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Species-Level Vegetation Mapping in a Himalayan Treeline Ecotone Using Unmanned Aerial System (UAS) Imagery

1
Department of Geography & Earth Science, University of Wisconsin-La Crosse, La Crosse, WI 54601, USA
2
National Socio-Environmental Synthesis Center (SESYNC), Annapolis, MD 21401, USA
3
Central Department of Botany, Tribhuvan University, Kathmandu 44613, Nepal
4
College of Applied Sciences, Kathmandu 44613, Nepal
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2018, 7(11), 445; https://doi.org/10.3390/ijgi7110445
Received: 8 October 2018 / Revised: 9 November 2018 / Accepted: 12 November 2018 / Published: 14 November 2018
Understanding ecological patterns and response to climate change requires unbiased data on species distribution. This can be challenging, especially in biodiverse but extreme environments like the Himalaya. This study presents the results of the first ever application of Unmanned Aerial Systems (UAS) imagery for species-level mapping of vegetation in the Himalaya following a hierarchical Geographic Object Based Image Analysis (GEOBIA) method. The first level of classification separated green vegetated objects from the rest with overall accuracy of 95%. At the second level, seven cover types were identified (including four woody vegetation species). For this, the suitability of various spectral, shape and textural features were tested for classifying them using an ensemble decision tree algorithm. Spectral features alone yielded ~70% accuracy (kappa 0.66) whereas adding textural and shape features marginally improved the accuracy (73%) but at the cost of a substantial increase in processing time. Contrast in plant morphological traits was the key to distinguishing nearby stands as different species. Hence, broad-leaved versus fine needle leaved vegetation were mapped more accurately than structurally similar classes such as Rhododendron anthopogon versus non-photosynthetic vegetation. Results highlight the potential and limitations of the suggested UAS-GEOBIA approach for detailed mapping of plant communities and suggests future research directions. View Full-Text
Keywords: species mapping; Unmanned Aerial Systems; hierarchical GEOBIA; Himalaya; treeline ecotone; random forest; Langtang National Park species mapping; Unmanned Aerial Systems; hierarchical GEOBIA; Himalaya; treeline ecotone; random forest; Langtang National Park
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Mishra, N.B.; Mainali, K.P.; Shrestha, B.B.; Radenz, J.; Karki, D. Species-Level Vegetation Mapping in a Himalayan Treeline Ecotone Using Unmanned Aerial System (UAS) Imagery. ISPRS Int. J. Geo-Inf. 2018, 7, 445.

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