Field spectroradiometer and simulated multispectral bands for discriminating invasive species from morphologically similar cohabitant plants-Reference-Cited by-同舟云学术

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Field spectroradiometer and simulated multispectral bands for discriminating invasive species from morphologically similar cohabitant plants

Published:2017-11-06 Issue:3 Volume:55 Page:417-436
ISSN:1548-1603
Container-title:GIScience & Remote Sensing
language:en
Short-container-title:GIScience & Remote Sensing

Author:

Tesfamichael Solomon G.¹,Newete Solomon W.²³,Adam Elhadi⁴,Dubula Bambo¹^ORCID

Affiliation:

1. Department of Geography, Environmental Management and Energy Studies, University of Johannesburg, Johannesburg, South Africa

2. Agricultural Research Council-Institute for Soil, Climate and Water (ARC-ISCW), Geoinformation Science Division, Pretoria, South Africa

3. School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, Johannesburg, South Africa

4. School of Geography, Archaeological and Environmental Studies, University of the Witwatersrand, Johannesburg, South Africa

Funder

University of Johannesburg

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/15481603.2017.1396658

Reference54 articles.

1. Mapping Prosopis glandulosa (mesquite) in the semi-arid environment of South Africa using high-resolution WorldView-2 imagery and machine learning classifiers

2. Mapping invasive species and spectral mixture relationships with neotropical woody formations in southeastern Brazil

3. Identifying invasive plant species using field spectroscopy in the VNIR region in successional systems of north-central Virginia

4. Mapping Bugweed (Solanum mauritianum) Infestations in Pinus patula Plantations Using Hyperspectral Imagery and Support Vector Machines

5. A training algorithm for optimal margin classifiers

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5. Technological innovations enhance invasive species management in the anthropocene;BioScience;2023-04

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