Hui Lin
Affiliations:- Research Center of Forestry Remote Sensing, Central South University of Forestry, Hunan, China
According to our database1,
Hui Lin
authored at least 34 papers
between 2007 and 2024.
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Bibliography
2024
A Novel Feature Evaluation Method in Mapping Forest AGB by Fusing Multiple Evaluation Metrics Using PolSAR Data.
IEEE Geosci. Remote. Sens. Lett., 2024
2023
Evaluating the Transferability of Spectral Variables and Prediction Models for Mapping Forest Aboveground Biomass Using Transfer Learning Methods.
Remote. Sens., November, 2023
Interpretation and Mapping Tree Crown Diameter Using Spatial Heterogeneity in Relation to the Radiative Transfer Model Extracted from GF-2 Images in Planted Boreal Forest Ecosystems.
Remote. Sens., April, 2023
Evaluating the Sensitivity of Polarimetric Features Related to Rotation Domain and Mapping Chinese Fir AGB Using Quad-Polarimetric SAR Images.
Remote. Sens., March, 2023
Mapping Forest Growing Stem Volume Using Novel Feature Evaluation Criteria Based on Spectral Saturation in Planted Chinese Fir Forest.
Remote. Sens., January, 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
Mapping Forest Stock Volume Based on Growth Characteristics of Crown Using Multi-Temporal Landsat 8 OLI and ZY-3 Stereo Images in Planted Eucalyptus Forest.
Remote. Sens., 2022
Inversion of Coniferous Forest Stock Volume Based on Backscatter and InSAR Coherence Factors of Sentinel-1 Hyper-Temporal Images and Spectral Variables of Landsat 8 OLI.
Remote. Sens., 2022
2021
A Combined Strategy of Improved Variable Selection and Ensemble Algorithm to Map the Growing Stem Volume of Planted Coniferous Forest.
Remote. Sens., 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
Mapping the Growing Stem Volume of the Coniferous Plantations in North China Using Multispectral Data from Integrated GF-2 and Sentinel-2 Images and an Optimized Feature Variable Selection Method.
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 the Planted Forest Using the General Linear Model and Time Series Quad-Polarimetric SAR Images.
Sensors, 2020
Estimating the Growing Stem Volume of Coniferous Plantations Based on Random Forest Using an Optimized Variable Selection Method.
Sensors, 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
Improving the Estimation of Forest Carbon Density in Mountainous Regions Using Topographic Correction and Landsat 8 Images.
Remote. Sens., 2019
Mapping Growing Stem Volume of Chinese Fir Plantation Using a Saturation-based Multivariate Method and Quad-polarimetric SAR Images.
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
Optimizing kNN for Mapping Vegetation Cover of Arid and Semi-Arid Areas Using Landsat Images.
Remote. Sens., 2018
Improving Selection of Spectral Variables for Vegetation Classification of East Dongting Lake, China, Using a Gaofen-1 Image.
Remote. Sens., 2018
2016
Multi-Resolution Mapping and Accuracy Assessment of Forest Carbon Density by Combining Image and Plot Data from a Nested and Clustering Sampling Design.
Remote. Sens., 2016
2015
Improvement of Forest Carbon Estimation by Integration of Regression Modeling and Spectral Unmixing of Landsat Data.
IEEE Geosci. Remote. Sens. Lett., 2015
Retrieval and Accuracy Assessment of Tree and Stand Parameters for Chinese Fir Plantation Using Terrestrial Laser Scanning.
IEEE Geosci. Remote. Sens. Lett., 2015
2013
Impacts of Plot Location Errors on Accuracy of Mapping and Scaling Up Aboveground Forest Carbon Using Sample Plot and Landsat TM Data.
IEEE Geosci. Remote. Sens. Lett., 2013
2012
Remotely sensed image intelligent interpretation based on robust segmentation and GIS system.
Proceedings of the 9th International Conference on Fuzzy Systems and Knowledge Discovery, 2012
2010
Proceedings of the Seventh International Conference on Fuzzy Systems and Knowledge Discovery, 2010
2009
Proceedings of the Sixth International Conference on Fuzzy Systems and Knowledge Discovery, 2009
2008
A SVM-Based Change Detection Method from Bi-Temporal Remote Sensing Images in Forest Area.
Proceedings of the International Workshop on Knowledge Discovery and Data Mining, 2008
2007
Design and Implementation of a High Spatial Resolution Remote Sensing Image Intelligent Interpretation System.
Data Sci. J., 2007