Jay Gao

9.0k total citations · 2 hit papers
141 papers, 6.8k citations indexed

About

Jay Gao is a scholar working on Ecology, Global and Planetary Change and Atmospheric Science. According to data from OpenAlex, Jay Gao has authored 141 papers receiving a total of 6.8k indexed citations (citations by other indexed papers that have themselves been cited), including 64 papers in Ecology, 61 papers in Global and Planetary Change and 47 papers in Atmospheric Science. Recurrent topics in Jay Gao's work include Land Use and Ecosystem Services (39 papers), Remote Sensing in Agriculture (29 papers) and Coastal wetland ecosystem dynamics (21 papers). Jay Gao is often cited by papers focused on Land Use and Ecosystem Services (39 papers), Remote Sensing in Agriculture (29 papers) and Coastal wetland ecosystem dynamics (21 papers). Jay Gao collaborates with scholars based in New Zealand, China and Australia. Jay Gao's co-authors include Yong Zha, Shaoxiang Ni, Yansui Liu, Fenghe Wang, Xilai Li, Gary Brierley, Tingting Xu, Yun Yang, Yan Qiao and Giovanni Coco and has published in prestigious journals such as Environmental Science & Technology, The Science of The Total Environment and Remote Sensing of Environment.

In The Last Decade

Jay Gao

137 papers receiving 6.5k citations

Hit Papers

Use of normalized difference built-up index in automatica... 2003 2026 2010 2018 2003 2024 500 1000 1.5k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jay Gao New Zealand 37 3.0k 2.4k 2.0k 1.6k 925 141 6.8k
Xiao‐Peng Song United States 38 4.3k 1.4× 3.1k 1.3× 1.7k 0.8× 1.1k 0.7× 654 0.7× 80 7.5k
V. K. Dadhwal India 43 4.0k 1.3× 2.7k 1.1× 1.9k 0.9× 1.7k 1.0× 865 0.9× 341 7.5k
Heiko Balzter United Kingdom 41 3.1k 1.0× 2.5k 1.1× 2.8k 1.4× 1.1k 0.7× 551 0.6× 182 6.4k
Dafang Zhuang China 37 3.6k 1.2× 2.5k 1.1× 1.4k 0.7× 1.5k 1.0× 683 0.7× 151 7.1k
Nicholas Clinton United States 37 3.1k 1.0× 2.7k 1.1× 1.7k 0.8× 1.1k 0.7× 356 0.4× 64 5.5k
Aqil Tariq United States 45 2.7k 0.9× 1.5k 0.6× 1.8k 0.9× 1.2k 0.7× 571 0.6× 229 5.6k
Claudia Kuenzer Germany 61 4.9k 1.6× 4.2k 1.8× 2.2k 1.1× 2.7k 1.7× 1.1k 1.2× 210 11.3k
Yuanwei Qin United States 45 6.3k 2.1× 5.2k 2.2× 2.3k 1.1× 2.1k 1.3× 644 0.7× 112 9.3k
Conghe Song United States 47 5.5k 1.8× 3.7k 1.6× 3.2k 1.6× 1.7k 1.1× 446 0.5× 132 8.6k
Zongming Wang China 52 4.3k 1.4× 4.8k 2.0× 1.9k 1.0× 1.1k 0.7× 905 1.0× 286 8.6k

Countries citing papers authored by Jay Gao

Since Specialization
Citations

This map shows the geographic impact of Jay Gao's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jay Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay Gao more than expected).

Fields of papers citing papers by Jay Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jay Gao. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jay Gao. The network helps show where Jay Gao may publish in the future.

Co-authorship network of co-authors of Jay Gao

This figure shows the co-authorship network connecting the top 25 collaborators of Jay Gao. A scholar is included among the top collaborators of Jay Gao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jay Gao. Jay Gao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ma, Xuying, Lídia Morawska, Bin Zou, et al.. (2025). Towards compliance with the 2021 WHO air quality guidelines: A comparative analysis of PM2.5 trends in australia and china. Environment International. 198. 109378–109378. 3 indexed citations
2.
Gao, Jay, et al.. (2024). Analysis of the spatial heterogeneity of glacier melting in Tibet Autonomous Region and its influential factors using the K-means and XGBoost-SHAP algorithms. Environmental Modelling & Software. 182. 106194–106194. 13 indexed citations
3.
Gao, Jay. (2024). Quantitative Remote Sensing. 2 indexed citations
4.
Ma, Xuying, Bin Zou, Jun Deng, et al.. (2024). A comprehensive review of the development of land use regression approaches for modeling spatiotemporal variations of ambient air pollution: A perspective from 2011 to 2023. Environment International. 183. 108430–108430. 56 indexed citations breakdown →
5.
Shi, Yan, et al.. (2023). Spatiotemporal Variability of Alpine Meadow Aboveground Biomass and Sustainable Grazing in Light of Climate Warming. Rangeland Ecology & Management. 90. 64–77. 3 indexed citations
6.
Wang, Yicong, et al.. (2022). Health assessment of plantations based on LiDAR canopy spatial structure parameters. International Journal of Digital Earth. 15(1). 712–729. 16 indexed citations
7.
Brierley, Gary, Xilai Li, Kirstie Fryirs, et al.. (2022). Degradation and recovery of alpine meadow catenas in the source zone of the Yellow River, Western China. Journal of Mountain Science. 19(9). 2487–2505. 8 indexed citations
8.
Li, Xilai, et al.. (2021). Influences of pika and simulated grazing disturbances on bare patches of alpine meadow in the Yellow River Source Zone. Journal of Mountain Science. 18(5). 1307–1320. 10 indexed citations
9.
Gao, Jay, et al.. (2021). Phenology-based delineation of irrigated and rain-fed paddy fields with Sentinel-2 imagery in Google Earth Engine. Geo-spatial Information Science. 24(4). 695–710. 18 indexed citations
11.
Shi, Yan, et al.. (2021). Improved Estimation of Aboveground Biomass of Disturbed Grassland through Including Bare Ground and Grazing Intensity. Remote Sensing. 13(11). 2105–2105. 18 indexed citations
13.
Gao, Jay, et al.. (2021). Effects of the hummock–depression microhabitat on plant communities of alpine marshy meadows in the Yellow River Source Zone, China. Journal of Plant Ecology. 15(1). 111–128. 7 indexed citations
14.
Ma, Xuying, Ian Longley, Jay Gao, & Jennifer Salmond. (2020). Evaluating the Effect of Ambient Concentrations, Route Choices, and Environmental (in)Justice on Students’ Dose of Ambient NO2 While Walking to School at Population Scales. Environmental Science & Technology. 54(20). 12908–12919. 17 indexed citations
15.
Ma, Xuying, et al.. (2019). A site-optimised multi-scale GIS based land use regression model for simulating local scale patterns in air pollution. The Science of The Total Environment. 685. 134–149. 48 indexed citations
16.
Li, Xilai, Jay Gao, & Jing Zhang. (2018). A topographic perspective on the distribution of degraded meadows and their changes on the Qinghai‐Tibet Plateau, West China. Land Degradation and Development. 29(6). 1574–1582. 22 indexed citations
17.
Yang, Juan, Jay Gao, Alan Cheung, et al.. (2013). Vegetation and sediment characteristics in an expanding mangrove forest in New Zealand. Estuarine Coastal and Shelf Science. 134. 11–18. 35 indexed citations
18.
Gao, Jay. (2002). Integration of GPS with remote sensing and GIS: Reality and prospect. Photogrammetric Engineering & Remote Sensing. 68(5). 447–454. 30 indexed citations
19.
Gao, Jay. (2001). Non-differential GPS as an alternative source of planimetric control for rectifying satellite imagery. Photogrammetric Engineering & Remote Sensing. 67(1). 49–56. 11 indexed citations
20.
Gao, Jay, et al.. (1997). The role of spatial resolution in quantifying SSC from airborne remotely sensed data. Photogrammetric Engineering & Remote Sensing. 63(3). 267–271. 4 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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