GIS for Mapping Vegetation

GIS-based mapping of vegetation is a broadly established application with strong interconnections with remote sensing, digital surveying and mapping, as well as with more traditional approaches of mapping and cartography. It is also a major objective of vegetation sciences like agriculture, forestry, geobotany, biogeography, landscape ecology, and resource management and makes it a strongly interdisciplinary topic and task. In this context, the GIS-based mapping or monitoring results like vegetation maps, vegetation inventories, land use/land cover maps, or vegetation time series (like crop rotations) serve as a key information source for spatial decision making processes. Besides the main mapping objective, the mapping scale generally determines the mapping technology and is therefore under permanent change. For the last decades, field surveys were supported by aerial photography and satellite-based remote sensing. Consequently, the area of interest ranged from several hectares to global coverages. However, in the last ten years Unmanned Aerial Systems (UAS) or low-altitude flying manned vehicles like gyrocopters are increasingly used as sensor platforms for proximal and airborne remote sensing, providing subcentimeter resolution data. In addition to satellite-based systems (e.g. Landsat, Sentinel-2) they are combined with ground surveying techniques like field sampling, GPS, and laser scanning which already support vegetation mapping at all scales. This chapter of GIS applications on Mapping of Vegetation focuses on four major topics. In the Plant Communities and Vegetation Inventories section the technical developments, scale levels, GIS-based mapping methodologies, and the variety of available data products are handled. The follow-up section discusses official remote sensing and GIS-based datasets which contain highly valuable vegetation information, but are not intended as inventories in the first place. Multi-Data Methods which make use of such vegetation information to enhance remote sensing-based land use/land cover mapping from global to local scales are discusses thereafter. In the final section, the illustration of GIS methods for the analysis of remote sensing-based super high resolution Digital Surface Models (DSMs) in forestry and agriculture focuses the current state of the art in GIS-based vegetation mapping.