Quansheng Ge

Orcid: 0000-0001-8712-8565

According to our database1, Quansheng Ge authored at least 15 papers between 2005 and 2024.

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

Timeline

Legend:

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In proceedings 
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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Long-Term Dynamics of Atmospheric Sulfur Dioxide in Urban and Rural Regions of China: Urbanization and Policy Impacts.
Remote. Sens., January, 2024

Generating Urban Road Networks with Conditional Diffusion Models.
ISPRS Int. J. Geo Inf., 2024

2023
Analysis of the Winter AOD Trends over Iran from 2000 to 2020 and Associated Meteorological Effects.
Remote. Sens., February, 2023

2022
Quantifying the accuracies of six 30-m cropland datasets over China: A comparison and evaluation analysis.
Comput. Electron. Agric., 2022

Integrating climate and satellite remote sensing data for predicting county-level wheat yield in China using machine learning methods.
Int. J. Appl. Earth Obs. Geoinformation, 2022

Mapping irrigated croplands in China using a synergetic training sample generating method, machine learning classifier, and Google Earth Engine.
Int. J. Appl. Earth Obs. Geoinformation, 2022

2021
Aerosol Trends during the Dusty Season over Iran.
Remote. Sens., 2021

2019
Correction: Shang, R.; Liu, R.; Xu, M.; Liu, Y.; Dash, J.; Ge, Q. Determining the Start of the Growing Season from MODIS Data in the Indian Monsoon Region: Identifying Available Data in the Rainy Season and Modeling the Varied Vegetation Growth Trajectories, <i>Remote Sens.</i> 2018, <i>10</i>, 122.
Remote. Sens., 2019

2018
The Impact of Spatial Form of Urban Architecture on the Urban Thermal Environment: A Case Study of the Zhongshan District, Dalian, China.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2018

Determining the Start of the Growing Season from MODIS Data in the Indian Monsoon Region: Identifying Available Data in the Rainy Season and Modeling the Varied Vegetation Growth Trajectories.
Remote. Sens., 2018

Simulating Intraurban Land Use Dynamics under Multiple Scenarios Based on Fuzzy Cellular Automata: A Case Study of Jinzhou District, Dalian.
Complex., 2018

2016
Spatiotemporal Variability in Start and End of Growing Season in China Related to Climate Variability.
Remote. Sens., 2016

A Local Land Use Competition Cellular Automata Model and Its Application.
ISPRS Int. J. Geo Inf., 2016

2011
GIS-Based Assessment of Roof-Mounted Solar Energy Potential in Jiangsu, China.
Proceedings of the Second International Conference on Digital Manufacturing and Automation, 2011

2005
A case study on land use change analysis using RS and GIS in the west jilin province in China.
Proceedings of the IEEE International Geoscience & Remote Sensing Symposium, 2005


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