Haoyuan Hong: h-index, Total Citations, and Citation Map
Haoyuan Hong's h-index is 73 (95 i10-index, 19,050+ total citations across 99+ publications) according to Google Scholar as of June 2026. Haoyuan Hong is affiliated with Nanjing University of Information Science & Technology.
Haoyuan Hong is a researcher affiliated with Nanjing University of Information Science & Technology, specializing in GIS & Digital Cartography, Data Mining & Artificial Intelligence, Natural Hazard Assessment. Their work has been cited 19,050 times. This profile visualizes their global influence, highlighting strong citation networks in Australia.
Haoyuan Hong's Citation Metrics
Bibliometric impact based on 99 indexed publications.
- H-Index
- 73
- i10-Index
- 95
- Total Citations
- 19,050
- Citing Countries
- 10
As of June 2026.
Haoyuan Hong has an h-index of 73 and 19,050 total citations across 99 publications, with research cited by institutions in 10 countries.
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A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility
20171,103
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Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Haoyuan Hong's research
Haoyuan Hong is a researcher in GIS & Digital Cartography, Data Mining & Artificial Intelligence and Natural Hazard Assessment at Nanjing University of Information Science & Technology. Their work has been cited 19,050 times across 99 publications (h-index 73), according to Google Scholar.
Their most-cited work, “A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility” (2017), has accumulated 1,103 citations. Other influential works include “A comparative assessment of flood susceptibility modeling using multi-criteria decision-making analysis and machine learning methods” (2019) with 858 citations and “Modeling flood susceptibility using data-driven approaches of naïve bayes tree, alternating decision tree, and random forest methods” (2020) with 581 citations.
Citations of Haoyuan Hong's research come primarily from Australia, China and Japan, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
