A5027143880- Land Use and Ecosystem Services
- Coastal wetland ecosystem dynamics
- Remote Sensing in Agriculture
- Species Distribution and Climate Change
- Flood Risk Assessment and Management
- Environmental Changes in China
- Wetland Management and Conservation
- Remote-Sensing Image Classification
- Conservation, Biodiversity, and Resource Management
- Peatlands and Wetlands Ecology
Northeast Institute of Geography and Agroecology
2020-2024
Chinese Academy of Sciences
2020-2024
University of Chinese Academy of Sciences
2020-2024
Understanding the spatial patterns of plant communities is important for sustainable wetland ecosystem management and biodiversity conservation. With rapid development unmanned aerial vehicle (UAV) technology, UAV-borne hyperspectral data with high resolution have become ideal accurate classification communities. In this article, four dominant (Phragmites australis, Typha orientalis, Suaeda glauca, Scirpus triqueter) two unvegetated cover types (water bare land) in Momoge Ramsar site were...
Phragmites australis (P. australis) is one of the most important plant species found in wetland ecosystems, and its aboveground biomass (AGB) a key indicator for assessing quality or health site. In this study, we combined Sentinel-1/2 images field observation data collected 2020, to delineate distribution P. Momoge Ramsar Wetland site by using random forest method, further, estimate AGB comparing multiple linear regression models. The results showed that overall classification accuracy...
Understanding the distribution of wetland plant communities is critical to biodiversity conservation and habitat sustainable management, especially for migratory birds. However, limited road accessibility low spectral discriminability make mapping inadequate health assessment, necessitating improvement classification methods. In this study, we proposed a random forest classifier that combined multi-source remote sensing features community evaluated method Momoge Ramsar site (MRWS) in China....
The propagation of the invasive <i>Spartina alterniflora</i> (<i>S. alterniflora</i>) has seriously affected health coastal wetland ecosystems in China and thus requires an urgent response. In this research, we construct a feature vector set containing phenological other time-series features based on Google Earth Engine (GEE) platform by combining dense images from Sentinel-1 Sentinel-2 satellites. We obtained dataset annual distribution <i>S. Yellow River Delta (YRD) 2016 to 2021 developing...
The composition and dynamics of wetland plant communities play a critical role in maintaining the functionality ecosystems serve as important indicators degradation restoration. Accurately identifying using remote sensing techniques remains challenging due to complex environment cloud contamination. Here, we applied sample migration method based on change vector analysis random forest (RF) classifier incorporating SHapley Additive exPlanations (SHAP) explore spatiotemporal changes western...
Climate change and human activities have reduced the area degraded functions services of wetlands in China. To protect restore wetlands, it is urgent to predict spatial distribution potential wetlands. In this study, China was simulated by integrating advantages Google Earth Engine with geographic big data machine learning algorithms. Based on a wetland database 46,000 samples an indicator system 30 hydrologic, soil, vegetation, topographic factors, simulation model constructed The accuracy...
Wetland rehabilitation, highlighted in the United Nations (UN) Sustainable Development Goals (SDGs), is imperative for responding to decreased regional biodiversity and degraded ecosystem functions services. Knowing where most suitable wetland rehabilitation areas are can strengthen scientific planning decision-making natural conservation management implementation. Therefore, we integrated multisource geospatial data characterizing hydrological, topographical, management, policy factors,...
Examining vegetation aboveground biomass (AGB) changes is important to understanding wetland carbon sequestration. Here, we combined the field-measured AGB data (458 samples) from 2009 2021, moderate resolution imaging spectroradiometer reflectance products, and climatic reveal variations of marshes in Northeast China by comparing various models driven different indicators. The results indicated that random forest model six indices, land surface temperature, water index achieved accurate...