| Summary: | Since the early 20th century, changes of agricultural practices in Sweden have led to an increased competition from more dominant species in the old forage meadows. As a result, populations of the orchid Gymnadenia nigra (L.) Reichb.f. (G. nigra), have decreased significantly. It has also been discussed whether the climatic changes have had an impact on G. nigra due to a greening in northern latitudes. Today, G. nigra is an endangered species, its populations are decreasing and finding possible future habitat for it is therefore of great importance. By using remote sensing techniques, parameters such as Normalized Difference Vegetation Index (NDVI) can be calculated, which is based on the spectral response of vegetation. NDVI is widely used in vegetation studies analyzing biomass productivity and density, whereby it can act as an indicator for a greening or browning of vegetation. Furthermore, by using Geographical Information Systems (GIS) techniques, conditions such as slope, elevation, topographic wetness index (TWI) and aspect can be derived from a Digital Elevation Model (DEM). This report will use the techniques of remote sensing and GIS to 1) analyze the vegetation changes, 2) create a habitat profile based on prevailing conditions of G. nigra locales in Vålådalen, Jämtland, Northern Sweden and 3) use this profile to conduct a Multi Criteria Analysis (MCA), based on the Analytical Hierarchy Profile (AHP) to identify possible future habitat in the valley, visualized in a suitability map. It is therefore both an analysis concerning G. nigra as well as an evaluation of the method. I found that the number of flowers increased due to an increase in locales, especially since 2014, in Vålådalen. An increase has also occurred in NDVI, which contradicts the initial expectation that increased NDVI, representing increased competition, would negatively impact G. nigra. The results of the climatic impacts on G. nigra were somewhat ambiguous, however, the increased mean temperature coincides with the increase in NDVI ...
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