Filtern
Dokumenttyp
- Wissenschaftlicher Artikel (10)
- Dissertation (5)
Schlagworte
- Satellitenfernerkundung (15) (entfernen)
Institut
Die endemischen Arganbestände in Südmarokko sind die Quelle des wertvollen Arganöls, sind aber durch bspw. Überweidung oder illegale Feuerholzgewinnung stark übernutzt. Aufforstungsmaßnahmen sind vorhanden, sind aber aufgrund von zu kurz angelegten Bewässerungs- und Schutzverträgen häufig nicht erfolgreich. Das Aufkommen von Neuwuchs ist durch das beinahe restlose Sammeln von Kernen kaum möglich, durch Fällen oder Absterben von Bäumen verringert sich die kronenüberdeckte Fläche und unbedeckte Flächen zwischen den Bäumen nehmen zu.
Die Entwicklung der Arganbestände wurde über den Zeitraum von 1972 und 2018 mit historischen und aktuellen Satellitenbildern untersucht, ein Großteil der Bäume hat sich in dieser Zeit kaum verändert. Zustandsaufnahmen von 2018 zeigten, dass viele dieser Bäume durch Überweidung und Abholzung nur als Sträucher wachsen und so in degradiertem Zustand stabil sind.
Trotz der Degradierung einiger Bäume zeigt sich, dass der Boden unter den Bäumen die höchsten Gehalte an organischer Bodensubstanz und Nährstoffen auf den Flächen aufweist, zwischen zwei Bäumen sind die Gehalte am niedrigsten. Der Einfluss des Baumes auf den Boden geht über die Krone hinaus in Richtung Norden durch Beschattung in der Mittagssonne, Osten durch Windverwehung von Streu und Bodenpartikeln und hangabwärts durch Verspülung von Material.
Über experimentelle Methoden unter und zwischen den Arganbäumen wurden Erkenntnisse zur Bodenerosion gewonnen. Die hydraulische Leitfähigkeit unter Bäumen ist um den Faktor 1,2-1,5 höher als zwischen den Bäumen, Oberflächenabflüsse und Bodenabträge sind unter den Bäumen etwas niedriger, bei degradierten Bäumen ähnlich den Bereichen zwischen den Bäumen. Die unterschiedlichen Flächenbeschaffenheiten wurden mit einem Windkanal untersucht und zeigten, dass gerade frisch gepflügte Flächen hohe Windemissionen verursachen, während Flächen mit hoher Steinbedeckung kaum von Winderosion betroffen sind.
Die Oberflächenabflüsse von den unterschiedlichen Flächentypen werden in die Vorfluter abgeleitet. Die Sedimentdynamik in diesen Wadis wird hauptsächlich von Niederschlag zwischen den Messungen, Einzugsgebiet und Wadilänge und kaum von den verschiedenen Landnutzungen beeinflusst.
Das Landschaftssystem Argan konnte über diesen Multi-Methodenansatz auf verschiedenen Ebenen analysiert werden.
This paper describes the concept of the hyperspectral Earth-observing thermal infrared (TIR) satellite mission HiTeSEM (High-resolution Temperature and Spectral Emissivity Mapping). The scientific goal is to measure specific key variables from the biosphere, hydrosphere, pedosphere, and geosphere related to two global problems of significant societal relevance: food security and human health. The key variables comprise land and sea surface radiation temperature and emissivity, surface moisture, thermal inertia, evapotranspiration, soil minerals and grain size components, soil organic carbon, plant physiological variables, and heat fluxes. The retrieval of this information requires a TIR imaging system with adequate spatial and spectral resolutions and with day-night following observation capability. Another challenge is the monitoring of temporally high dynamic features like energy fluxes, which require adequate revisit time. The suggested solution is a sensor pointing concept to allow high revisit times for selected target regions (1"5 days at off-nadir). At the same time, global observations in the nadir direction are guaranteed with a lower temporal repeat cycle (>1 month). To account for the demand of a high spatial resolution for complex targets, it is suggested to combine in one optic (1) a hyperspectral TIR system with ~75 bands at 7.2"12.5 -µm (instrument NEDT 0.05 K"0.1 K) and a ground sampling distance (GSD) of 60 m, and (2) a panchromatic high-resolution TIR-imager with two channels (8.0"10.25 -µm and 10.25"12.5 -µm) and a GSD of 20 m. The identified science case requires a good correlation of the instrument orbit with Sentinel-2 (maximum delay of 1"3 days) to combine data from the visible and near infrared (VNIR), the shortwave infrared (SWIR) and TIR spectral regions and to refine parameter retrieval.
A satellite-based climatology of wind-induced surface temperature anomalies for the Antarctic
(2019)
It is well-known that katabatic winds can be detected as warm signatures in the surface temperature over the slopes of the Antarctic ice sheets. For appropriate synoptic forcing and/or topographic channeling, katabatic surges occur, which result in warm signatures also over adjacent ice shelves. Moderate Resolution Imaging Spectroradiometer (MODIS) ice surface temperature (IST) data are used to detect warm signatures over the Antarctic for the winter periods 2002–2017. In addition, high-resolution (5 km) regional climate model data is used for the years of 2002 to 2016. We present a case study and a climatology of wind-induced IST anomalies for the Ross Ice Shelf and the eastern Weddell Sea. The IST anomaly distributions show maxima around 10–15K for the slopes, but values of more than 25K are also found. Katabatic surges represent a strong climatological signal with a mean warm anomaly of more than 5K on more than 120 days per winter for the Byrd Glacier and the Nimrod Glacier on the Ross Ice Shelf. The mean anomaly for the Brunt Ice Shelf is weaker, and exceeds 5K on about 70 days per winter. Model simulations of the IST are compared to the MODIS IST, and show a very good agreement. The model data show that the near-surface stability is a better measure for the response to the wind than the IST itself.
The presence of sea ice leads in the sea ice cover represents a key feature in polar regions by controlling the heat exchange between the relatively warm ocean and cold atmosphere due to increased fluxes of turbulent sensible and latent heat. Sea ice leads contribute to the sea ice production and are sources for the formation of dense water which affects the ocean circulation. Atmospheric and ocean models strongly rely on observational data to describe the respective state of the sea ice since numerical models are not able to produce sea ice leads explicitly. For the Arctic, some lead datasets are available, but for the Antarctic, no such data yet exist. Our study presents a new algorithm with which leads are automatically identified in satellite thermal infrared images. A variety of lead metrics is used to distinguish between true leads and detection artefacts with the use of fuzzy logic. We evaluate the outputs and provide pixel-wise uncertainties. Our data yield daily sea ice lead maps at a resolution of 1 km2 for the winter months November– April 2002/03–2018/19 (Arctic) and April–September 2003–2019 (Antarctic), respectively. The long-term average of the lead frequency distributions show distinct features related to bathymetric structures in both hemispheres.
A model-based temperature adjustment scheme for wintertime sea-ice production retrievals from MODIS
(2022)
Knowledge of the wintertime sea-ice production in Arctic polynyas is an important requirement for estimations of the dense water formation, which drives vertical mixing in the upper ocean. Satellite-based techniques incorporating relatively high resolution thermal-infrared data from MODIS in combination with atmospheric reanalysis data have proven to be a strong tool to monitor large and regularly forming polynyas and to resolve narrow thin-ice areas (i.e., leads) along the shelf-breaks and across the entire Arctic Ocean. However, the selection of the atmospheric data sets has a large influence on derived polynya characteristics due to their impact on the calculation of the heat loss to the atmosphere, which is determined by the local thin-ice thickness. In order to overcome this methodical ambiguity, we present a MODIS-assisted temperature adjustment (MATA) algorithm that yields corrections of the 2 m air temperature and hence decreases differences between the atmospheric input data sets. The adjustment algorithm is based on atmospheric model simulations. We focus on the Laptev Sea region for detailed case studies on the developed algorithm and present time series of polynya characteristics in the winter season 2019/2020. It shows that the application of the empirically derived correction decreases the difference between different utilized atmospheric products significantly from 49% to 23%. Additional filter strategies are applied that aim at increasing the capability to include leads in the quasi-daily and persistence-filtered thin-ice thickness composites. More generally, the winter of 2019/2020 features high polynya activity in the eastern Arctic and less activity in the Canadian Arctic Archipelago, presumably as a result of the particularly strong polar vortex in early 2020.