Delineation of the forest-tundra ecotone using texture-based classification of satellite imagery ...

• Main Authors: Guo, W, Rees, G, Hofgaard, A
• Format: Article in Journal/Newspaper
• Language: English
• Published: Informa UK Limited 2020
• Subjects: 37 Earth Sciences; 4013 Geomatic Engineering; 40 Engineering; 15 Life on Land; Arctic; Tundra
• Online Access: https://dx.doi.org/10.17863/cam.55311; https://www.repository.cam.ac.uk/handle/1810/308221

© 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group. The transition zone between the boreal forest and Arctic tundra, the forest-tundra ecotone (FTE), is an area of high ecological and climatological significance. Despite its importance, a globally consistent high spatial resolution mapping is lacking. Accurate mapping of the FTE requires the use of satellite remote sensing data. Here we use the Landsat Vegetation Continuous Fields (VCF) product and reference point data to derive the location and characteristics of the FTE. An image texture-based supervised classification scheme is developed based on a study area in Central Eurasia to statistically exploit the spatial patterns of the transition zone. Texture statistics for the VCF image are derived from the grey-level co-occurrence matrix (GLCM) based on which the study area is classified into forest, tundra, and FTEs. Adaptive parameterization is implemented to achieve optimal classification performance in the study area. This method is ...