Guiying Li
Orcid: 0000-0001-7198-4607Affiliations:
- Fujian Normal University, Fuzhou, Fujian, China
According to our database1,
Guiying Li
authored at least 14 papers
between 2014 and 2025.
Collaborative distances:
Collaborative distances:
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Bibliography
2025
Vegetation classification in a subtropical region with Sentinel-2 time series data and deep learning.
Geo spatial Inf. Sci., January, 2025
2024
Examining the Impact of Topography and Vegetation on Existing Forest Canopy Height Products from ICESat-2 ATLAS/GEDI Data.
Remote. Sens., October, 2024
A comparative analysis of grid-based and object-based modeling approaches for poplar forest growing stock volume estimation in plain regions using airborne LiDAR data.
Geo spatial Inf. Sci., September, 2024
Examining the Effects of Soil and Water Conservation Measures on Patterns and Magnitudes of Vegetation Cover Change in a Subtropical Region Using Time Series Landsat Imagery.
Remote. Sens., February, 2024
Mapping Forest Carbon Stock Distribution in a Subtropical Region with the Integration of Airborne Lidar and Sentinel-2 Data.
Remote. Sens., 2024
2020
Examining the Roles of Spectral, Spatial, and Topographic Features in Improving Land-Cover and Forest Classifications in a Subtropical Region.
Remote. Sens., 2020
Modeling Forest Aboveground Carbon Density in the Brazilian Amazon with Integration of MODIS and Airborne LiDAR Data.
Remote. Sens., 2020
Stratification-Based Forest Aboveground Biomass Estimation in a Subtropical Region Using Airborne Lidar Data.
Remote. Sens., 2020
2019
Classification of Land Cover, Forest, and Tree Species Classes with ZiYuan-3 Multispectral and Stereo Data.
Remote. Sens., 2019
Integration of ZiYuan-3 Multispectral and Stereo Data for Modeling Aboveground Biomass of Larch Plantations in North China.
Remote. Sens., 2019
2018
Examining Spatial Patterns of Urban Distribution and Impacts of Physical Conditions on Urbanization in Coastal and Inland Metropoles.
Remote. Sens., 2018
Comparative Analysis of Modeling Algorithms for Forest Aboveground Biomass Estimation in a Subtropical Region.
Remote. Sens., 2018
2016
A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems.
Int. J. Digit. Earth, 2016
2014
Int. J. Digit. Earth, 2014