Vegetation Characterization at Community Level Using Sentinel-2 Satellite Data and Random Forest Classifier in Western H
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RESEARCH ARTICLE
Vegetation Characterization at Community Level Using Sentinel-2 Satellite Data and Random Forest Classifier in Western Himalayan Foothills, Uttarakhand Arun Pratap Mishra1
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Ishwari Datt Rai2 • Divesh Pangtey2 • Hitendra Padalia2
Received: 15 July 2020 / Accepted: 29 October 2020 Ó Indian Society of Remote Sensing 2020
Abstract Characterization of forests is an important aspect for the management and conservation of biodiversity and satellite remote sensing provides opportunity to rapidly assess biodiversity patterns across large geographical areas. The present study aimed to characterize vegetation in a landscape with heterogenous topography using medium resolution Sentinel-2 satellite data and random forest (RF) machine learning algorithm. The study area falls in the Nandhaur landscape of western Himalayan foothills and forms an important part of the Terai Arc Landscape. Sentinel-2 satellite data of January, April and May months was used along with SRTM Digital Elevation Model. Primary field data was collected for dominant vegetation community characteristics and used for training and validation of the model in RF. A total of eleven forest vegetation communities was characterized with an accuracy of 70–87% for individual imageries as well as in collocation of images. Satellite image of April was found most useful for discriminating forest communities with high spectral separability among communities. Variable important analysis revealed Vegetation Red Edge, Narrow NIR and NIR bands were useful for discriminating communities with maximum information along with SWIR and Red bands. Study found that collocation of the multi-date images was useful for classifying communities with higher accuracies. This attempt at characterizing heterogeneous vegetation communities with advanced machine learning tools in Himalayan foothills showed encouraging outcomes which can be used in future studies for monitoring and management of key habitats in this area. Keywords Forest community characterization Random forest Nandhaur landscape Sentinel
Introduction
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s12524-020-01253-x) contains supplementary material, which is available to authorized users. & Arun Pratap Mishra [email protected] Ishwari Datt Rai [email protected] Divesh Pangtey [email protected] Hitendra Padalia [email protected] 1
Botanical Survey of India, Northern Regional Centre, 192 Kaulagarh Road, Dehradun, Uttarakhand, India
2
Indian Institute of Remote Sensing, 4, Kalidas Road, Dehradun, Uttarakhand, India
Western Himalaya is one of the geo-botanical sub-regions of the Himalayan Biodiversity Hotspot (Myers 1988) and well-known for its rich wealth of flora and fauna distributed over a wide environmental gradient. In this area, the heterogeneity in the local climatic conditions due to topographic variation leads to formation of a variety of vegetation communities distributed along the suitable environmental conditions. The wide-
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