Land cover classification of treeline ecotones along a 1100 km latitudinal transect using spectral? and three?dimensional information from <scp>UAV</scp> ?based aerial imagery
نویسندگان
چکیده
The alpine treeline ecotone is expected to move upwards in elevation with global warming. Thus, mapping ecotones crucial monitoring potential changes. Previous remote sensing studies have focused on the usage of satellites and aircrafts for ecotone. However, can be highly heterogenous, thus use imagery higher spatial resolution should investigated. We evaluate using unmanned aerial vehicles (UAVs) collection ultra-high land covers. acquired field reference data from 32 sites along a 1100 km latitudinal gradient Norway (60–69°N). Before classification, we performed superpixel segmentation UAV-derived orthomosaics assigned cover classes segments: rock, water, snow, shadow, wetland, tree-covered area five within ridge-snowbed gradient. calculated features providing spectral, textural, three-dimensional vegetation structure, topographical shape information classification. To influence acquisition time during growing season geographical variations, four sets classifications: global, seasonal-based, regional-based seasonal-regional-based. found no differences overall accuracy (OA) between different classifications, model observations irrespective timing region had an OA 73%. When accounting similarities closely related gradient, increased 92.6%. spectral visible, red-edge near-infrared bands most important predict classes. Our results show that UAVs efficient ecotones, get accurate maps. This overcome constraints short field-season or low-resolution data.
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ژورنال
عنوان ژورنال: Remote Sensing in Ecology and Conservation
سال: 2022
ISSN: ['2056-3485']
DOI: https://doi.org/10.1002/rse2.260