Classification of shoreline vegetation in the Western Basin of Lake Erie using airborne hyperspectral imager HSI2, Pleiades and UAV data-Reference-Cited by-同舟云学术

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Classification of shoreline vegetation in the Western Basin of Lake Erie using airborne hyperspectral imager HSI2, Pleiades and UAV data

Published:2018-11-13 Issue:8 Volume:40 Page:3008-3028
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Rupasinghe Prabha Amali¹,Simic Milas Anita¹,Arend Kristin²,Simonson Martin Albert³,Mayer Christine³,Mackey Scudder⁴

Affiliation:

1. Department of Geology, Bowling Green State University, Bowling Green, OH, USA

2. Ohio Department of Natural Resources, Division of Wildlife, Old Woman Creek National Estuarine Research Reserve, Huron, OH, USA

3. Department of Environmental Sciences and Lake Erie Centre, University of Toledo, Toledo, OH, USA

4. Ohio Department of Natural Resources, Office of Coastal Management, Sandusky, OH, USA

Funder

National Oceanic and Atmospheric Administration

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2018.1539267

Reference64 articles.

1. Spectral discrimination of papyrus vegetation (Cyperus papyrus L.) in swamp wetlands using field spectrometry

2. Anderson, J. R. 1976. “A Land Use and Land Cover Classification System for Use with Remote Sensor Data. Vol. 964.” US Government Printing Office. Accessed March 15. https://books.google.ca/books?hl=en‎&id=dE-ToP4UpSIC&oi=fnd&pg=PA1&dq=Anderson,+J.+R.+(1976).+A+land+use+and+land+cover+classification+system+for+use+with+remote+sensor+data+(Vol.+964).+US+Government+Printing+Office.&ots=sWqq_X1f4E&sig=bcC7c7fbzdrUvkhSyztASJVzf6Q.

3. MULTI-TEMPORAL LANDSAT IMAGE CLASSIFICATION AND CHANGE ANALYSIS OF LAND COVER IN THE TWIN CITIES (MINNESOTA) METROPOLITAN AREA

4. Remote Sensing of Wetlands

5. Evaluation of Random Forest and Adaboost tree-based ensemble classification and spectral band selection for ecotope mapping using airborne hyperspectral imagery

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