Dehua Mao
Orcid: 0000-0003-3101-9153
According to our database1,
Dehua Mao
authored at least 27 papers
between 2012 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
Potential of Sample Migration and Explainable Machine Learning Model for Monitoring Spatiotemporal Changes of Wetland Plant Communities.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024
Identify and map coastal aquaculture ponds and their drainage and impoundment dynamics.
Int. J. Appl. Earth Obs. Geoinformation, 2024
2023
Modeling potential wetland distributions in China based on geographic big data and machine learning algorithms.
Int. J. Digit. Earth, December, 2023
Comparison of Machine Learning Methods for Predicting Soil Total Nitrogen Content Using Landsat-8, Sentinel-1, and Sentinel-2 Images.
Remote. Sens., 2023
Land Use Change and Hotspot Identification in Harbin-Changchun Urban Agglomeration in China from 1990 to 2020.
ISPRS Int. J. Geo Inf., 2023
2022
High-Resolution Mapping Changes in the Invasion of Spartina Alterniflora in the Yellow River Delta.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022
Mapping Coastal Wetlands Using Transformer in Transformer Deep Network on China ZY1-02D Hyperspectral Satellite Images.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022
Mapping Phragmites australis Aboveground Biomass in the Momoge Wetland Ramsar Site Based on Sentinel-1/2 Images.
Remote. Sens., 2022
Annual Wetland Mapping in Metropolis by Temporal Sample Migration and Random Forest Classification with Time Series Landsat Data and Google Earth Engine.
Remote. Sens., 2022
3DUNetGSFormer: A deep learning pipeline for complex wetland mapping using generative adversarial networks and Swin transformer.
Ecol. Informatics, 2022
Tracking annual dynamics of mangrove forests in mangrove National Nature Reserves of China based on time series Sentinel-2 imagery during 2016-2020.
Int. J. Appl. Earth Obs. Geoinformation, 2022
2021
Mapping Wetland Plant Communities Using Unmanned Aerial Vehicle Hyperspectral Imagery by Comparing Object/Pixel-Based Classifications Combining Multiple Machine-Learning Algorithms.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021
Identifying Urban Functional Areas in China's Changchun City from Sentinel-2 Images and Social Sensing Data.
Remote. Sens., 2021
2020
Combining Artificial Neural Network and Ordinary Kriging to Predict Wetland Soil Organic Carbon Concentration in China's Liao River Basin.
Sensors, 2020
Monitoring Invasion Process of Spartina alterniflora by Seasonal Sentinel-2 Imagery and an Object-Based Random Forest Classification.
Remote. Sens., 2020
Mapping the Essential Urban Land Use in Changchun by Applying Random Forest and Multi-Source Geospatial Data.
Remote. Sens., 2020
Tracking long-term floodplain wetland changes: A case study in the China side of the Amur River Basin.
Int. J. Appl. Earth Obs. Geoinformation, 2020
2019
Rapid Invasion of <i>Spartina Alterniflora</i> in the Coastal Zone of Mainland China: Spatiotemporal Patterns and Human Prevention.
Sensors, 2019
Monitoring 40-Year Lake Area Changes of the Qaidam Basin, Tibetan Plateau, Using Landsat Time Series.
Remote. Sens., 2019
A New Vegetation Index to Detect Periodically Submerged Mangrove Forest Using Single-Tide Sentinel-2 Imagery.
Remote. Sens., 2019
Rapid expansion of coastal aquaculture ponds in China from Landsat observations during 1984-2016.
Int. J. Appl. Earth Obs. Geoinformation, 2019
2018
Remote. Sens., 2018
Rapid Invasion of <i>Spartina alterniflora</i> in the Coastal Zone of Mainland China: New Observations from Landsat OLI Images.
Remote. Sens., 2018
Monitoring loss and recovery of mangrove forests during 42 years: The achievements of mangrove conservation in China.
Int. J. Appl. Earth Obs. Geoinformation, 2018
2016
Evaluating the Effectiveness of Conservation on Mangroves: A Remote Sensing-Based Comparison for Two Adjacent Protected Areas in Shenzhen and Hong Kong, China.
Remote. Sens., 2016
Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, 2016
2012
Integrating AVHRR and MODIS data to monitor NDVI changes and their relationships with climatic parameters in Northeast China.
Int. J. Appl. Earth Obs. Geoinformation, 2012