Guiying Li

Orcid: 0000-0001-7198-4607

Affiliations:
  • Fujian Normal University, Fuzhou, Fujian, China


According to our database1, Guiying Li authored at least 14 papers between 2014 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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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
Methods to extract impervious surface areas from satellite images.
Int. J. Digit. Earth, 2014


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