Jinwen Xu
Biographic Data
| ID | 4265833 |
|---|---|
| NAME | Jinwen Xu |
| GIVEN NAMES | Jinwen |
| FAMILY NAME | Xu |
| SIGNATURE | XU J |
| AFFILIATIONS | University of Hawaiʻi at Mānoa |
| ORCID | 0000-0001-9663-5737 |
| VERIFIED | Yes |
| TOTAL WORKS | 10 |
| TOTAL CITATIONS | 21 |
| AUTHOR COUNT | 10 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2016 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 2 |
Erchen Decoction and its active flavonoids hesperidin and quercetin alleviate high-fat diet-induced neuroinflammation by targeting HK2-mediated microglial glycolysis
Map Reading and Analysis with GPT-4V(ision)
In late 2023, the image-reading capability added to a Generative Pre-trained Transformer (GPT) framework provided the opportunity to potentially revolutionize the way we view and understand geographic maps, the core component of cartography, geography, and spatial data science. In this study, we explore reading and analyzing maps with the latest version of GPT-4-vision-preview (GPT-4V), to fully evaluate its advantages and disadvantages in compar…
Analysis of the evolution characteristics of international ICT services trade based on complex network
Environmental justice implications of flood risk in the contiguous United States – a spatiotemporal assessment of flood exposure change from 2001 to 2019
Flood hazard is one of America's most frequent and expensive natural hazards and causes enormous economic losses in the United States every year. Flood hazards disproportionately affect marginalized and socioeconomically disadvantaged populations. This disproportionate flood exposure constitutes a form of environmental injustice. Few studies have undertaken a large-scale assessment of the long-term change of flood exposure. To fill this gap, this…
Mapping with ChatGPT
The emergence and rapid advancement of large language models (LLMs), represented by OpenAI’s Generative Pre-trained Transformer (GPT), has brought up new opportunities across various industries and disciplines. These cutting-edge technologies are transforming the way we interact with information, communicate, and solve complex problems. We conducted a pilot study exploring making maps with ChatGPT, a popular artificial intelligence (AI) chatbot. …
Analyzing multi-scale spatial point patterns in a pyramid modeling framework
Many spatial analysis methods suffer from the scaling issue identified as part of the Modifiable Areal Unit Problem (MAUP). This article introduces the Pyramid Model (PM), a hierarchical data framework integrating space and spatial scale in a 3D environment to support multi-scale analysis. The utility of the PM is tested in examining quadrat density and kernel density, which are commonly used measures of point patterns. The two metrics computed f…
Global rainbow distribution under current and future climates
Rainbows contribute to human wellbeing by providing an inspiring connection to nature. Because the rainbow is an atmospheric optical phenomenon that results from the refraction of sunlight by rainwater droplets, changes in precipitation and cloud cover due to anthropogenic climate forcing will alter rainbow distribution. Yet, we lack a basic understanding of the current spatial distribution of rainbows and how climate change might alter this patt…
Observing community resilience from space: Using nighttime lights to model economic disturbance and recovery pattern in natural disaster
The shapes of US cities: Revisiting the classic population density functions using crowdsourced geospatial data
The declining pattern of population density from city centres to the outskirts has been widely observed in American cities. Such a pattern reflects a trade-off between housing price/commuting cost and employment. However, most previous studies in urban population density functions are based on the Euclidean distance, and do not consider commuting cost in cities. This study provides an empirical evaluation of the classic population density functio…
How Durable are Social Norms? Immigrant Trust and Generosity in 132 Countries
How Durable are Social Norms? Immigrant Trust and Generosity in 132 Countries
The shapes of US cities: Revisiting the classic population density functions using crowdsourced geospatial data
The declining pattern of population density from city centres to the outskirts has been widely observed in American cities. Such a pattern reflects a trade-off between housing price/commuting cost and employment. However, most previous studies in urban population density functions are based on the Euclidean distance, and do not consider commuting cost in cities. This study provides an empirical evaluation of the classic population density functio…
Environmental justice implications of flood risk in the contiguous United States – a spatiotemporal assessment of flood exposure change from 2001 to 2019
Flood hazard is one of America's most frequent and expensive natural hazards and causes enormous economic losses in the United States every year. Flood hazards disproportionately affect marginalized and socioeconomically disadvantaged populations. This disproportionate flood exposure constitutes a form of environmental injustice. Few studies have undertaken a large-scale assessment of the long-term change of flood exposure. To fill this gap, this…
How Durable are Social Norms? Immigrant Trust and Generosity in 132 Countries
Observing community resilience from space: Using nighttime lights to model economic disturbance and recovery pattern in natural disaster
The shapes of US cities: Revisiting the classic population density functions using crowdsourced geospatial data
The declining pattern of population density from city centres to the outskirts has been widely observed in American cities. Such a pattern reflects a trade-off between housing price/commuting cost and employment. However, most previous studies in urban population density functions are based on the Euclidean distance, and do not consider commuting cost in cities. This study provides an empirical evaluation of the classic population density functio…
Analyzing multi-scale spatial point patterns in a pyramid modeling framework
Many spatial analysis methods suffer from the scaling issue identified as part of the Modifiable Areal Unit Problem (MAUP). This article introduces the Pyramid Model (PM), a hierarchical data framework integrating space and spatial scale in a 3D environment to support multi-scale analysis. The utility of the PM is tested in examining quadrat density and kernel density, which are commonly used measures of point patterns. The two metrics computed f…
Global rainbow distribution under current and future climates
Rainbows contribute to human wellbeing by providing an inspiring connection to nature. Because the rainbow is an atmospheric optical phenomenon that results from the refraction of sunlight by rainwater droplets, changes in precipitation and cloud cover due to anthropogenic climate forcing will alter rainbow distribution. Yet, we lack a basic understanding of the current spatial distribution of rainbows and how climate change might alter this patt…
Mapping with ChatGPT
The emergence and rapid advancement of large language models (LLMs), represented by OpenAI’s Generative Pre-trained Transformer (GPT), has brought up new opportunities across various industries and disciplines. These cutting-edge technologies are transforming the way we interact with information, communicate, and solve complex problems. We conducted a pilot study exploring making maps with ChatGPT, a popular artificial intelligence (AI) chatbot. …
Map Reading and Analysis with GPT-4V(ision)
In late 2023, the image-reading capability added to a Generative Pre-trained Transformer (GPT) framework provided the opportunity to potentially revolutionize the way we view and understand geographic maps, the core component of cartography, geography, and spatial data science. In this study, we explore reading and analyzing maps with the latest version of GPT-4-vision-preview (GPT-4V), to fully evaluate its advantages and disadvantages in compar…
Analysis of the evolution characteristics of international ICT services trade based on complex network
Environmental justice implications of flood risk in the contiguous United States – a spatiotemporal assessment of flood exposure change from 2001 to 2019
Flood hazard is one of America's most frequent and expensive natural hazards and causes enormous economic losses in the United States every year. Flood hazards disproportionately affect marginalized and socioeconomically disadvantaged populations. This disproportionate flood exposure constitutes a form of environmental injustice. Few studies have undertaken a large-scale assessment of the long-term change of flood exposure. To fill this gap, this…
Erchen Decoction and its active flavonoids hesperidin and quercetin alleviate high-fat diet-induced neuroinflammation by targeting HK2-mediated microglial glycolysis
Geography (6 works) · Cartography (4 works) · Computer Science (4 works) · Economics (3 works) · Political science (3 works) · Sociology (3 works) · Artificial Intelligence (2 works) · Data mining (2 works) · Environmental planning (2 works) · Environmental Science (2 works)