Scale-specific Hyperspectral Remote Sensing Approach in Environmental Research

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Abstract:

Hyperspectral remote-sensing data can contribute significantly to data analysis in research, opening up a wide spectrum for fields of application due to geometrical as well as spectral characteristics, e.g. in water status analysis, in the classification of vegetation types, in the classification of physical-biochemical vegetation parameters, in classifying soil composition and structure, and in determining large-scale soil contamination. Hence, there is a tremendous demand for hyperspectral information. However the use of commercial hyperspectral data is associated with a number of problems and a great deal of time and effort is required for research using hyperspectral data that spans different spatial and/or hierarchical as well as temporal scales. As a result few investigations have been conducted on the causal relationships between imaging hyperspectral signals and meaningful vegetation variables over a longer monitoring period. At the Helmholtz Centre for Environmental Research (UFZ) Leipzig a scale-specific hyperspectral remote sensing based on the sensors AISAEAGLE (400–970 nm) and AISA-HAWK (970–2500 nm) has been set up. On three different scales (plot, local and regional) intensive investigations are being carried out on the spatio-temporal responses of biophysical and biochemical state variables of vegetation, soil and water compared to the hyperspectral response. This paper introduces and discusses the scale approach and demonstrates some preliminary examples from its implementation.

German
Hyperspektraldaten stellen für die Forschung eine sehr bedeutsame Auswertegrundlage dar, da sie aufgrund ihrer geometrischen als auch spektralen Eigenschaften eine Vielzahl unterschiedlicher Anwendungsgebiete, z.B. Gewässerzustandserfassung, Vegetationsklassifizierungen, Charakterisierung physikalisch-biochemischer Vegetationsparameter, Strukturierung und Zusammensetzung des Bodens, Erfassung von großflächigen Bodenkontaminationen, eröffnen. Es besteht somit ein sehr hoher Bedarf an Hyperspektralinformationen. Der Einsatz von kommerziellen Hyperspektraldaten ist jedoch mit einer Vielzahl von Problemen verbunden. So sind Forschungen hinsichtlich unterschiedlicher räumlich/hierarchischer als auch zeitlicher Skalen mit Hyperspektraldaten nur sehr schwer möglich, andererseits existieren nur wenige Untersuchungen zu kausalen Zusammenhängen zwischen abbildenden Hyperspektralsignalen und gesuchten Vegetationsvariablenüber einen langen Monitoringzeitraum. Am Helmholtz Zentrum für Umweltforschung (UFZ) Leipzig wurde eine skalenspezifische hyperspektrale Fernerkundung auf Grundlage der Sensoren AISA-EAGLE (400–970 nm) und AISA-HAWK (970–2500 nm) etabliert. In drei unterschiedlichen Maßstabsbereichen (Grundstück (plot), kommunal (local) und regional) werden intensive Untersuchungen zum raum-zeitlichen Verhalten von biophysikalischen und biochemischen Zustandsgrößen von Vegetation, Boden und Wasser gegenüber hyperspectral response durchgeführt. Im Artikel wird der Skalenansatz vorgestellt, diskutiert und erste Umsetzungsbeispiele gezeigt.

Keywords: IMAGING HYPERSPECTRAL REMOTE SENSING; MULTI-SCALE ANALYSES; VEGETATION MONITORING

Document Type: Research Article

DOI: http://dx.doi.org/10.1127/1432-8364/2012/0141

Publication date: October 1, 2012

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  • Photogrammetrie - Fernerkundung - Geoinformation (PFG) is an international scholarly journal covering the progress and application of photogrammetric methods, remote sensing technology and the intricately connected field of geoinformation processing.

    Papers published in PFG highlight new developments and applications of these technologies in practice. The journal hence addresses both researchers and student of these disciplines at academic institutions and universities and the downstream users in both the private sector and public administration.

    PFG places special editorial emphasis on the communication of new methodologies in data acquisition, new approaches to optimized processing and interpretation of all types of data which were acquired by photogrammetric methods, remote sensing, image processing and the computer-aided interpretation of such data in general.

    PFG is the official journal of the German Society of Photogrammetry and Remote Sensing.
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