Mapping invasive noxious weed species in the alpine grassland ecosystems using very high spatial resolution UAV hyperspectral imagery and a novel deep learning model

Fei Xinga College of Geography and Remote Sensing, Hohai University, Nanjing, China;b School of Earth Sciences and Engineering, Hohai University, Nanjing, China;c Department of Geography and Planning, University of Saskatchewan, Saskatoon, Canada;d The National Key Laboratory of Water Disaster Prevention, Hohai University, Nanjing, ChinaView further author information

Ru Ana College of Geography and Remote Sensing, Hohai University, Nanjing, ChinaView further author information

Xulin Guoc Department of Geography and Planning, University of Saskatchewan, Saskatoon, CanadaView further author information

Xiaoji Shend The National Key Laboratory of Water Disaster Prevention, Hohai University, Nanjing, China;e Yangtze Institute for Conservation and Development, Hohai University, Nanjing, ChinaCorrespondence[email protected]
View further author information

Mapping invasive noxious weed species in the alpine grassland ecosystems using very high spatial resolution UAV hyperspectral imagery and a novel deep learning model

Information for

Open access

Opportunities

Help and information

Your download is now in progress and you may close this window

Login or register to access this feature

Mapping invasive noxious weed species in the alpine grassland ecosystems using very high spatial resolution UAV hyperspectral imagery and a novel deep learning model

Citations (0)

Related research

To cite this article:

Download citation

Information for

Open access

Opportunities

Help and information

Keep up to date