Optische Flugzeugfernerkundung für Europa - Das fliegende Auge

Trotz Konkurrenz durch Satelliten: Erdbeobachtung aus der Luft ist für die Forschung unverzichtbar. Mit seinen Instituten in Oberpfaffenhofen und seinen Flugzeugen übernimmt das DLR dabei in Europa eine führende Rolle

Monitoring of river contamination derived from acid mine drainage using airborne imaging spectroscopy (HyMap data, South-West Spain)

Imaging spectroscopy is used in this work as an essential mapping tool to monitor changes in contaminated river sediments. Multidate hyperspectral image data (HyMap) are utilized to identify spatial mineral patterns, to detect temporal changes in mineralogy and to link these changes with geochemical processes and short-term climate characteristics. River sediments contaminated by acid mine drainage are covered by crusts with variably hydrated iron sulphate. The mineralogy of the crusts and the grain size of the underlying fluvial sediments overlap. The spectra used to build up maps from HyMap data are diagnosed mineralogically with archive spectral libraries from pyrite oxidation minerals from well-known sequences of minerals. The maps compiled from hyperspectral imagery display generalized oxidation shown by the coatings over river sediments following warm and dry periods with low water level. After the wet periods, the area covered by oxidized mineralogical phases recedes in favour of hydrated sulphate. The iteration of image processing algorithms and the mineralogical and potential contamination in a geological context are described. Change detection of the mineral crusts on the river sediments by mapping using hyperspectral remote sensing data may thus enable a quantitative and qualitative environmental evaluation by the regulators

A European Time Series of Daily Snow Cover from AVHRR Data over 36 Years: Results of the TIMELINE Project

The TIMELINE project is dedicated to generating comprehensive and consistent long-term time series using NOAA and METOP AVHRR data for Europe and North Africa, utilizing the extensive DLR-DFD historical data archive. Its primary objective is to address socially significant inquiries regarding climate change and identify potential trends. To achieve this, the project has developed a multitude of processors that produce essential data products pertaining to radiation, land surface, atmosphere, and cryosphere. Specifically focusing on the cryosphere, the daily estimation of the snow-covered area from AVHRR data between 1982 and 2018 in TIMELINE provides an unprecedented 36-year period of observation, almost doubling the duration of available MODIS snow product records in the region. This paper presents the snow cover processor, along with the initial outcomes of the time series analysis, shedding light on important insights gained from the data

Longterm Dynamics of Sea Surface Temperature (SST) in Europe between 1982 and 2018 - Exploring the new TIMELINE AVHRR SST Product

In the TIMELINE project, consistent SST product were developed from AVHRR brightness temperatures over Europe and North Africa for the period 1982-2018. The daily, 10-daily and monthly Level 3 products contain statistics of SST (minimum, maximum, median, mean) for the respective period. Only high quality SST is used, which is ensured by filtering and quality and uncertainty variables. In this study we present results of the first analysis of long-term dynamics of SST at 1 km resolution over Europe and North Africa based on the Level 3 TIMELINE products

Long-term dynamics of Land Surface Temperature (LST) over Europe

LST is recognized as one of the Essential Climate Variables by the World Meteorological Organization. It is a key parameter for climate models and a direct indicator of global warming. The Advanced Very High-Resolution Radiometer (AVHRR) is the only sensor that has been providing spatially and temporally continuous daily measurements for 40 years. In the TIMELINE project, consistent LST products were developed from AVHRR over Europe [1,2]. However, the different overpass times and the orbital drift effect hide actual trends and anomalies in LST. In this study TIMELINE LST from NOAA 9, 11, 14, 16, 17, 18 and 19 for the years 1984-2017 over four regions in Western and Central Europe was analyzed. A physical daily temperature cycle (DTC) model was applied to normalize the LST to a consistent observation time and then monthly anomalies and a linear trend was calculated