Nengcheng Chen
Biographic Data
| ID | 7573793 |
|---|---|
| NAME | Nengcheng Chen |
| GIVEN NAMES | Nengcheng |
| FAMILY NAME | Chen |
| SIGNATURE | CHEN N |
| AFFILIATIONS | China University of Geosciences |
| ORCID | 0000-0002-3521-9972 |
| VERIFIED | Yes |
| TOTAL WORKS | 12 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 12 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Social media big data reveals how mobility reshapes human environmental exposure inequality
We compared residence-based and mobility-based measures of green exposure across 317 Chinese cities. • Residence-based measures significantly overestimate green exposure and its inequality. • When using mobility-based measures, the disparity between large and small cities decreases. • Differences in green exposure between high and low-income groups narrowed. • This is the first large-scale study incorporating human mobility data in green exposure…
A novel cross-city video-based ensemble deep learning model for air quality estimation
STPam
Analyzing and mining spatiotemporal processes refers to the extraction of geographic phenomena from spatiotemporal data and the analysis of available geographic knowledge and patterns. It finds applications in various fields such as natural disaster evolution, environmental pollution, and human behavior prediction. However, training spatiotemporal models based on big data is time-consuming, and the traditional physical models and static objects u…
Balancing Flood Control and Economic Development in Flood Detention Areas of the Yangtze River Basin
Serving as a crucial part of the Yangtze River Basin (YRB)’s flood control system, Flood Detention Areas (FDAs) are vital in mitigating large-scale floods. Urbanization has led to the development of urban FDAs, but significant losses could ensue if these FDAs are activated. With improved reservoirs and embankments, flood pressure in the middle reaches has lessened, posing challenges in balancing flood control and economic benefits. This paper pre…
Modeling Population Mobility Flows
Population mobility between cities significantly affects traffic congestion, disease spread, and societal well-being. As globalization and urbanization accelerate, understanding the dynamics of population mobility becomes increasingly important. Traditional population migration models reveal the factors influencing migration, while machine learning methods provide effective tools for creating data-driven models to handle the nonlinear relationshi…
Applicability Analysis and Ensemble Application of Bert with TF-IDF, TextRank, MMR, and LDA for Topic Classification Based on Flood-Related VGI
Volunteered geographic information (VGI) plays an increasingly crucial role in flash floods. However, topic classification and spatiotemporal analysis are complicated by the various expressions and lengths of social media textual data. This paper conducted applicability analysis on bidirectional encoder representation from transformers (BERT) and four traditional methods, TextRank, term frequency–inverse document frequency (TF-IDF), maximal margi…
Spatiotemporal evolution of carbon balance based on the enhanced two-step floating catchment area (E2SFCA) method in the Yangtze River Economic Belt, China
City2vec
PM2.5 Estimation and Spatial-Temporal Pattern Analysis Based on the Modified Support Vector Regression Model and the 1 km Resolution Maiac AOD in Hubei, China
The satellite-retrieved Aerosol Optical Depth (AOD) is widely used to estimate the concentrations and analyze the spatiotemporal pattern of Particulate Matter that is less than or equal to 2.5 microns (PM2.5), also providing a way for the related research of air pollution. Many studies generated PM2.5 concentration networks with resolutions of 3 km or 10 km. However, the relatively coarse resolution of the satellite AOD products make it difficult…
Ke-CNN
Integrating spatial nonstationarity into SLEUTH for urban growth modeling
A New Geo-Propagation Model of Event Evolution Chain Based on Public Opinion and Epidemic Coupling
The online public opinion is the sum of public views, attitudes and emotions spread on major public health emergencies through the Internet, which maps out the scope of influence and the disaster situation of public health events in real space. Based on the multi-source data of COVID-19 in the context of a global pandemic, this paper analyzes the propagation rules of disasters in the coupling of the spatial dimension of geographic reality and the…
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Integrating spatial nonstationarity into SLEUTH for urban growth modeling
A New Geo-Propagation Model of Event Evolution Chain Based on Public Opinion and Epidemic Coupling
The online public opinion is the sum of public views, attitudes and emotions spread on major public health emergencies through the Internet, which maps out the scope of influence and the disaster situation of public health events in real space. Based on the multi-source data of COVID-19 in the context of a global pandemic, this paper analyzes the propagation rules of disasters in the coupling of the spatial dimension of geographic reality and the…
PM2.5 Estimation and Spatial-Temporal Pattern Analysis Based on the Modified Support Vector Regression Model and the 1 km Resolution Maiac AOD in Hubei, China
The satellite-retrieved Aerosol Optical Depth (AOD) is widely used to estimate the concentrations and analyze the spatiotemporal pattern of Particulate Matter that is less than or equal to 2.5 microns (PM2.5), also providing a way for the related research of air pollution. Many studies generated PM2.5 concentration networks with resolutions of 3 km or 10 km. However, the relatively coarse resolution of the satellite AOD products make it difficult…
Ke-CNN
City2vec
Applicability Analysis and Ensemble Application of Bert with TF-IDF, TextRank, MMR, and LDA for Topic Classification Based on Flood-Related VGI
Volunteered geographic information (VGI) plays an increasingly crucial role in flash floods. However, topic classification and spatiotemporal analysis are complicated by the various expressions and lengths of social media textual data. This paper conducted applicability analysis on bidirectional encoder representation from transformers (BERT) and four traditional methods, TextRank, term frequency–inverse document frequency (TF-IDF), maximal margi…
Spatiotemporal evolution of carbon balance based on the enhanced two-step floating catchment area (E2SFCA) method in the Yangtze River Economic Belt, China
Balancing Flood Control and Economic Development in Flood Detention Areas of the Yangtze River Basin
Serving as a crucial part of the Yangtze River Basin (YRB)’s flood control system, Flood Detention Areas (FDAs) are vital in mitigating large-scale floods. Urbanization has led to the development of urban FDAs, but significant losses could ensue if these FDAs are activated. With improved reservoirs and embankments, flood pressure in the middle reaches has lessened, posing challenges in balancing flood control and economic benefits. This paper pre…
Modeling Population Mobility Flows
Population mobility between cities significantly affects traffic congestion, disease spread, and societal well-being. As globalization and urbanization accelerate, understanding the dynamics of population mobility becomes increasingly important. Traditional population migration models reveal the factors influencing migration, while machine learning methods provide effective tools for creating data-driven models to handle the nonlinear relationshi…
STPam
Analyzing and mining spatiotemporal processes refers to the extraction of geographic phenomena from spatiotemporal data and the analysis of available geographic knowledge and patterns. It finds applications in various fields such as natural disaster evolution, environmental pollution, and human behavior prediction. However, training spatiotemporal models based on big data is time-consuming, and the traditional physical models and static objects u…
Social media big data reveals how mobility reshapes human environmental exposure inequality
We compared residence-based and mobility-based measures of green exposure across 317 Chinese cities. • Residence-based measures significantly overestimate green exposure and its inequality. • When using mobility-based measures, the disparity between large and small cities decreases. • Differences in green exposure between high and low-income groups narrowed. • This is the first large-scale study incorporating human mobility data in green exposure…
A novel cross-city video-based ensemble deep learning model for air quality estimation
Computer Science (8 works) · Geography (7 works) · Environmental Science (4 works) · Artificial Intelligence (3 works) · Data science (3 works) · Economic geography (3 works) · Economics (3 works) · Human Mobility and Location-Based Analysis (3 works) · Population (3 works) · Social media (3 works)