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.
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.
GeoMultiSens exploits current scientific and technological advances in Big Data infrastructures, parallel computing environments, Visual Analytics and links them with the potential of satellite remote sensing data to address global challenges such as deforestation, loss of biodiversity, and mega cities.
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.
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.
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.
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.