Zusammenhang zwischen Vegetation und Relief in alpinen Einzugsgebieten des Wallis (Schweiz) : Ein multiskaliger GIS- und Fernerkundungsansatz

Die Vegetationsverteilung in der Kulturlandschaft alpiner Hochgebirge ist durch eine starke räumliche Heterogenität natürlicher und anthropogener Standortbedingungen gekennzeichnet. In einem komplexen System direkter und indirekter Einflußfaktoren auf die Vegetationsverteilung stellt das Relief den wichtigsten natürlichen, jedoch indirekten Einflußfaktor dar. Es bedingt ein kleinräumiges Verteilungsmuster von Niederschlag, Einstrahlung und Luft- bzw. Bodentemperatur, Wind und Schnee sowie von geomorphologischen Prozessen (Lawinen, Steinschlag etc.) und erzeugt damit ein patchworkartiges Muster unterschiedlichster Vegetationshabitate. Neben den natürlichen Einflußfaktoren spielt die historische bzw. aktuelle menschliche Nutzung eine große Rolle für die Entwicklung der Vegetation, so daß man in der alpinen Kulturlandschaft anstelle von natürlichen Vegetationseinheiten von quasi-natürlichen Einheiten aus dem Zusammenspiel menschlicher Einflußnahme und natürlicher Umweltbedingungen ausgehen muß. Die aktuell anzutreffende Vegetation wurde daher im Rahmen der vorliegenden Studie als "Status Quo" im Sinne von "Lebensraumeinheiten" auf der Basis von pflanzensoziologischen Verbänden nach DELARZE et al. (1999) definiert. Da vor allem im Gebirge räumlich hochaufgelöste Informationen zu Klima, Wasserhaushalt oder Böden fehlen, galt es zu untersuchen, inwieweit die Vegetationsverbände vom Relief d.h. von der räumlichen Verteilung verschiedener Reliefparameter abhängig sind bzw. inwieweit ihre Habitate allein durch den Einsatz von Reliefdaten mit Hilfe von Digitalen Höhenmodellen charakterisiert werden können. In einem ca. 40km x 20km großen Transekt vom Lötschental zum Turtmanntal im Schweizer Kanton Wallis wurden zu diesem Zweck in mehreren Geländekampagnen, gestützt durch halbautomatische satelliten- und luftbildbasierte Auswerteverfahren und GIS-Ansätze Vegetationskarten auf 2 verschiedenen räumlichen Auflösungen (25m, 5m) erstellt. Dabei wurde das Potential der verschieden räumlich aufgelösten Fernerkundungsdaten für die geobotanisch-inhaltliche Differenzierbarkeit analysiert: während satellitenbasierte Klassifikationen nur bedingt bei genügender Größe der Areale in der Lage waren, zwischen verschiedenen Vegetationsverbänden zu differenzieren und ihre hierarchische Entsprechung eher auf der Stufe von (Sub-) Formationen hatten, konnten mit Hilfe von CIR-Luftbildern 52 Vegetationsklassen auf der synatxonomischen Hierarchiestufe von Pflanzenverbänden differenziert werden. Eine aus der hochauflösenden Vegetationskarte abgeleitete Hemerobiekarte trägt der anthropogenen Einflußnahme Rechnung. Auf Basis der hochauflösenden Vegetationskarte erfolgte eine Analyse der Zusammenhänge zwischen Vegetation und Relief, nachdem geeignete Reliefparameter abgeleitet worden waren. Darüber hinaus wurde mit Hilfe verschiedener Reliefklassifikationsansätze die Hochgebirgslandschaft in Bereiche gleicher geomorphometrischer Eigenschaften im Sinne von „Geotopen“ strukturiert, um deren räumliche Koinzidenz mit den Vegetationsverbänden zu analysieren. Für die verschiedenen Vegetationsverbände waren sowohl qualitativ mit Hilfe von deskriptiv-statistischen Verteilungsmaßen und Flächenbilanzen wie auch mittels analytisch-statistischer Methoden wie Kontingenzkoeffizienten, Hauptkomponentenanalysen und t-Test Zusammenhänge mit verschiedenen Reliefparametern signifikant nachzuweisen. Demgegenüber zeigten die verwendeten Reliefklassifikationsverfahren nur eine geringe Eignung für die Standortindikation. In einem letzten Schritt wurde die räumliche Verbreitung verschiedener Vegetationsverbände mit Hilfe von 2 verschiedenen Modellverfahren (Klassifikations- und Regressionsbäume CART sowie Parallel-Epiped Boxklassifikatoren PPD) unter Einbezug als geeignet identifizierter Reliefparameter simuliert. Es zeigte sich neben einer generellen Überlegenheit der PPD- gegenüber den CART-Modellen, daß vor allem für großflächige, zonale und intensiv bewirtschaftete Vegetationsklassen allein mit Hilfe von Reliefparametern die räumliche Verbreitung mit hoher Genauigkeit (z.T. über 95%) simuliert werden konnte, während für kleinflächige, azonale und extensiv bewirtschaftete Flächen nur Genauigkeiten um 50-70% erreicht wurden. Darüber hinaus war es möglich, aus den Simulationen bzw. deren Fehlern 1. Art die potentielle Verbreitung einzelner Vegetationsklassen zu rekonstruieren, was z.T. durch historische Quellen verifiziert werden konnte. Neben fehlenden Informationen bezüglich der (historischen) Landnutzung, der unzureichenden Parametrisierung von geomorphologischen Prozessen und topologischen Beziehungen lag die hauptsächliche Ursache von weniger signifikanten Zusammenhängen, die sich in der Modellierung vor allem kleinflächiger Einheiten fortsetzte, in der gegenüber den Vegetationsdaten schlechten räumlichen Auflösung des Digitalen Höhenmodells begründet. Diese ist nur unzureichend in der Lage, reale Kleinstrukturen des Reliefs zu repräsentieren. Die angewandte Methodik sowie die entwickelten Modelle dienen vor allem vor dem Hintergrund einer geringen Informationsdichte ökologischer Daten im Hochgebirge der Verbesserung der Inventarisierung globaler Vegetation, eng verknüpft mit der Erforschung, dem Monitoring und dem Schutz von Biodiversität. Nicht zuletzt auch im Hinblick auf potentielle Klima- und damit Habitatveränderungen soll daher die vorliegende Studie sowohl inhaltlich als auch methodisch zur Grundlagenforschung im Bereich der Vegetations- und Hochgebirgsökologie beitragen.The vegetation distribution of high mountain cultural landscapes is characterised by an extreme spatial heterogeneity concerning natural and anthropogenic site factors. In a complex system of direct and indirect factors influencing vegetation distribution landform is the major natural, but indirect ecological factor: landform highly varies the spatial distribution of precipitation, irradiation, air and soil temperature as well as geomorphological processes (avalanches, rockfall etc.). It thus produces a patchwork-like pattern of diverse vegetation habitats. Besides these natural factors the human dimension in the sense of historic and recent land use was and is important for the development of vegetation. Thus present-day vegetation in alpine cultural landscapes has to be regarded largely as quasi-natural replacement vegetation, resulting from the interaction of human impact and natural environmental conditions. In this study present-day vegetation types were therefore defined as the „status quo“ in the sense of „habitat-units“ on the basis of plant sociological vegetation alliances after DELARZE et al. (1999). As spatial information on climatic and other environmental conditions are commonly lacking in mountain areas, the main aim was to analyse to what extent vegetation alliances were dependent on landform i.e. on the spatial distribution of landform parameters. Additionally it had to be investigated to what extent vegetation habitats could be indicated by the exclusive use of landform parameters represented by digital elevation models. For this purpose field campaigns were conducted in a 40km by 20km transect from the Lötschental to the Turtmanntal in the Swiss canton Wallis. Integrating the data, supported by semi-automatic satellite- and aerial photograph-based classification procedures as well as GIS-methodology, resulted in the production of 2 vegetation maps of different resolution (25m, 5m). The potential of the different spatial resolutions of aerial and satellite based remote sensing data was analysed for differentiating geobotanically defined vegetation types: while satellite based classifications could only distinguish between vegetation alliances with habitat areas large enough and were mainly capable of defining (sub-)formations, it was possible to extract 52 vegetation classes at vegetation alliance level using CIR-aerial photographs. Additionally, a hemerobiotic map was derived, showing the degree of anthropogenic influence on the vegetation. Based on the high (spatial and thematic) resolution vegetation map the relation between vegetation and landform was analysed, after a set of appropriate landform parameters had been derived. Furthermore the landscape represented by the digital elevation model was decomposed into area-units of homogeneous geomorphometric characteristics. These area-units in the sense of „geotopes“ were created by applying different landform classification schemes, in order to analyse the spatial concurrence of these “geomorphometric topes” with vegetation alliances. Using qualitative-descriptive distribution measures as well as analytic-statistical methods like contingency tables, principal components analysis and a students t-test, it was possible to prove significant correlations between certain vegetation alliances and landform parameters. In contrast to this the landform classification schemes were hardly suitable for the indication of habitats. In a last step the spatial distributions of different vegetation alliances were simulated using 2 different model approaches (classification and regression trees CART, parallel-epiped box-classificators PPD) and relevant landform parameters. Besides a better performance of the PPD as compared to the CART model it appeared that the spatial distribution of large, zonally arranged and intensively cultivated vegetation classes could be simulated with high accuracy (> 95%) by the exclusive use of landform parameters. In contrast to that respective accuracies for small, azonal and extensively used classes only reached 50-70%. Furthermore it was possible to reconstruct potential distributions of vegetation alliances from the false positive rate of the simulations, which could be verified by the use of historic sources. Besides the lack of information on (historic) land use, insufficient parameterisation of geomorphological processes as well as topological relations, the major source of error within the correlation calculations and in the model simulations mainly of smaller vegetation classes was the poor spatial resolution of the digital elevation model as compared to the vegetation map, not being capable of representing microscale landform characteristics. Especially in the view of a low information density concerning ecological data within high mountain areas, the methodology used here and the models developed aim at improving global vegetation investigations. This research is closely related to the analysis, the monitoring and the protection of biodiversity. Generally, with regard to a potential climate and therefore habitat change, the present study aims at contributing both thematically and methodologically to the research fields of vegetation and high mountain ecology

GMES Fast Track Land Service 2006-2008 - Orthorectification of SPOT 4/5 and IRS-P6 LISS III Data

The GMES (Global Monitoring for Environment and Security) Fast Track Land monitoring Service (FTLS) is a service to provide on a regular basis land cover and land use change datasets, which can be used by a wide range of downstream services at European, national, regional and local scale. Under ESA contract DLR (German Aerospace Center) produced two multi-temporal datasets of orthorectified images covering the participating EU27 and neighbouring countries (overall 38 countries). An operational and automatic processing chain to process about 3700 satellite images has been established including quality control and creation of a European wide consistent GCP database. The orthorectified products are derived from a mixture of high resolution satellite images from SPOT 4 with 20 m GSD, SPOT 5 with 10 m GSD and IRS-P6 LISS III with 23 m GSD, each with four spectral bands, and geometrically corrected towards European Map Projection with 25 m resolution and national map projection for each country with 20 m resolution using DLR’s in-house developed versatile orthorectification S/W package. An overall geometric accuracy of about 10 m RMSE in each direction with respect to the European land cover dataset Image2000 (EU25) and USGS ETM+ land cover dataset (neighbouring countries) has been reached. The paper describes the background of the Image2006 project, the newly developed procedures and methodologies of the automatic and operational orthorectification chain including its limitations in problematic cases, as well as the results in terms of statistical evaluations

Urban Atlas – DLR Processing Chain for Orthorectification of Prism and AVNIR-2 Images and TerraSAR-X as possible GCP Source

In the first part of this paper, the semi-automatic processing chain established at the DLR for the processing of PRISM and AVNIR-2 data in the framework of Urban Atlas is described. Although the processing chain was designed to be fully automatic, the lack of a sufficient accurate reference image necessitates the manual measurement of ground control points (GCP) from digital maps and aerial imagery to fulfill the accuracy requirements of 5 m RMSE in case of PRISM images. In case of AVNIR-2 images, the internal reference database available at DLR was sufficient accurate to allow for an automatic GCP generation. Since no ground truth was available, the included quality check uses different criteria to allow for a quality measure for each image. In the second part of the paper, the accuracy of the orthorectified scenes is analyzed. Up to now, more than 200 PRISM and 100 AVNIR-2 scenes for 43 European cities are processed. The overall accuracy statistics are presented and additionally some single scenes are evaluated in areas where additional ground truth is available. In further investigations, TerraSAR-X data was evaluated regarding its potential as source for GCPs. The very high geometric accuracy of geocoded data of the TerraSAR-X satellite has been shown in several investigations and thus qualifies the data as GCP source. Different methods of retrieving GCPs from TerraSAR-X data have been evaluated in the third part of the paper: manual measurements or local image matching using mutual information. By adjustment calculations, falsely matched points can be eliminated and an optimal improvement can be found. After the orthorectification of the PRISM data using these improvements, the results are compared to PRISM data that were orthorectified using conventional ground control information from GPS measurements

ESA's Atmospheric Chemistry Mission - A Status Report

The challenges in understanding the atmospheric chemistry processes for climate research and to model and forecast the air quality on regional scale are still manifold. Presently, ESA is providing atmospheric chemistry data both from their core missions ERS-2 and Envisat as well as from Third Party Missions (TPM). ESAs core atmospheric chemistry instruments onboard ERS-2 and ENVISAT are GOME, GOMOS, MIPAS and SCIAMACHY. With ERS-2 launched in 1995 and ENVISAT in 2002, these instruments are providing a rich dataset to the scientific community and supporting operational services since more than 14 years. Currently, data from the following missions can be provided through ESA: ACE-FTS and MAESTRO data from the CSA SCISAT mission, OSIRIS and SMR data from the SSC ODIN mission, TANSO-FTS AND -CAI data from the JAXA/NIES/MOE GOSAT mission. It is currently planned that also OMI data from the NASA AURA mission will be accessible through ESA. In addition to the operational data, ESA acknowledges that the science community is developing and providing a number of important, quality products based on ESA missions. The presentation will summarise the status of all the issues addressed above with a focus on ESA instruments, algorithm development and data distribution