Qing Wang

About Qing Wang

Qing Wang, With an exceptional h-index of 5 and a recent h-index of 5 (since 2020), a distinguished researcher at Southern Illinois University Carbondale, specializes in the field of Geography, Remote Sensing, GIS.

His recent articles reflect a diverse array of research interests and contributions to the field:

Spatially characterizing land surface deformation and permafrost active layer thickness for Donnelly installation of Alaska using DInSAR and MODIS data

A CNN-based rescaling algorithm and performance analysis for spatial resolution enhancement of Landsat images

Simulating glacier mass balance in the cross-border Poiqu/Bhotekoshi Basin, China and Nepal

The potential of integrating landscape, geochemical and economical indices to analyze watershed ecological environment

Hyperspectral remote sensing applications in soil: a review

Qing Wang Information

University

Position

___

Citations(all)

149

Citations(since 2020)

145

Cited By

35

hIndex(all)

5

hIndex(since 2020)

5

i10Index(all)

5

i10Index(since 2020)

5

Email

University Profile Page

Google Scholar

Qing Wang Skills & Research Interests

Geography

Remote Sensing

GIS

Top articles of Qing Wang

Spatially characterizing land surface deformation and permafrost active layer thickness for Donnelly installation of Alaska using DInSAR and MODIS data

Cold Regions Science and Technology

2022/4/1

A CNN-based rescaling algorithm and performance analysis for spatial resolution enhancement of Landsat images

International Journal of Remote Sensing

2022/1/29

Simulating glacier mass balance in the cross-border Poiqu/Bhotekoshi Basin, China and Nepal

Journal of Water and Climate Change

2021/8/1

The potential of integrating landscape, geochemical and economical indices to analyze watershed ecological environment

Journal of hydrology

2020/4/1

Hyperspectral remote sensing applications in soil: a review

2020/1/1

See List of Professors in Qing Wang University(Southern Illinois University Carbondale)

Co-Authors

academic-engine