22.8.11.1 GIS: for COVID Specific Tracking, Spread, Analysis

Chapter Contents (Back)
GIS. Covid. Medical. Health. Disease. GIS, Applications.
See also Pneumonia, Lung Analysis, Flu, COVID.

Fan, C.[Cheng], Li, Y.[Ying], Guang, J.[Jie], Li, Z.Q.[Zheng-Qiang], Elnashar, A.[Abdelrazek], Allam, M.[Mona], de Leeuw, G.[Gerrit],
The Impact of the Control Measures during the COVID-19 Outbreak on Air Pollution in China,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Nichol, J.E.[Janet E.], Bilal, M.[Muhammad], Ali, M.A.[Md. Arfan], Qiu, Z.F.[Zhong-Feng],
Air Pollution Scenario over China during COVID-19,
RS(12), No. 13, 2020, pp. xx-yy.
DOI Link 2007
BibRef

Zhang, K.[Kainan], de Leeuw, G.[Gerrit], Yang, Z.Q.A.[Zhi-Qi-Ang], Chen, X.F.[Xing-Feng], Jiao, J.S.[Jia-Shuang],
The Impacts of the COVID-19 Lockdown on Air Quality in the Guanzhong Basin, China,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Javed, Z.[Zeeshan], Wang, Y.H.[Yu-Hang], Xie, M.J.[Ming-Jie], Tanvir, A.[Aimon], Rehman, A.[Abdul], Ji, X.G.[Xiang-Guang], Xing, C.Z.[Cheng-Zhi], Shakoor, A.[Awais], Liu, C.[Cheng],
Investigating the Impacts of the COVID-19 Lockdown on Trace Gases Using Ground-Based MAX-DOAS Observations in Nanjing, China,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Peng, Z.H.[Zheng-Hong], Wang, R.[Ru], Liu, L.[Lingbo], Wu, H.[Hao],
Exploring Urban Spatial Features of COVID-19 Transmission in Wuhan Based on Social Media Data,
IJGI(9), No. 6, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Thakar, V.[Vaishnavi],
Unfolding Events in Space and Time: Geospatial Insights into COVID-19 Diffusion in Washington State during the Initial Stage of the Outbreak,
IJGI(9), No. 6, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Wang, Z.H.[Zhi-Huan], Yao, M.Y.[Meng-Yuan], Meng, C.G.[Chen-Guang], Claramunt, C.[Christophe],
Risk Assessment of the Overseas Imported COVID-19 of Ocean-Going Ships Based on AIS and Infection Data,
IJGI(9), No. 6, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Zheng, N., Du, S., Wang, J., Zhang, H., Cui, W., Kang, Z., Yang, T., Lou, B., Chi, Y., Long, H., Ma, M., Yuan, Q., Zhang, S., Zhang, D., Ye, F., Xin, J.,
Predicting COVID-19 in China Using Hybrid AI Model,
Cyber(50), No. 7, July 2020, pp. 2891-2904.
IEEE DOI 2006
Epidemics, Viruses (medical), Predictive models, Market research, Analytical models, Natural language processing, natural language processing (NLP) BibRef

Zhang, Z.J.[Zhi-Jie], Arshad, A.[Arfan], Zhang, C.R.[Chuan-Rong], Hussain, S.[Saddam], Li, W.D.[Wei-Dong],
Unprecedented Temporary Reduction in Global Air Pollution Associated with COVID-19 Forced Confinement: A Continental and City Scale Analysis,
RS(12), No. 15, 2020, pp. xx-yy.
DOI Link 2008
BibRef

Brito, P.L.[Patricia Lustosa], Kuffer, M.[Monika], Koeva, M.[Mila], Pedrassoli, J.C.[Julio Cesar], Wang, J.[Jiong], Costa, F.[Federico], Dias de Freitas, A.[Anderson],
The Spatial Dimension of COVID-19: The Potential of Earth Observation Data in Support of Slum Communities with Evidence from Brazil,
IJGI(9), No. 9, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Liu, Y.[Yanwen], He, Z.Y.[Zong-Yi], Zhou, X.[Xia],
Space-Time Variation and Spatial Differentiation of COVID-19 Confirmed Cases in Hubei Province Based on Extended GWR,
IJGI(9), No. 9, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Antoniou, V.[Varvara], Vassilakis, E.[Emmanuel], Hatzaki, M.[Maria],
Is Crowdsourcing a Reliable Method for Mass Data Acquisition? The Case of COVID-19 Spread in Greece During Spring 2020,
IJGI(9), No. 10, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Barragan, R.[Ruben], Molero, F.[Francisco], Granados-Muoz, M.J.[Mara Jos], Salvador, P.[Pedro], Pujadas, M.[Manuel], Artano, B.[Begoa],
Feasibility of Ceilometers Data to Estimate Radiative Forcing Values: Application to Different Conditions around the COVID-19 Lockdown Period,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link 2011
BibRef

Huang, J.W.[Jian-Wei], Kwan, M.P.[Mei-Po], Kan, Z.[Zihan], Wong, M.S.[Man Sing], Kwok, C.Y.T.[Coco Yin Tung], Yu, X.Y.[Xin-Yu],
Investigating the Relationship between the Built Environment and Relative Risk of COVID-19 in Hong Kong,
IJGI(9), No. 11, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Gianquintieri, L.[Lorenzo], Brovelli, M.A.[Maria Antonia], Pagliosa, A.[Andrea], Dassi, G.[Gabriele], Brambilla, P.M.[Piero Maria], Bonora, R.[Rodolfo], Sechi, G.M.[Giuseppe Maria], Caiani, E.G.[Enrico Gianluca],
Mapping Spatiotemporal Diffusion of COVID-19 in Lombardy (Italy) on the Base of Emergency Medical Services Activities,
IJGI(9), No. 11, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Huang, X.[Xiao], Li, Z.L.[Zhen-Long], Lu, J.Y.[Jun-Yu], Wang, S.C.[Si-Cheng], Wei, H.X.[Han-Xue], Chen, B.X.[Bai-Xu],
Time-Series Clustering for Home Dwell Time during COVID-19: What Can We Learn from It?,
IJGI(9), No. 11, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Edwards, C.[Chris],
Coalition of the Willing Takes Aim at COVID-19,
CACM(64), No. 1, January 2021, pp. 19-21. 2012

DOI Link COVID Data and privacy BibRef

Gan, T.[Tian], Li, W.F.[Wei-Feng], He, L.[Linghui], Li, J.[Jian],
Intracity Pandemic Risk Evaluation Using Mobile Phone Data: The Case of Shanghai during COVID-19,
IJGI(9), No. 12, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Kim, J.[Junghwan], Kwan, M.P.[Mei-Po],
An Examination of People's Privacy Concerns, Perceptions of Social Benefits, and Acceptance of COVID-19 Mitigation Measures That Harness Location Information: A Comparative Study of the U.S. and South Korea,
IJGI(10), No. 1, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Ojagh, S.[Soroush], Saeedi, S.[Sara], Liang, S.H.L.[Steve H. L.],
A Person-to-Person and Person-to-Place COVID-19 Contact Tracing System Based on OGC IndoorGML,
IJGI(10), No. 1, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Jawak, S.D.[Shridhar D.], Andersen, B.N.[Bo N.], Pohjola, V.A.[Veijo A.], Gody, .[ystein], Hbner, C.[Christiane], Jennings, I.[Inger], Ignatiuk, D.[Dariusz], Holmn, K.[Kim], Sivertsen, A.[Agnar], Hann, R.[Richard], Tmmervik, H.[Hans], Kb, A.[Andreas], Blaszczyk, M.[Malgorzata], Salzano, R.[Roberto], Luks, B.[Bartlomiej], Hgda, K.A.[Kjell Arild], Storvold, R.[Rune], Nilsen, L.[Lennart], Salvatori, R.[Rosamaria], Krishnan, K.P.[Kottekkatu Padinchati], Chatterjee, S.[Sourav], Lorentzen, D.A.[Dag A.], Erlandsson, R.[Rasmus], Lauknes, T.R.[Tom Rune], Malnes, E.[Eirik], Karlsen, S.R.[Stein Rune], Enomoto, H.[Hiroyuki], Fjraa, A.M.[Ann Mari], Zhang, J.[Jie], Marty, S.[Sabine], Nygrd, K.O.[Knut Ove], Lihavainen, H.[Heikki],
SIOS's Earth Observation (EO), Remote Sensing (RS), and Operational Activities in Response to COVID-19,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Willberg, E.[Elias], Jrv, O.[Olle], Visnen, T.[Tuomas], Toivonen, T.[Tuuli],
Escaping from Cities during the COVID-19 Crisis: Using Mobile Phone Data to Trace Mobility in Finland,
IJGI(10), No. 2, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Prez-Arnal, R.[Raquel], Conesa, D.[David], Alvarez-Napagao, S.[Sergio], Suzumura, T.[Toyotaro], Catal, M.[Mart], Alvarez-Lacalle, E.[Enrique], Garcia-Gasulla, D.[Dario],
Comparative Analysis of Geolocation Information through Mobile-Devices under Different COVID-19 Mobility Restriction Patterns in Spain,
IJGI(10), No. 2, 2021, pp. xx-yy.
DOI Link 2103
BibRef

de Oliveira, G.L.A.[Gisliany Lillian Alves], Lima, L.[Luciana], Silva, I.[Ivanovitch], Ribeiro-Dantas, M.D.[Marcel Da_Cmara], Monteiro, K.H.[Kayo Henrique], Endo, P.T.[Patricia Takako],
Evaluating Social Distancing Measures and Their Association with the Covid-19 Pandemic in South America,
IJGI(10), No. 3, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Mller, H.[Hartmut], Louwsma, M.[Marije],
The Role of Spatio-Temporal Information to Govern the COVID-19 Pandemic: A European Perspective,
IJGI(10), No. 3, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Purwanto, P.[Purwanto], Utaya, S.[Sugeng], Handoyo, B.[Budi], Bachri, S.[Syamsul], Astuti, I.S.[Ike Sari], Utomo, K.S.B.[Kresno Sastro Bangun], Aldianto, Y.E.[Yulius Eka],
Spatiotemporal Analysis of COVID-19 Spread with Emerging Hotspot Analysis and Space-Time Cube Models in East Java, Indonesia,
IJGI(10), No. 3, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Qiu, Z.F.[Zhong-Feng], Ali, M.A.[Md. Arfan], Nichol, J.E.[Janet E.], Bilal, M.[Muhammad], Tiwari, P.[Pravash], Habtemicheal, B.A.[Birhanu Asmerom], Almazroui, M.[Mansour], Mondal, S.K.[Sanjit Kumar], Mazhar, U.[Usman], Wang, Y.[Yu], Sarker, S.[Sajib], Mustafa, F.[Farhan], Rahman, M.A.[Muhammad Ashfaqur],
Spatiotemporal Investigations of Multi-Sensor Air Pollution Data over Bangladesh during COVID-19 Lockdown,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Song, Z.[Zigeng], Bai, Y.[Yan], Wang, D.F.[Di-Feng], Li, T.[Teng], He, X.Q.[Xian-Qiang],
Satellite Retrieval of Air Pollution Changes in Central and Eastern China during COVID-19 Lockdown Based on a Machine Learning Model,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Elshorbany, Y.F.[Yasin F.], Kapper, H.C.[Hannah C.], Ziemke, J.R.[Jerald R.], Parr, S.A.[Scott A.],
The Status of Air Quality in the United States During the COVID-19 Pandemic: A Remote Sensing Perspective,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
BibRef

Ibrahim, S.[Saleem], Landa, M.[Martin], Peek, O.[Ondrej], Pavelka, K.[Karel], Halounova, L.[Lena],
Space-Time Machine Learning Models to Analyze COVID-19 Pandemic Lockdown Effects on Aerosol Optical Depth over Europe,
RS(13), No. 15, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Cai, Z.N.[Zhao-Nan], Che, K.[Ke], Liu, Y.[Yi], Yang, D.X.[Dong-Xu], Liu, C.[Cheng], Yue, X.[Xu],
Decreased Anthropogenic CO2 Emissions during the COVID-19 Pandemic Estimated from FTS and MAX-DOAS Measurements at Urban Beijing,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
BibRef

Zhou, M.Q.[Min-Qiang], Jiang, J.Y.[Jing-Yi], Langerock, B.[Bavo], Dils, B.[Bart], Sha, M.K.[Mahesh Kumar], de Mazire, M.[Martine],
Change of CO Concentration Due to the COVID-19 Lockdown in China Observed by Surface and Satellite Observations,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Tanvir, A.[Aimon], Javed, Z.[Zeeshan], Jian, Z.[Zhu], Zhang, S.[Sanbao], Bilal, M.[Muhammad], Xue, R.[Ruibin], Wang, S.S.[Shan-Shan], Bin, Z.[Zhou],
Ground-Based MAX-DOAS Observations of Tropospheric NO2 and HCHO During COVID-19 Lockdown and Spring Festival Over Shanghai, China,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
BibRef

Yu, X.Y.[Xin-Yu], Wong, M.S.[Man Sing], Kwan, M.P.[Mei Po], Nichol, J.E.[Janet Elizabeth], Zhu, R.[Rui], Heo, J.[Joon], Chan, P.W.[Pak Wai], Chin, D.C.W.[David C. W.], Kwok, C.Y.T.[Coco Yin Tung], Kan, Z.[Zihan],
COVID-19 Infection and Mortality: Association with PM2.5 Concentration and Population Density: An Exploratory Study,
IJGI(10), No. 3, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Li, Q.L.[Qiu-Lun], Zhu, Q.Y.[Qing-Yang], Xu, M.[Muwu], Zhao, Y.[Yu], Narayan, K.M.V.[K. M. Venkat], Liu, Y.[Yang],
Estimating the Impact of COVID-19 on the PM2.5 Levels in China with a Satellite-Driven Machine Learning Model,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Lu, D.B.[De-Bin], Mao, W.[Wanliu], Zheng, L.[Lilin], Xiao, W.[Wu], Zhang, L.[Liang], Wei, J.[Jing],
Ambient PM2.5 Estimates and Variations during COVID-19 Pandemic in the Yangtze River Delta Using Machine Learning and Big Data,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Sun, Y.[Yeran], Huang, Y.[Ying], Yuan, K.[Ke], Chan, T.O.[Ting On], Wang, Y.[Yu],
Spatial Patterns of COVID-19 Incidence in Relation to Crime Rate Across London,
IJGI(10), No. 2, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Yang, M.J.[Meng-Jie], Chen, Z.[Zhe], Zhou, M.J.[Meng-Jie], Liang, X.J.[Xiao-Jin], Bai, Z.Y.[Zi-Yue],
The Impact of COVID-19 on Crime: A Spatial Temporal Analysis in Chicago,
IJGI(10), No. 3, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Straka, W.[William], Kondragunta, S.[Shobha], Wei, Z.G.[Zi-Gang], Zhang, H.[Hai], Miller, S.D.[Steven D.], Watts, A.[Alexander],
Examining the Economic and Environmental Impacts of COVID-19 Using Earth Observation Data,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Avtar, R.[Ram], Singh, D.[Deepak], Umarhadi, D.A.[Deha Agus], Yunus, A.P.[Ali P.], Misra, P.[Prakhar], Desai, P.N.[Pranav N.], Kouser, A.[Asma], Kurniawan, T.A.[Tonni Agustiono], Phanindra, K.[KBVN],
Impact of COVID-19 Lockdown on the Fisheries Sector: A Case Study from Three Harbors in Western India,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Yan, Y.R.[Yi-Ran], Wang, X.P.[Xing-Ping],
Global Contraction and Local Strengthening of Firms' Supply and Sales Logistics Networks in the Context of COVID-19: Evidence from the Development Zones in Weifang, China,
IJGI(10), No. 7, 2021, pp. xx-yy.
DOI Link 2108
BibRef

de Cos, O.[Olga], Castillo, V.[Valentn], Cantarero, D.[David],
Differencing the Risk of Reiterative Spatial Incidence of COVID-19 Using Space-Time 3D Bins of Geocoded Daily Cases,
IJGI(10), No. 4, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Li, W.R.[Wei-Rong], Sun, K.[Kai], Zhu, Y.Q.[Yun-Qiang], Song, J.[Jia], Yang, J.[Jie], Qian, L.[Lang], Wang, S.[Shu],
Analyzing the Research Evolution in Response to COVID-19,
IJGI(10), No. 4, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Beecham, R.[Roger], Dykes, J.[Jason], Hama, L.[Layik], Lomax, N.[Nik],
On the Use of 'Glyphmaps' for Analysing the Scale and Temporal Spread of COVID-19 Reported Cases,
IJGI(10), No. 4, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Braca, P.[Paolo], Gaglione, D.[Domenico], Marano, S.[Stefano], Millefiori, L.M.[Leonardo Maria], Willett, P.[Peter], Pattipati, K.R.[Krishna R.],
Quickest Detection of COVID-19 Pandemic Onset,
SPLetters(28), 2021, pp. 683-687.
IEEE DOI 2104
COVID-19, Pandemics, Delays, Standards, Space technology, Maximum likelihood estimation, Tools, COVID-19 pandemic, MAST, quickest detection BibRef

Jahmunah, V.[Vicnesh], Sudarshan, V.K.[Vidya K.], Oh, S.L.[Shu Lih], Gururajan, R.[Raj], Gururajan, R.[Rashmi], Zhou, X.[Xujuan], Tao, X.H.[Xiao-Hui], Faust, O.[Oliver], Ciaccio, E.J.[Edward J.], Ng, K.H.[Kwan Hoong], Acharya, U.R.[U. Rajendra],
Future IoT tools for COVID-19 contact tracing and prediction: A review of the state-of-the-science,
IJIST(31), No. 2, 2021, pp. 455-471.
DOI Link 2105
contact tracing, coronavirus disease, COVID-19, deep learning, digital tools, intelligent internet of things, wearable devices BibRef

Zhou, Z.Q.[Zhen-Qi], Xu, Z.[Zhen], Liu, A.Q.[An-Qi], Zhou, S.[Shuang], Mu, L.[Lan], Zhang, X.[Xuan],
Mapping the Accessibility of Medical Facilities of Wuhan during the COVID-19 Pandemic,
IJGI(10), No. 5, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Jiang, Y.Q.[Yu-Qin], Huang, X.[Xiao], Li, Z.L.[Zhen-Long],
Spatiotemporal Patterns of Human Mobility and Its Association with Land Use Types during COVID-19 in New York City,
IJGI(10), No. 5, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Baron, A.F.[Anne-Flore], Boulant, O.[Olivier], Panico, I.[Ivan], Vayatis, N.[Nicolas],
A Compartmental Epidemiological Model Applied to the Covid-19 Epidemic,
IPOL(11), 2021, pp. 105-119.
DOI Link 2106
Code, Epidemic Model. BibRef

Liu, L.[Lingbo], Hu, T.[Tao], Bao, S.M.[Shu-Ming], Wu, H.[Hao], Peng, Z.H.[Zheng-Hong], Wang, R.[Ru],
The Spatiotemporal Interaction Effect of COVID-19 Transmission in the United States,
IJGI(10), No. 6, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Luo, M.[Minghai], Qin, S.[Sixian], Tan, B.[Bo], Cai, M.M.[Ming-Ming], Yue, Y.[Yufeng], Xiong, Q.Q.[Qiang-Qiang],
Population Mobility and the Transmission Risk of the COVID-19 in Wuhan, China,
IJGI(10), No. 6, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Meng, Y.[Yuan], Wong, M.S.[Man Sing], Xing, H.[Hanfa], Kwan, M.P.[Mei-Po], Zhu, R.[Rui],
Yearly and Daily Relationship Assessment between Air Pollution and Early-Stage COVID-19 Incidence: Evidence from 231 Countries and Regions,
IJGI(10), No. 6, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Huang, J.W.[Jian-Wei], Kwan, M.P.[Mei-Po], Kim, J.[Junghwan],
How Culture and Sociopolitical Tensions Might Influence People's Acceptance of COVID-19 Control Measures That Use Individual-Level Georeferenced Data,
IJGI(10), No. 7, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Castro, D.A.[David Alvarez], Ford, A.[Alistair],
3D Agent-Based Model of Pedestrian Movements for Simulating COVID-19 Transmission in University Students,
IJGI(10), No. 8, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Yu, H.C.[Han-Chen], Li, J.W.[Jing-Wei], Bardin, S.[Sarah], Gu, H.Y.[Heng-Yu], Fan, C.J.[Chen-Jing],
Spatiotemporal Dynamic of COVID-19 Diffusion in China: A Dynamic Spatial Autoregressive Model Analysis,
IJGI(10), No. 8, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Huang, Z.C.[Ze-Chun],
Spatiotemporal Evolution Patterns of the COVID-19 Pandemic Using Space-Time Aggregation and Spatial Statistics: A Global Perspective,
IJGI(10), No. 8, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Carballada, A.M.[Angel Miramontes], Balsa-Barreiro, J.[Jose],
Geospatial Analysis and Mapping Strategies for Fine-Grained and Detailed COVID-19 Data with GIS,
IJGI(10), No. 9, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Zheng, A.[Anran], Wang, T.[Tao], Li, X.J.[Xiao-Juan],
Spatiotemporal Characteristics and Risk Factors of the COVID-19 Pandemic in New York State: Implication of Future Policies,
IJGI(10), No. 9, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Alamri, A.[Abdullah],
Semantic-Linked Data Ontologies for Indoor Navigation System in Response to COVID-19,
IJGI(10), No. 9, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Romeo, L.[Luca], Frontoni, E.[Emanuele],
A Unified Hierarchical XGBoost model for classifying priorities for COVID-19 vaccination campaign,
PR(121), 2022, pp. 108197.
Elsevier DOI 2109
COVID-19, Vaccination, Machine learning, XGBoost, Clinical decision support system, Model interpretability BibRef

Qiu, Q.[Qihang], Zuo, Y.[Yifan], Zhang, M.[Mu],
Can Live Streaming Save the Tourism Industry from a Pandemic? A Study of Social Media,
IJGI(10), No. 9, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Dash, S.[Sujata], Chakraborty, C.[Chinmay], Giri, S.K.[Sourav K.], Pani, S.K.[Subhendu Kumar],
Intelligent computing on time-series data analysis and prediction of COVID-19 pandemics,
PRL(151), 2021, pp. 69-75.
Elsevier DOI 2110
Facebook Prophet Model, Changepoints, Infectious Disease, Pandemics, Logistic growth function, High Incidence, Additive model BibRef

Ma, Y.L.[Yan-Li], Li, Z.H.[Zhong-Hua], Gou, J.X.[Ji-Xiang], Ding, L.H.[Li-Hua], Yang, D.[Dong], Feng, G.[Guiliang],
Adoption of improved neural network blade pattern recognition in prevention and control of corona virus disease-19 pandemic,
PRL(151), 2021, pp. 275-280.
Elsevier DOI 2110
Improved neural network blade model, Corona virus disease (COVID)-19, Artificial intelligence, Neural network model BibRef

Gao, Y.[Yu], Sun, D.Q.[Dong-Qi], Zhang, J.X.[Jing-Xiang],
Study on the Impact of the COVID-19 Pandemic on the Spatial Behavior of Urban Tourists Based on Commentary Big Data: A Case Study of Nanjing, China,
IJGI(10), No. 10, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Ren, H.[Hui], Wang, P.X.[Pei-Xiao], Guo, W.[Wei], Zhu, X.Y.[Xin-Yan],
Exploring the Spatiotemporal Characteristics of COVID-19 Infections among Healthcare Workers: A Multi-Scale Perspective,
IJGI(10), No. 10, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Alemdar, K.D.[Kadir Diler], Kaya, .[mer], odur, M.Y.[Muhammed Yasin], Campisi, T.[Tiziana], Tesoriere, G.[Giovanni],
Accessibility of Vaccination Centers in COVID-19 Outbreak Control: A GIS-Based Multi-Criteria Decision Making Approach,
IJGI(10), No. 10, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Deshpande, G.[Gauri], Batliner, A.[Anton], Schuller, B.W.[Bjrn W.],
AI-Based human audio processing for COVID-19: A comprehensive overview,
PR(122), 2022, pp. 108289.
Elsevier DOI 2112
COVID-19, Digital health, Audio processing, Computational paralinguistics BibRef

Hasaninasab, M.[Mehdi], Khansari, M.[Mohammad],
Efficient COVID-19 testing via contextual model based compressive sensing,
PR(122), 2022, pp. 108253.
Elsevier DOI 2112
COVID-19, Graph signal model, Group testing, Model-based compressive sensing BibRef

Das, M.[Manob], Das, A.[Arijit], Pereira, P.[Paulo], Mandal, A.[Asish],
Mapping the Impact of COVID-19 Lockdown on Urban Surface Ecological Status (USES): A Case Study of Kolkata Metropolitan Area (KMA), India,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112
BibRef

He, B.[Bin], Yan, F.Q.[Feng-Qin], Yu, H.[Hao], Su, F.Z.[Fen-Zhen], Lyne, V.[Vincent], Cui, Y.K.[Yi-Kun], Kang, L.[Lu], Wu, W.Z.[Wen-Zhou],
Global Fisheries Responses to Culture, Policy and COVID-19 from 2017 to 2020,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Alahmadi, M.[Mohammed], Mansour, S.[Shawky], Dasgupta, N.[Nataraj], Abulibdeh, A.[Ammar], Atkinson, P.M.[Peter M.], Martin, D.J.[David J.],
Using Daily Nighttime Lights to Monitor Spatiotemporal Patterns of Human Lifestyle under COVID-19: The Case of Saudi Arabia,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Amen, B.[Bakhtiar], Faiz, S.[Syahirul], Do, T.T.[Thanh-Toan],
Big data directed acyclic graph model for real-time COVID-19 twitter stream detection,
PR(123), 2022, pp. 108404.
Elsevier DOI 2112
Anomaly detection, Big data, COVID-19, Directed acyclic graph, Event stream BibRef

Werner, P.A.[Piotr A.], Skrynyk, O.[Oleh], Porczek, M.[Mariusz], Szczepankowska-Bednarek, U.[Urszula], Olszewski, R.[Robert], Kesik-Brodacka, M.[Malgorzta],
The Effects of Climate and Bioclimate on COVID-19 Cases in Poland,
RS(13), No. 23, 2021, pp. xx-yy.
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Ding, C.C.[Cai-Chang], Chen, Y.Q.[Yi-Qin], Liu, Z.Y.[Zhi-Yuan], Liu, T.Y.[Tian-Yin],
Prediction on transmission trajectory of COVID-19 based on particle swarm algorithm,
PRL(152), 2021, pp. 70-78.
Elsevier DOI 2112
Particle swarm optimization, Susceptible exposed infected recovered model, Prediction of infectious disease BibRef

Liang, Q.[Qin], Hu, C.[Chunchun], Chen, S.[Si],
Evaluation of the Optimal Topic Classification for Social Media Data Combined with Text Semantics: A Case Study of Public Opinion Analysis Related to COVID-19 with Microblogs,
IJGI(10), No. 12, 2021, pp. xx-yy.
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Wu, J.S.[Jian-Sheng], Qian, Y.[Yun], Wang, Y.[Yuan], Wang, N.[Na],
Analyzing the Contribution of Human Mobility to Changes in Air Pollutants: Insights from the COVID-19 Lockdown in Wuhan,
IJGI(10), No. 12, 2021, pp. xx-yy.
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Guo, X.X.[Xiao-Xiang], Xiong, N.N.[Neal N.], Wang, H.Y.[Hai-Yan], Ren, J.L.[Jing-Li],
Design and Analysis of a Prediction System About Influenza-Like Illness From the Latent Temporal and Spatial Information,
SMCS(52), No. 1, January 2022, pp. 66-77.
IEEE DOI 2112
Mathematical model, Predictive models, Data models, Internet, Diseases, Market research, Analytical models, multivariate regression BibRef

Airoldi, C.[Chiara], Bertolotti, M.[Marinella], Rowinski, M.[Maria], Betti, M.[Marta], Pecere, A.[Alessandro], Sarro, A.[Andrea], Franceschetti, G.[Genny], Pacileo, G.[Guglielmo], Maconi, A.[Antonio], Ferrante, D.[Daniela],
Georeferencing of COVID-19 Positive Nasopharyngeal Swabs to Support Emergency Management in an Area of Northern Italy,
IJGI(11), No. 1, 2022, pp. xx-yy.
DOI Link 2201
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Gopalakrishnan, S.[Sathyanarayanan], Sridharan, S.[Supriya], Nayak, S.R.[Soumya Ranjan], Nayak, J.[Janmenjoy], Venkataraman, S.[Swaminathan],
Central hubs prediction for bio networks by directed hypergraph: GA with validation to COVID-19 PPI,
PRL(153), 2022, pp. 246-253.
Elsevier DOI 2201
Directed hypergraph, Centrality measures, Degree centrality, Strong tie, Weak tie, Genetic algorithm, COVID-19 BibRef

Malarvizhi, A.S.[Anusha Srirenganathan], Liu, Q.[Qian], Sha, D.[Dexuan], Lan, H.[Hai], Yang, C.[Chaowei],
An Open-Source Workflow for Spatiotemporal Studies with COVID-19 as an Example,
IJGI(11), No. 1, 2022, pp. xx-yy.
DOI Link 2201
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Chen, M.J.[Mei-Jie], Chen, Y.M.[Yu-Min], Wilson, J.P.[John P.], Tan, H.Y.[Huang-Yuan], Chu, T.Y.[Tian-You],
Using an Eigenvector Spatial Filtering-Based Spatially Varying Coefficient Model to Analyze the Spatial Heterogeneity of COVID-19 and Its Influencing Factors in Mainland China,
IJGI(11), No. 1, 2022, pp. xx-yy.
DOI Link 2201
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Yao, J.Q.[Jia-Qi], Zhai, H.R.[Hao-Ran], Yang, X.M.[Xiao-Meng], Wen, Z.[Zhen], Wu, S.Q.[Shu-Qi], Zhu, H.[Hong], Tang, X.M.[Xin-Ming],
Spatiotemporal Variations of Aerosols in China during the COVID-19 Pandemic Lockdown,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
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Pnek, J.[Jir], Falco, E.[Enzo], Lysek, J.[Jakub],
The COVID-19 Crisis and the Case for Online GeoParticipation in Spatial Planning,
IJGI(11), No. 2, 2022, pp. xx-yy.
DOI Link 2202
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Guo, Z.J.[Zi-Jian], Liu, X.[Xintao], Zhao, P.X.[Peng-Xiang],
A Vector Field Approach to Estimating Environmental Exposure Using Human Activity Data,
IJGI(11), No. 2, 2022, pp. xx-yy.
DOI Link 2202
Total exposure based on mobility. BibRef

Werner, P.A.[Piotr A.], Kesik-Brodacka, M.[Malgorzata], Nowak, K.[Karolina], Olszewski, R.[Robert], Kaleta, M.[Mariusz], Liebers, D.T.[David T.],
Modeling the Spatial and Temporal Spread of COVID-19 in Poland Based on a Spatial Interaction Model,
IJGI(11), No. 3, 2022, pp. xx-yy.
DOI Link 2204
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Ma, J.F.[Jian-Fang], Zhu, H.H.[Hai-Hong], Li, P.[Peng], Liu, C.C.[Cheng-Cheng], Li, F.[Feng], Luo, Z.W.[Zhen-Wei], Zhang, M.[Meihui], Li, L.[Lin],
Spatial Patterns of the Spread of COVID-19 in Singapore and the Influencing Factors,
IJGI(11), No. 3, 2022, pp. xx-yy.
DOI Link 2204
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Sarkar, S.[Shuchismita], Zhu, X.[Xuwen],
Multiple change point clustering of count processes with application to California COVID data,
PRL(157), 2022, pp. 83-89.
Elsevier DOI 2205
Finite mixture modeling, Count process, Multiple change point estimation, EM algorithm BibRef

MacTavish, M.[Mia], Wecker, L.[Lakin], Samavati, F.[Faramarz],
Perspective Charts in a Multi-Foci Globe-Based Visualization of COVID-19 Data,
IJGI(11), No. 4, 2022, pp. xx-yy.
DOI Link 2205
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Luo, Z.W.[Zhen-Wei], Li, L.[Lin], Ma, J.[Jianfang], Tang, Z.[Zhuo], Shen, H.[Hang], Zhu, H.[Haihong], Wu, B.[Bin],
Moderating Effect of a Cross-Level Social Distancing Policy on the Disparity of COVID-19 Transmission in the United States,
IJGI(11), No. 4, 2022, pp. xx-yy.
DOI Link 2205
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Hu, Z.Y.[Zhi-Yuan], Jin, Q.[Qinjian], Ma, Y.Y.[Yuan-Yuan], Ji, Z.[Zhenming], Zhu, X.[Xian], Dong, W.J.[Wen-Jie],
How Does COVID-19 Lockdown Impact Air Quality in India?,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link 2205
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Cianciosi, A.[Alessandra], Caval, S.[Saa], Calaon, D.[Diego], Seetah, K.[Krish],
Integrated Remote Sensing to Assess Disease Control: Evidence from Flat Island Quarantine Station, Mauritius,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link 2205
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Zarro, C.[Chiara], Cerra, D.[Daniele], Auer, S.[Stefan], Ullo, S.L.[Silvia Liberata], Reinartz, P.[Peter],
Urban Sprawl and COVID-19 Impact Analysis by Integrating Deep Learning with Google Earth Engine,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
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Liu, Z.M.[Zhi-Min], Jiang, Z.[Zuodong], Kip, G.[Geoffrey], Snigdha, K.[Kirti], Xu, J.[Jennings], Wu, X.Y.[Xiao-Ying], Khan, N.[Najat], Schultz, T.[Timothy],
An infodemiological framework for tracking the spread of SARS-CoV-2 using integrated public data,
PRL(158), 2022, pp. 133-140.
Elsevier DOI 2205
Infodemiology, News mining, Word2Vec, Signal burst model, Google trends, Prophet model BibRef

Aturinde, A.[Augustus], Mansourian, A.[Ali],
Space: Time Surveillance of COVID-19 Seasonal Clusters: A Case of Sweden,
IJGI(11), No. 5, 2022, pp. xx-yy.
DOI Link 2206
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Fall, S.[Souleymane], Abdalla, E.[Ehsan], Quansah, J.[Joseph], Franklin, M.J.[Meghan J.], Whaley-Omidire, T.[Timmera],
County-Level Assessment of Vulnerability to COVID-19 in Alabama,
IJGI(11), No. 5, 2022, pp. xx-yy.
DOI Link 2206
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Luo, Y.[Yuhao], Zhang, H.J.[Heng-Jing], Liu, H.C.[Heng-Chang],
Towards Fast and Accurate Intimate Contact Recognition through Video Analysis,
IPTA22(1-6)
IEEE DOI 2206
COVID-19, Image recognition, Costs, Databases, Human factors, Cameras, Social factors, Contact Tracing, Distance Detection, Covid-19 BibRef

Han, X.[Xuehua], Wang, J.[Juanle],
Modelling and Analyzing the Semantic Evolution of Social Media User Behaviors during Disaster Events: A Case Study of COVID-19,
IJGI(11), No. 7, 2022, pp. xx-yy.
DOI Link 2208
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Spadon, G.[Gabriel], Hong, S.[Shenda], Brandoli, B.[Bruno], Matwin, S.[Stan], Rodrigues-Jr, J.F.[Jose F.], Sun, J.[Jimeng],
Pay Attention to Evolution: Time Series Forecasting With Deep Graph-Evolution Learning,
PAMI(44), No. 9, September 2022, pp. 5368-5384.
IEEE DOI 2208
Forecasting, Time series analysis, COVID-19, Predictive models, Evolution (biology), Sun, Recurrent neural networks, Time series, representation learning BibRef

Jardim de Figueiredo, C.J.[Ciro Jos], de Miranda Mota, C.M.[Caroline Maria], Dias de Arajo, K.G.[Kaliane Gabriele], Ferreira Rosa, A.G.[Amanda Gadelha], Gomes de Souza, A.P.[Arthur Pimentel],
Measuring COVID-19 Vulnerability for Northeast Brazilian Municipalities: Social, Economic, and Demographic Factors Based on Multiple Criteria and Spatial Analysis,
IJGI(11), No. 8, 2022, pp. xx-yy.
DOI Link 2209
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Tayarani-Najaran, M.H.[Mohammad-Hassan],
A Novel Ensemble Machine Learning and an Evolutionary Algorithm in Modeling the COVID-19 Epidemic and Optimizing Government Policies,
SMCS(52), No. 10, October 2022, pp. 6362-6372.
IEEE DOI 2209
Prediction algorithms, Pandemics, Uncertainty, Optimization, Predictive models, COVID-19, Neural networks, Ensemble learning, policy making BibRef

Ak, .[igdem], Chitsazan, A.D.[Alex D.], Gnen, M.[Mehmet], Etzioni, R.[Ruth], Grossberg, A.J.[Aaron J.],
Spatial Prediction of COVID-19 Pandemic Dynamics in the United States,
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Sarwar Uddin, M.Y.[Md Yusuf], Rafiq, R.[Rezwana],
Characterizing pandemic waves: A latent class analysis of COVID-19 spread across US counties,
PRL(162), 2022, pp. 31-39.
Elsevier DOI 2210
COVID-19 pandemic, Pandemic waves, Spread patterns, Latent class analysis, Human mobility BibRef

Zandavi, S.M.[Seid Miad], Rashidi, T.H.[Taha Hossein], Vafaee, F.[Fatemeh],
Dynamic Hybrid Model to Forecast the Spread of COVID-19 Using LSTM and Behavioral Models Under Uncertainty,
Cyber(52), No. 11, November 2022, pp. 11977-11989.
IEEE DOI 2211
Predictive models, COVID-19, Data models, Mathematical models, Uncertainty, Logic gates, Recurrent neural networks, spread prediction BibRef

Tabasi, M.[Mohammad], Alesheikh, A.A.[Ali Asghar], Kalantari, M.[Mohsen], Babaie, E.[Elnaz], Mollalo, A.[Abolfazl],
Spatial Modeling of COVID-19 Prevalence Using Adaptive Neuro-Fuzzy Inference System,
IJGI(11), No. 10, 2022, pp. xx-yy.
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Majeed, A.[Abdul],
Technical Analysis of Contact Tracing Platform Developed by Google-Apple for Constraining the Spread of COVID-19,
IJGI(11), No. 11, 2022, pp. xx-yy.
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Tutsoy, O.[Onder],
Pharmacological, Non-Pharmacological Policies and Mutation: An Artificial Intelligence Based Multi-Dimensional Policy Making Algorithm for Controlling the Casualties of the Pandemic Diseases,
PAMI(44), No. 12, December 2022, pp. 9477-9488.
IEEE DOI 2212
Artificial intelligence, Pandemics, Vaccines, Parametric statistics, COVID-19, Computational modeling, mutant virus BibRef

Yang, X.R.[Xiao-Rui], Li, W.H.[Wei-Hong], Chen, Y.B.[Ye-Bin], Guo, Y.J.[Yun-Jian],
Construction of a COVID-19 Pandemic Situation Knowledge Graph Considering Spatial Relationships: A Case Study of Guangzhou, China,
IJGI(11), No. 11, 2022, pp. xx-yy.
DOI Link 2212
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Tampubolon, B.D., Mulyono, A.B., Isharyadi, F., Purwanto, E.H., Anggundari, W.C., Gensly,
Indicator Analysis of Smart City Standard SNI ISO 37122 Plays a Role In The Covid-19 Pandemic,
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Ismail, A., Sah, M.,
CODCA - Covid-19 Ontology for Data Collection and Analysis in E-health,
SmartCityApp21(299-305).
DOI Link 2201
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Belasri, K., Mazri, T.,
IOT in the Wake of Covid-19,
SmartCityApp21(103-107).
DOI Link 2201
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Magdy Mohamed, S., Moati, D., Elsayed, M.A.,
Implementing Smart City Strategies as an Innovative Practice for Covid-19 Pandemic in Egyptian Context,
SmartCityApp21(361-368).
DOI Link 2201
BibRef

Carey, C., Romero, J., Laefer, D.F.,
New Potree Shader Capabilities for 3d Visualization of Behaviors Near Covid-19 Rich Healthcare Facilities,
GeoInfo21(61-66).
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Sharma, S.[Sharad], Bodempudi, S.T.[Sri Teja], Reehl, A.[Aishwarya],
Real-Time Data Analytics of COVID Pandemic Using Virtual Reality,
VAMR21(106-116).
Springer DOI 2108
BibRef

Alambo, A.[Amanuel], Padhee, S.[Swati], Banerjee, T.[Tanvi], Thirunarayan, K.[Krishnaprasad],
Covid-19 and Mental Health/substance Use Disorders on Reddit: A Longitudinal Study,
CAIHA20(20-27).
Springer DOI 2103
BibRef

Ennafiri, M., Mazri, T.,
Internet of Things for Smart Healthcare: A Review on A Potential Iot Based System and Technologies to Control Covid-19 Pandemic,
SmartCityApp20(219-225).
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Comai, S., Costa, S., Ventura, S.M.[S. Mastrolembo], Vassena, G., Tagliabue, L.C., Simeone, D., Bertuzzi, E., Scurati, G.W., Ferrise, F., Ciribini, A.L.C.,
Indoor Mobile Mapping System and Crowd Simulation to Support School Reopening Because of Covid-19: A Case Study,
Gi4DM20(29-36).
DOI Link 2012
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Mezzour, G., Boudanga, Z., Benhadou, S.,
Smart Pandemic Management Through A Smart, Resilient and Flexible Decision-making System,
SmartCityApp20(285-294).
DOI Link 2012
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Oxoli, D., Jimenez, J.R.C.[J. R. Cedeno], Brovelli, M.A.,
Assessment of Sentinel-5p Performance for Ground-level Air Quality Monitoring: Preparatory Experiments Over the Covid-19 Lockdown Period,
Gi4DM20(111-116).
DOI Link 2012
BibRef

Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
GIS: Database Issues, Implementation Issues, Design .


Last update:Dec 4, 2022 at 15:58:45