Can time-series Sentinel images be used to properly identify wetland plant communities?
Open Access
- 12 December 2022
- journal article
- research article
- Published by Taylor & Francis in GIScience & Remote Sensing
- Vol. 59 (1) , 2202-2216
Abstract
No abstract availableKeywords
Funding Information
- research was jointly funded by the National Natural Science Foundation of China
- Science and Technology Development program of Jilin Province, China
- Youth Innovation Promotion Association of Chinese Academy of Sciences
- Professional Association of the Alliance of International Science Organizations
- Young Scientist Group Project of Northeast Institute of Geography and Agroecology
This publication has 51 references indexed in Scilit:
- Remote sensing of plant communities as a tool for assessing the condition of semiarid Mediterranean saline wetlands in agricultural catchmentsInternational Journal of Applied Earth Observation and Geoinformation, 2014
- Continuous monitoring of forest disturbance using all available Landsat imageryRemote Sensing of Environment, 2012
- Coastal wetland vegetation classification with a Landsat Thematic Mapper imageInternational Journal of Remote Sensing, 2011
- Radar detection of wetland ecosystems: a reviewInternational Journal of Remote Sensing, 2008
- Using a hybrid fuzzy classifier (HFC) to map typical grassland vegetation in Xilin River Basin, Inner Mongolia, ChinaInternational Journal of Remote Sensing, 2008
- Mapping specific habitats from remotely sensed imagery: Support vector machine and support vector data description based classification of coastal saltmarsh habitatsEcological Informatics, 2007
- Mapping an invasive plant, Phragmites australis, in coastal wetlands using the EO-1 Hyperion hyperspectral sensorRemote Sensing of Environment, 2007
- Mapping salt-marsh vegetation by multispectral and hyperspectral remote sensingRemote Sensing of Environment, 2006
- A rule-based method for mapping Canada's wetlands using optical, radar and DEM dataInternational Journal of Remote Sensing, 2005
- Spectral discrimination of vegetation types in a coastal wetlandRemote Sensing of Environment, 2003