Jing Gao

Assistant Professor of Geospatial Data Science

University of Delaware

United States

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Jing Gao is an Assistant Professor of Geospatial Data Science at the University of Delaware, USA. His research focuses on urban land dynamics, climate change implications, and advanced geospatial modeling techniques. Recent publications include studies on urban heat stress vulnerability, the impacts of population projections on urban land use, and the integration of GeoAI in addressing environmental challenges.

Articles (11)

Year:

2024

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2024

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2024

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2024

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2023

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2022

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2021

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2021

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2021

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2021

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2020

Collaborators (10)

Jesus Crespo Cuaresma

WU Vienna University of Economics and Business

AUSTRIA

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Yingjie Hu

Assistant Professor

University at Buffalo

UNITED STATES

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Bruno Martins

Associate Professor

Universidade de Lisboa Instituto Superior Técnico

PORTUGAL

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Stephen Powers

Baylor University

UNITED STATES

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Alejandro Flores

Professor

Boise State University

UNITED STATES

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Linda Shi

Assistant Professor

Cornell University

UNITED STATES

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Luis F. Rodríguez

Associate Professor

University of Illinois at Urbana-Champaign

UNITED STATES

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Johannes Scholz

Graz University of Technology (90000)

AUSTRIA

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Ryan A. McManamay

UNITED STATES

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Gengchen Mai

Assistant Professor

University of Georgia

UNITED STATES

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Jing Gao

Research Interests

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About

Articles (11)

Divergent urban land trajectories under alternative population projections within the Shared Socioeconomic Pathways

Research to Confront Climate Change Complexity: Intersectionality, Integration, and Innovative Governance

High-Resolution Modeling and Projecting Local Dynamics of Differential Vulnerability to Urban Heat Stress

Large disagreements in estimates of urban land across scales and their implications

Urban land patterns can moderate population exposures to climate extremes over the 21st century

Symbolic and subsymbolic GeoAI: Geospatial knowledge graphs and spatially explicit machine learning

Downscaling SSP-consistent global spatial urban land projections from 1/8-degree to 1-km resolution 2000–2100

Different Spatiotemporal Patterns in Global Human Population and Built‐Up Land

Double cropping and cropland expansion boost grain production in Brazil

SSP‐Based Land‐Use Change Scenarios: A Critical Uncertainty in Future Regional Climate Change Projections

Mapping global urban land for the 21st century with data-driven simulations and Shared Socioeconomic Pathways

Collaborators (10)

Jesus Crespo Cuaresma

Yingjie Hu

Bruno Martins

Stephen Powers

Alejandro Flores

Linda Shi

Luis F. Rodríguez

Johannes Scholz

Ryan A. McManamay

Gengchen Mai

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