It is also equipped with a three line along-track stereo device, recording for/aft and high resolution nadir panchromatic data.
The detection of soil moisture from ENVISAT-ASAR data
The project OPAQUE is aimed at the task to improve the operational flood forecast for small head catchment areas. While for large river basins the forecast of floods on the basis of models works well, a warning is often insufficient in the head catchments because of the direct reaction of the landscape to the higher quantities of water.
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.
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 3-year joint research project aims at observing and modelling water and suspended sediment transport processes and connectivity phenomena in two meso-scale dryland catchments in NE Spain and NE Brazil in order to enhance process understanding at spatial scales relevant for water and land management.