Meng Zhang
Orcid: 0000-0003-3082-9410Affiliations:
- Central South University of Forestry and Technology, Research Center of Forest Remote Sensing and Information Engineering, Changsha, China
According to our database1,
Meng Zhang
authored at least 13 papers
between 2018 and 2023.
Collaborative distances:
Collaborative distances:
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Bibliography
2023
Driving Mechanisms of Spatiotemporal Heterogeneity of Land Use Conflicts and Simulation under Multiple Scenarios in Dongting Lake Area.
Remote. Sens., September, 2023
Mapping Mangrove Using a Red-Edge Mangrove Index (REMI) Based on Sentinel-2 Multispectral Images.
IEEE Trans. Geosci. Remote. Sens., 2023
Forest Mapping Using a VGG16-UNet++& Stacking Model Based on Google Earth Engine in the Urban Area.
IEEE Geosci. Remote. Sens. Lett., 2023
2022
Analyzing the Saturation of Growing Stem Volume Based on ZY-3 Stereo and Multispectral Images in Planted Coniferous Forest.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022
2021
A Novel Method for Estimating Spatial Distribution of Forest Above-Ground Biomass Based on Multispectral Fusion Data and Ensemble Learning Algorithm.
Remote. Sens., 2021
Coniferous Plantations Growing Stock Volume Estimation Using Advanced Remote Sensing Algorithms and Various Fused Data.
Remote. Sens., 2021
Mapping the vegetation distribution and dynamics of a wetland using adaptive-stacking and Google Earth Engine based on multi-source remote sensing data.
Int. J. Appl. Earth Obs. Geoinformation, 2021
2020
Classification of Paddy Rice Using a Stacked Generalization Approach and the Spectral Mixture Method Based on MODIS Time Series.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2020
Estimating the Urban Fractional Vegetation Cover Using an Object-Based Mixture Analysis Method and Sentinel-2 MSI Imagery.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2020
Estimating the Growing Stem Volume of Chinese Pine and Larch Plantations based on Fused Optical Data Using an Improved Variable Screening Method and Stacking Algorithm.
Remote. Sens., 2020
Mapping wetland using the object-based stacked generalization method based on multi-temporal optical and SAR data.
Int. J. Appl. Earth Obs. Geoinformation, 2020
2019
Correction: Zhang, M., et al. Estimation of Vegetation Productivity Using a Landsat 8 Time Series in a Heavily Urbanized Area, Central China. <i>Remote Sens.</i> 2019, <i>11</i>, 133.
Remote. Sens., 2019
2018
Mapping Paddy Rice Using a Convolutional Neural Network (CNN) with Landsat 8 Datasets in the Dongting Lake Area, China.
Remote. Sens., 2018