On the public citation graph
Global and Geographically and Temporally Weighted Regression Models for Modeling PM2.5 in Heilongjiang, China from 2015 to 2018
0 signed · 114 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/sim.3429openalex-snapshot
An R2 statistic for fixed effects in the linear mixed model
inferredcites →https://doi.org/10.1007/s00477-013-0800-4openalex-snapshot
Time series analysis and forecasting for air pollution in small urban area: an SARIMA and factor analysis approach
inferredcites →https://doi.org/10.1007/s10661-005-9033-4openalex-snapshot
Multivariate Statistical Analysis of Meteorological and Air Pollution Data in the ‘Campo De Gibraltar’ Region, Spain
inferredcites →https://doi.org/10.1007/s10661-019-7421-4openalex-snapshot
Time-series analysis of satellite-derived fine particulate matter pollution and asthma morbidity in Jackson, MS
inferredcites →https://doi.org/10.1007/s11356-018-3763-7openalex-snapshot
PM2.5 mapping using integrated geographically temporally weighted regression (GTWR) and random sample consensus (RANSAC) models
inferredcites →https://doi.org/10.1016/j.apgeog.2012.11.003openalex-snapshot
Geographically local modeling of occurrence, count, and volume of downwood in Northeast China
inferredcites →https://doi.org/10.1016/j.apr.2018.12.013openalex-snapshot
Estimating PM2.5 concentration from satellite derived aerosol optical depth and meteorological variables using a combination model
inferredcites →https://doi.org/10.1016/j.atmosenv.2014.11.062openalex-snapshot
Modeling the spatio-temporal heterogeneity in the PM10-PM2.5 relationship
inferredcites →https://doi.org/10.1016/j.atmosres.2018.05.008openalex-snapshot
Emission-driven changes in anthropogenic aerosol concentrations in China during 1970–2010 and its implications for PM2.5 control policy
inferredcites →https://doi.org/10.1016/j.atmosres.2018.05.013openalex-snapshot
Spatial distribution of wintertime air pollution in major cities over eastern China: Relationship with the evolution of trough, ridge and synoptic system over East Asia
inferredcites →https://doi.org/10.1016/j.chemosphere.2019.01.121openalex-snapshot
An ensemble long short-term memory neural network for hourly PM2.5 concentration forecasting
inferredcites →https://doi.org/10.1016/j.compenvurbsys.2018.03.001openalex-snapshot
A geographically and temporally weighted regression model to explore the spatiotemporal influence of built environment on transit ridership
inferredcites →https://doi.org/10.1016/j.ecolmodel.2005.01.007openalex-snapshot
Spatial residual analysis of six modeling techniques
inferredcites →https://doi.org/10.1016/j.envint.2014.08.016openalex-snapshot
Spatial and temporal variations of six criteria air pollutants in 31 provincial capital cities in China during 2013–2014
inferredcites →https://doi.org/10.1016/j.envint.2018.11.075openalex-snapshot
Spatiotemporal continuous estimates of PM2.5 concentrations in China, 2000–2016: A machine learning method with inputs from satellites, chemical transport model, and ground observations
inferredcites →https://doi.org/10.1016/j.envpol.2017.11.077openalex-snapshot
Spatiotemporal characterization and mapping of PM2.5 concentrations in southern Jiangsu Province, China
inferredcites →https://doi.org/10.1016/j.envpol.2019.02.071openalex-snapshot
The relationships between PM2.5 and aerosol optical depth (AOD) in mainland China: About and behind the spatio-temporal variations
inferredcites →https://doi.org/10.1016/j.envres.2015.04.004openalex-snapshot
Relationships between meteorological parameters and criteria air pollutants in three megacities in China
inferredcites →https://doi.org/10.1016/j.envres.2017.01.029openalex-snapshot
Characterization of criteria air pollutants in Beijing during 2014–2015
inferredcites →https://doi.org/10.1016/j.jes.2018.01.017openalex-snapshot
Are current Chinese national ambient air quality standards on 24-hour averages for particulate matter sufficient to protect public health?
inferredcites →https://doi.org/10.1016/j.resconrec.2019.04.024openalex-snapshot
Temporal characteristics and forecasting of PM2.5 concentration based on historical data in Houston, USA
inferredcites →https://doi.org/10.1016/j.rse.2017.06.001openalex-snapshot
Estimating ground-level PM2.5 concentrations in Beijing using a satellite-based geographically and temporally weighted regression model
inferredcites →https://doi.org/10.1016/j.scitotenv.2017.12.102openalex-snapshot
Spatial-temporal variation characteristics of air pollution in Henan of China: Localized emission inventory, WRF/Chem simulations and potential source contribution analysis
inferredcites →https://doi.org/10.1016/j.tree.2008.10.008openalex-snapshot
Generalized linear mixed models: a practical guide for ecology and evolution
inferredcites →https://doi.org/10.1016/s0140-6736(15)00551-6openalex-snapshot
Cause-specific mortality for 240 causes in China during 1990–2013: a systematic subnational analysis for the Global Burden of Disease Study 2013
inferredcites →https://doi.org/10.1016/s2542-5196(18)30141-4openalex-snapshot
Health impact of China's Air Pollution Prevention and Control Action Plan: an analysis of national air quality monitoring and mortality data
inferredcites →https://doi.org/10.1068/a34110openalex-snapshot
A General Framework for Estimation and Inference of Geographically Weighted Regression Models: 1. Location-Specific Kernel Bandwidths and a Test for Locational Heterogeneity
inferredcites →https://doi.org/10.1080/02664763.2016.1193725openalex-snapshot
AnR2statistic for fixed effects in the generalized linear mixed model
inferredcites →https://doi.org/10.1080/13658810802672469openalex-snapshot
Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices
inferredcites →https://doi.org/10.1080/13658816.2013.878463openalex-snapshot
A geographically and temporally weighted autoregressive model with application to housing prices
inferredcites →https://doi.org/10.1093/forestscience/51.4.334openalex-snapshot
Spatial Assessment of Model Errors from Four Regression Techniques
inferredcites →https://doi.org/10.1093/forestscience/55.6.533openalex-snapshot
An Evaluation of Spatial Autocorrelation and Heterogeneity in the Residuals of Six Regression Models
inferredcites →https://doi.org/10.1109/tgrs.2019.2895351openalex-snapshot
A Geographically and Temporally Weighted Regression Model for Spatial Downscaling of MODIS Land Surface Temperatures Over Urban Heterogeneous Regions
inferredcites →https://doi.org/10.1111/gean.12071openalex-snapshot
Geographical and Temporal Weighted Regression (GTWR)
inferredcites →https://doi.org/10.1111/j.2041-210x.2012.00261.xopenalex-snapshot
A general and simple method for obtaining R 2 from generalized linear mixed‐effects models
inferredcites →https://doi.org/10.1136/thoraxjnl-2016-209687openalex-snapshot
Ambient particulate matter and COPD in China: a challenge for respiratory health research
inferredcites →https://doi.org/10.1371/journal.pone.0173612openalex-snapshot
How to reach haze control targets by air pollutants emission reduction in the Beijing-Tianjin-Hebei region of China?
inferredcites →https://doi.org/10.1371/journal.pone.0192614openalex-snapshot
Visualizing the intercity correlation of PM2.5 time series in the Beijing-Tianjin-Hebei region using ground-based air quality monitoring data
inferredcites →https://doi.org/10.18637/jss.v063.i17openalex-snapshot
GWmodel : An R Package for Exploring Spatial Heterogeneity Using Geographically Weighted Models
inferredcites →https://doi.org/10.2307/143141openalex-snapshot
A Computer Movie Simulating Urban Growth in the Detroit Region
inferredcites →https://doi.org/10.30955/gnj.000372openalex-snapshot
PM10-PM2.5 time series and fractal analysis
inferredcites →https://doi.org/10.3390/atmos8080137openalex-snapshot
Temporal and Spatial Patterns of China’s Main Air Pollutants: Years 2014 and 2015
inferredcites →https://doi.org/10.3390/ijerph110100173openalex-snapshot
Spatio-Temporal Variation of PM2.5 Concentrations and Their Relationship with Geographic and Socioeconomic Factors in China
inferredcites →https://doi.org/10.3390/ijerph14050549openalex-snapshot
An Ensemble Spatiotemporal Model for Predicting PM2.5 Concentrations
inferredcites →https://doi.org/10.3390/ijerph14121538openalex-snapshot
Spatiotemporal Variations and Driving Factors of Air Pollution in China
inferredcites →https://doi.org/10.3390/ijerph15030558openalex-snapshot
Spatial and Temporal Dynamics in Air Pollution Exposure Assessment
inferredcites →https://doi.org/10.3390/ijerph16091585openalex-snapshot
Temporal Cross-Correlations between Ambient Air Pollutants and Seasonality of Tuberculosis: A Time-Series Analysis
inferredcites →https://doi.org/10.3390/ijgi8010023openalex-snapshot
Spatiotemporal Influence of Urban Environment on Taxi Ridership Using Geographically and Temporally Weighted Regression
inferredcites →https://doi.org/10.3390/rs8030262openalex-snapshot
A Geographically and Temporally Weighted Regression Model for Ground-Level PM2.5 Estimation from Satellite-Derived 500 m Resolution AOD
inferredcites →https://doi.org/10.3390/su10082624openalex-snapshot
Economic Transition and Changing Location of Manufacturing Industry in China: A Study of the Yangtze River Delta
inferredcites →https://doi.org/10.3390/su10082772openalex-snapshot
Estimates of Daily PM2.5 Exposure in Beijing Using Spatio-Temporal Kriging Model
inferredcites →https://doi.org/10.5194/acp-17-13473-2017openalex-snapshot
Analysis of influential factors for the relationship between PM 2.5 and AOD in Beijing
inferredcites →https://doi.org/10.5849/forsci.09-123openalex-snapshot
Geographically Local Linear Mixed Models for Tree Height-Diameter Relationship
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4790418openalex-extracted
How Do 3d Urban Morphological Characteristics Spatiotemporally Affect the Urban Thermal Environment? A Case Study of San Antonio
inferred← citeshttps://doi.org/10.1007/978-981-97-9060-9_6openalex-snapshot
Geographically and Temporally Weighted Regression: Exploring Demographic Changes in Poland
inferred← citeshttps://doi.org/10.1007/s00024-026-03950-zopenalex-snapshot
Modeling and Comparative Analysis of Spatial Distribution of SO2 Concentration Using MLR and GWR Models: A Case Study of Karabük, Türkiye
inferred← citeshttps://doi.org/10.1007/s00704-024-04840-xopenalex-snapshot
Assessment of vegetation dynamics under changed climate situation using geostatistical modeling
inferred← citeshttps://doi.org/10.1007/s10668-024-05309-7openalex-snapshot
Analysis of temporal and spatial changes in urban air pollution and influencing factors from 2017 to 2021—a case study of 54 cities in the Yellow River Basin
inferred← citeshttps://doi.org/10.1007/s11356-021-15942-8openalex-snapshot
The lag effect of exposure to PM2.5 on esophageal cancer in urban-rural areas across China
inferred← citeshttps://doi.org/10.1007/s11356-022-24118-xopenalex-snapshot
Consumption-based emissions at city level in China and the spatial heterogeneity analysis of the influential factors
inferred← citeshttps://doi.org/10.1007/s11600-022-00881-wopenalex-snapshot
Multi-control spatial history of groundwater reservoirs in Pakistan using satellite-driven data
inferred← citeshttps://doi.org/10.1007/s11869-022-01179-yopenalex-snapshot
Temporal and spatial distribution mapping of particulate matter in southwest of Iran using remote sensing, GIS, and statistical techniques
inferred← citeshttps://doi.org/10.1007/s11869-023-01361-wopenalex-snapshot
Spatial and temporal distribution of absorbing aerosols in sub-Saharan Africa and GTWR model analysis
inferred← citeshttps://doi.org/10.1007/s13762-022-04681-zopenalex-snapshot
Street dust pollution by heavy metals: a geographically weighted regression approach in México City
inferred← citeshttps://doi.org/10.1007/s41324-023-00524-2openalex-snapshot
Spatiotemporal associations of mental distress with socioeconomic and environmental factors in Chicago, IL, 2015–2019
inferred← citeshttps://doi.org/10.1016/j.aap.2021.106538openalex-snapshot
Spatiotemporal analysis of crash severity on rural highway: A case study in Anhui, China
inferred← citeshttps://doi.org/10.1016/j.apr.2022.101480openalex-snapshot
Spatial interpolation of PM2.5 concentrations during holidays in south-central China considering multiple factors
inferred← citeshttps://doi.org/10.1016/j.asr.2025.06.009openalex-snapshot
Spatiotemporal dynamics of refugees and displaced persons during the Russia-Ukraine conflict: a nighttime light remote sensing perspective
inferred← citeshttps://doi.org/10.1016/j.atmosenv.2023.119956openalex-snapshot
Full-coverage estimation of PM2.5 in the Beijing-Tianjin-Hebei region by using a two-stage model
inferred← citeshttps://doi.org/10.1016/j.buildenv.2022.109037openalex-snapshot
Effects of block morphology on the surface thermal environment and the corresponding planning strategy using the geographically weighted regression model
inferred← citeshttps://doi.org/10.1016/j.buildenv.2024.111738openalex-snapshot
How do the 3D urban morphological characteristics spatiotemporally affect the urban thermal environment? A case study of San Antonio
inferred← citeshttps://doi.org/10.1016/j.envres.2025.121748openalex-snapshot
Spatiotemporal evolutions and drivers of ground-level ozone in China (2015–2020): A GTWR-Kriging approach
inferred← citeshttps://doi.org/10.1016/j.ijdrr.2025.105477openalex-snapshot
Spatio-temporal distribution estimation and analysis of post-earthquake casualties in urban areas: A case study in Chenghua District, Chengdu
inferred← citeshttps://doi.org/10.1016/j.jclepro.2025.146143openalex-snapshot
Decoding county-level air quality in China: Spatio-temporal trends, nonstationary influencing factors, and management zoning
inferred← citeshttps://doi.org/10.1016/j.jth.2022.101412openalex-snapshot
Modeling spatiotemporal associations of obesity prevalence with biking, housing cost and green spaces in Chicago, IL, USA, 2015–2017
inferred← citeshttps://doi.org/10.1016/j.jum.2025.01.008openalex-snapshot
How does urban spatial structure affect sustainable development Goal 11.7? An empirical study of 265 cities in China
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2023.162009openalex-snapshot
RETRACTED: Determining the spatial non-stationarity underlying social and natural environment in thyroid cancer in China
inferred← citeshttps://doi.org/10.1016/j.scs.2026.107417openalex-snapshot
Impacts of multidimensional urban factors on the nighttime light environment and its spatial heterogeneity
inferred← citeshttps://doi.org/10.1016/j.uclim.2026.102770openalex-snapshot
Combined effects of blue-green space on land surface temperature and PM2.5 and its spatio-temporal heterogeneity in Urumqi City, China
inferred← citeshttps://doi.org/10.1080/02626667.2024.2385003openalex-snapshot
Improving the empirical sediment yield index and identifying the spatiotemporal heterogeneity of its driving factors
inferred← citeshttps://doi.org/10.1109/icecos63900.2024.10791153openalex-snapshot
Theoretical Study to Support Proposed Framework for Spatial Modeling of PM2.5 Concentration in Pekanbaru City
inferred← citeshttps://doi.org/10.1109/tpwrd.2024.3474013openalex-snapshot
Analyzing the Effects of Lightning Strike on Distribution Transformer Failure via Geographically and Temporally Weighted Regression
inferred← citeshttps://doi.org/10.1111/tgis.70098openalex-snapshot
Leveraging User‐Generated Spatial Content for Urban Crime Analysis: A Data‐Driven Approach
inferred← citeshttps://doi.org/10.1155/sci5/6670733openalex-snapshot
Spatial Heterogeneity of Mangrove Changes and Its Local Driving Factors on the Southern Coast of Java Island, Indonesia
inferred← citeshttps://doi.org/10.1177/0958305x261474851openalex-snapshot
The path toward decarbonization in energy systems: A review on optimization, machine learning and spatiotemporal approaches
inferred← citeshttps://doi.org/10.1371/journal.pone.0288241openalex-snapshot
Spatial distribution of mortality from colorectal cancer in the southern region of Brazil
inferred← citeshttps://doi.org/10.17977/um017v28i22023p228-241openalex-snapshot
Influencing factors for the human development index in West Java using geographically and temporally weighted regression kernel functions
inferred← citeshttps://doi.org/10.18494/sam.2020.3077openalex-snapshot
Optimization of Seasonal Geographically and Temporally Weighted Regression Model for Accurate Estimation of Seasonal PM2.5 Concentrations in Beijing–Tianjin–Hebei Region
inferred← citeshttps://doi.org/10.25103/jestr.165.13openalex-snapshot
Utilizing Ridge Techniques to Combat Food Waste
inferred← citeshttps://doi.org/10.3389/fenvs.2022.893437openalex-snapshot
Analysis of the temporal and spatial pattern of air pollution and the heterogeneity of its influencing factors in central Inner Mongolia from 2016 to 2018
inferred← citeshttps://doi.org/10.3389/fenvs.2024.1509460openalex-snapshot
Exploring the altitude differentiation and influencing factors of PM2.5 and O3: a case study of the Fenwei Plain, China
inferred← citeshttps://doi.org/10.3389/fpubh.2022.954247openalex-snapshot
Government drivers of breast cancer prevention: A spatiotemporal analysis based on the association between breast cancer and macro factors
inferred← citeshttps://doi.org/10.3389/fpubh.2025.1699572openalex-snapshot
Spatiotemporal trends and driving factors of gonorrhea incidence in China: a 20-year analysis (2003–2022)
inferred← citeshttps://doi.org/10.3390/atmos13060904openalex-snapshot
A Suitable Model for Spatiotemporal Particulate Matter Concentration Prediction in Rural and Urban Landscapes, Thailand
inferred← citeshttps://doi.org/10.3390/f13020346openalex-snapshot
Research on the Temporal and Spatial Distributions of Standing Wood Carbon Storage Based on Remote Sensing Images and Local Models
inferred← citeshttps://doi.org/10.3390/f14040739openalex-snapshot
Comparison of Global and Local Poisson Models for the Number of Recruitment Trees in Natural Forests
inferred← citeshttps://doi.org/10.3390/f14101970openalex-snapshot
Estimation of Above-Ground Carbon Storage and Light Saturation Value in Northeastern China’s Natural Forests Using Different Spatial Regression Models
inferred← citeshttps://doi.org/10.3390/f16111632openalex-snapshot
A Spatiotemporal Wildfire Risk Prediction Framework Integrating Density-Based Clustering and GTWR-RFR
inferred← citeshttps://doi.org/10.3390/ijerph17041223openalex-snapshot
Who Could Not Avoid Exposure to High Levels of Residence-Based Pollution by Daily Mobility? Evidence of Air Pollution Exposure from the Perspective of the Neighborhood Effect Averaging Problem (NEAP)
inferred← citeshttps://doi.org/10.3390/ijerph17062157openalex-snapshot
Spatio-Temporal Variations of Satellite-Based PM2.5 Concentrations and Its Determinants in Xinjiang, Northwest of China
inferred← citeshttps://doi.org/10.3390/ijerph17238883openalex-snapshot
Comparison of Spatial Modelling Approaches on PM10 and NO2 Concentration Variations: A Case Study in Surabaya City, Indonesia
inferred← citeshttps://doi.org/10.3390/ijerph18137094openalex-snapshot
The Impact of Urban Development Intensity on Ecological Carrying Capacity: A Case Study of Ecologically Fragile Areas
inferred← citeshttps://doi.org/10.3390/ijerph18157931openalex-snapshot
Ingestion of GNSS-Derived ZTD and PWV for Spatial Interpolation of PM2.5 Concentration in Central and Southern China
inferred← citeshttps://doi.org/10.3390/ijerph191811627openalex-snapshot
Spatiotemporal Heterogeneity and the Key Influencing Factors of PM2.5 and PM10 in Heilongjiang, China from 2014 to 2018
inferred← citeshttps://doi.org/10.3390/ijerph20021621openalex-snapshot
The Heterogeneous Effects of Formal and Informal Environmental Regulation on Green Technology Innovation—An Empirical Study of 284 Cities in China
inferred← citeshttps://doi.org/10.3390/ijgi15010003openalex-snapshot
Spatial Patterns and Influencing Factors of Chinese Traditional Villages: A Sustainability Perspective
inferred← citeshttps://doi.org/10.3390/land14010059openalex-snapshot
How Do Temporal and Geographical Kernels Differ in Reflecting Regional Disparities? Insights from a Case Study in China
inferred← citeshttps://doi.org/10.3390/land14020319openalex-snapshot
A Village-Scale Study Regarding Landscape Evolution and Ecological Effects in a Coastal Inner Harbor
inferred← citeshttps://doi.org/10.3390/land14081627openalex-snapshot
Coupling Coordination Between Ecosystem Services and Sustainable Development Goals from a County-Level Perspective in Jiangsu Province, China
inferred← citeshttps://doi.org/10.3390/rs12162547openalex-snapshot
Regional Precipitation Model Based on Geographically and Temporally Weighted Regression Kriging
inferred← citeshttps://doi.org/10.3390/su12229357openalex-snapshot
Spatiotemporal Analysis of Environmental Factors on the Birdstrike Risk in High Plateau Airport with Multi-Scale Research
inferred← citeshttps://doi.org/10.34123/icdsos.v2021i1.202openalex-snapshot
Spatial-Temporal Analysis of Deforestation in Sumatera Island 2011-2019
inferred← citeshttps://doi.org/10.3832/ifor3705-014openalex-snapshot
A geographically weighted deep neural network model for research on the spatial distribution of the down dead wood volume in Liangshui National Nature Reserve (China)
inferred← citeshttps://doi.org/10.51847/bt9odbzg9nopenalex-snapshot
Spatiotemporal Analysis of Air Pollution Patterns and Their Environmental Impacts Using Advanced Statistical Models
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.