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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/21242
Title: Fractional cover mapping of invasive plant species by combining very high-resolution stereo and multi-sensor multispectral imageries
Authors: Khare S.
Latifi H.
Rossi S.
Ghosh, Sanjay Kumar
Published in: Forests
Abstract: Invasive plant species are major threats to biodiversity. They can be identified and monitored by means of high spatial resolution remote sensing imagery. This study aimed to test the potential of multiple very high-resolution (VHR) optical multispectral and stereo imageries (VHRSI) at spatial resolutions of 1.5 and 5mto quantify the presence of the invasive lantana (Lantana camara L.) and predict its distribution at large spatial scale using medium-resolution fractional cover analysis. We created initial training data for fractional cover analysis by classifying smaller extent VHR data (SPOT-6 and RapidEye) along with three dimensional (3D) VHRSI derived digital surface model (DSM) datasets. We modelled the statistical relationship between fractional cover and spectral reflectance for a VHR subset of the study area located in the Himalayan region of India, and finally predicted the fractional cover of lantana based on the spectral reflectance of Landsat-8 imagery of a larger spatial extent. We classified SPOT-6 and RapidEye data and used the outputs as training data to create continuous field layers of Landsat-8 imagery. The area outside the overlapping region was predicted by fractional cover analysis due to the larger extent of Landsat-8 imagery compared with VHR datasets. Results showed clear discrimination of understory lantana from upperstory vegetation with 87.38% (for SPOT-6), and 85.27% (for RapidEye) overall accuracy due to the presence of additional VHRSI derived DSM information. Independent validation for lantana fractional cover estimated root-mean-square errors (RMSE) of 11.8% (for RapidEye) and 7.22% (for SPOT-6), and R2 values of 0.85 and 0.92 for RapidEye (5 m) and SPOT-6 (1.5 m), respectively. Results suggested an increase in predictive accuracy of lantana within forest areas along with increase in the spatial resolution for the same Landsat-8 imagery. The variance explained at 1.5 m spatial resolution to predict lantana was 64.37%, whereas it decreased by up to 37.96% in the case of 5 m spatial resolution data. This study revealed the high potential of combining small extent VHR and VHRSI- derived 3D optical data with larger extent, freely available satellite data for identification and mapping of invasive species in mountainous forests and remote regions. © 2019 by the authors.
Citation: Forests, 10(7)
URI: https://doi.org/10.3390/f10070540
http://repository.iitr.ac.in/handle/123456789/21242
Issue Date: 2019
Publisher: MDPI AG
Keywords: 3D
DSM
Fractional cover analysis
Lantana camara
RapidEye
SPOT-6
ISSN: 19994907
Author Scopus IDs: 56448200900
15073733900
57192104579
55478984700
Author Affiliations: Khare, S., Département des Sciences Fondamentales, Université du Québec à Chicoutimi, Saguenay, QC G7H 2B1, Canada, Department of Civil Engineering, Geomatics Engineering Division, Indian Institute of Technology, Roorkee, 247667, India
Latifi, H., Department of Photogrammetry and Remote Sensing, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, 19967-15433, Iran, Department of Remote Sensing, University of Würzburg, Würzburg, D-97074, Germany
Rossi, S., Département des Sciences Fondamentales, Université du Québec à Chicoutimi, Saguenay, QC G7H 2B1, Canada, Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, Guangdong Provincial Key Laboratory of Applied Botany, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, China
Ghosh, S.K., Department of Civil Engineering, Geomatics Engineering Division, Indian Institute of Technology, Roorkee, 247667, India
Funding Details: Funding: The SPOT-6 multispectral and stereo pair dataset were funded by European Space Agency (ESA) with project id: 33429 and and RapidEye datasets were funded by RapidEye Science Archive (RESA) with project id: 00184. European Space Agency, ESA: 00184, 33429
Corresponding Author: Khare, S.; Département des Sciences Fondamentales, Canada; email: siddhartha.khare1@uqac.ca
Appears in Collections:Journal Publications [CE]

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