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Faculty of Biology, Chemistry and Earth Sciences

Graduate Program (M.Sc.) - Global Change Ecology

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Exercise course/Seminar: Remote Sensing Data Analysis (GCE:B7b) (74091)

SS 2021


Frank Weiser

Exercise, 3 ECTS

Starting date: t.b.a.

Learning Objectives (Module B7): Possibilities of continual surface data collection through remote sensing for biodiversity research are taught. An important objective is to inform about the different ways of closing spatial gaps in field data collection by using remote sensing data. A suitable sampling design comes along with in-situ field data collection as well as processing steps in the evaluation of different data sets (field and remote sensing data). The latter includes statistical procedures and spatial models.

Course Content: Results of biological assessments and records from applied sciences such as forestry, nature conservation, agriculture in the field (Basal area, forest successional stages, species, drought impact, tree mortality etc.) are linked with remote sensing data (hyperspectral data, results from remotely sensed field data and products such as FAO land cover classification system LCCS or Global Land Cover - Sentinel 2; LAI records and hemispheric measuring). With selected examples, the potential and limitations of using aircraft- and satellite-based missions for the collection of biodiversity patterns will be shown. Processing steps like dimension reduction, index calculation as well as spatial filters and measures to determine heterogeneity of habitats and ecosystems will be taught.

 


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