{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T19:53:58Z","timestamp":1774122838076,"version":"3.50.1"},"reference-count":66,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,9,17]],"date-time":"2022-09-17T00:00:00Z","timestamp":1663372800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Science and Technology Research Project of Jiangxi Provincial Department of Education","award":["GJJ170211"],"award-info":[{"award-number":["GJJ170211"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>The distribution and sentiment characteristics of tourists directly reflect the state of tourism development, and are an important reference for tourists to choose scenic areas. Sensing the tourist distributions and their sentiment variations can provide decision support for the development planning of scenic areas. In this study, we crawled tourist social media data to explore tourist distribution characteristics and the patterns of tourist sentiment variations. First, we used web crawlers to obtain social media data (tourist comment data) and the location data of China\u2019s 5A scenic areas from the Ctrip tourism platform. Second, SnowNLP (Simplified Chinese Text Processing) was optimized and used to classify the sentiment of tourists\u2019 comments and calculate the sentiment value. Finally, we mined the distribution characteristics of tourists in 5A scenic areas and the spatio-temporal variations in tourists\u2019 sentiments. The results show that: (1) There is a negative correlation between the number of tourists to China\u2019s 5A scenic areas and tourist sentiment: the number of tourists is highest in October and lowest in March, while tourist sentiment is highest in March and lowest in October. (2) The spatio-temporal distribution of tourists has obvious aggregation: temporally mainly in July, August and October, spatially mainly in the Yangtze River Delta city cluster, Beijing-Tianjin-Hebei city cluster, and Guanzhong Plain city cluster. (3) Tourist sentiment cold\/hot spots vary significantly by city clusters: the Yangtze River Delta city cluster is always a sentiment hot spot; the northern city cluster has more sentiment cold spots; the central city cluster varies significantly during the year; the southwestern city cluster has more sentiment hot spots.<\/jats:p>","DOI":"10.3390\/ijgi11090492","type":"journal-article","created":{"date-parts":[[2022,9,18]],"date-time":"2022-09-18T23:39:22Z","timestamp":1663544362000},"page":"492","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Sensing Tourist Distributions and Their Sentiment Variations Using Social Media: Evidence from 5A Scenic Areas in China"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9855-4041","authenticated-orcid":false,"given":"Jingbo","family":"Wang","sequence":"first","affiliation":[{"name":"School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China"}]},{"given":"Yu","family":"Xia","sequence":"additional","affiliation":[{"name":"School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China"},{"name":"Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China"}]},{"given":"Yuting","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,17]]},"reference":[{"key":"ref_1","first-page":"91","article-title":"High-Quality Development of China\u2019s Tourism Industry: Strategic Mission, Power Factors and Promotion Path","volume":"01","author":"Geng","year":"2022","journal-title":"Macroeconomics"},{"key":"ref_2","first-page":"91","article-title":"Research on the Construction of Driving System and Development Level Measurement of Tourism High-Quality Development in Mountain Scenic Area","volume":"56","author":"Ming","year":"2022","journal-title":"J. Cent. China Norm. Univ."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Yu, Y., Lang, M., Zhao, Y., Liu, W., and Hu, B. (2021). Tourist Perceived Value, Tourist Satisfaction, and Life Satisfaction: Evidence From Chinese Buddhist Temple Tours. J. Hosp. Tour. Res., 109634802110153.","DOI":"10.1177\/10963480211015338"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1080\/14616688.2016.1169313","article-title":"Visitors\u2019 Place-Based Evaluations of Unacceptable Tourism Impacts in Oulanka National Park, Finland","volume":"18","author":"Fagerholm","year":"2016","journal-title":"Tour. Geogr."},{"key":"ref_5","first-page":"1091","article-title":"Exploring emotion methods of tourism destination evaluation: A big-data approach","volume":"36","author":"Liu","year":"2017","journal-title":"Geogr. Res."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"527","DOI":"10.37741\/t.69.4.4","article-title":"Can a Mature Sun & Beach Tourist DestinationChange Its Image Among Tourists?: The Case Study of Lloret de Mar","volume":"69","author":"Marin","year":"2021","journal-title":"Tourism"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Wang, P., Hu, T., Gao, F., Wu, R., Guo, W., and Zhu, X. (2022). A Hybrid Data-Driven Framework for Spatiotemporal Traffic Flow Data Imputation. IEEE Internet Things J., 1.","DOI":"10.1109\/JIOT.2022.3151238"},{"key":"ref_8","first-page":"102989","article-title":"Migratable Urban Street Scene Sensing Method Based on Vision Language Pre-Trained Model","volume":"113","author":"Zhang","year":"2022","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1007\/s40558-019-00144-3","article-title":"Determining Tourist Satisfaction from Travel Reviews","volume":"21","author":"Song","year":"2019","journal-title":"Inf. Technol. Tour."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"104000","DOI":"10.1016\/j.scs.2022.104000","article-title":"City2vec: Urban Knowledge Discovery Based on Population Mobile Network","volume":"85","author":"Zhang","year":"2022","journal-title":"Sustain. Cities Soc."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1007\/s40558-018-0121-z","article-title":"A Study on Online Travel Reviews through Intelligent Data Analysis","volume":"20","author":"Fazzolari","year":"2018","journal-title":"Inf. Technol. Tour."},{"key":"ref_12","first-page":"139","article-title":"What Makes Online Reviews Helpful in Tourism and Hospitality? A Bare-Bones Meta-Analysis","volume":"30","author":"Hu","year":"2021","journal-title":"J. Hosp. Mark. Manag."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Su, L., Yang, Q., Swanson, S.R., and Chen, N.C. (2021). The Impact of Online Reviews on Destination Trust and Travel Intention: The Moderating Role of Online Review Trustworthiness. J. Vacat. Mark., 135676672110632.","DOI":"10.1177\/13567667211063207"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Chen, W., Xu, Z., Zheng, X., Yu, Q., and Luo, Y. (2020). Research on Sentiment Classification of Online Travel Review Text. Appl. Sci., 10.","DOI":"10.3390\/app10155275"},{"key":"ref_15","first-page":"12","article-title":"An Emotional Analysis of Tourists in Wildlife Tourism Scenic Spots\u2014\u2014A Case Study in Chimelong Safari Park","volume":"35","author":"Cong","year":"2020","journal-title":"Tour. Trib."},{"key":"ref_16","first-page":"185","article-title":"Empirical research on the influencing factors of tourists\u2019pro-environment behavior:based on the dual perspectives of emotion and cognition","volume":"36","author":"Dang","year":"2021","journal-title":"Hum. Geogr."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1080\/10095020.2019.1649848","article-title":"Exploring the Characteristics of Tourism Industry by Analyzing Consumer Review Contents from Social Media: A Case Study of Bamako, Mali","volume":"22","author":"Bruno","year":"2019","journal-title":"Geo-Spat. Inf. Sci."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"550","DOI":"10.1016\/j.tourman.2019.06.020","article-title":"Analysing TripAdvisor Reviews of Tourist Attractions in Phuket, Thailand","volume":"75","author":"Taecharungroj","year":"2019","journal-title":"Tour. Manag."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Baniya, R., Dogru-Dastan, H., and Thapa, B. (2020). Visitors\u2019 Experience at Angkor Wat, Cambodia: Evidence from Sentiment and Topic Analysis. J. Herit. Tour., 1\u201314.","DOI":"10.1080\/1743873X.2020.1833892"},{"key":"ref_20","first-page":"2898","article-title":"High-quality development of urban agglomerations in China and construction of science and technology collaborative innovation community","volume":"76","author":"Fang","year":"2021","journal-title":"Acta Geogr. Sin."},{"key":"ref_21","first-page":"2075","article-title":"The Spatio-temporal Evolution and Mechanism of the Coordination Between Quality and Quantity of Economic Growth in Chinese Urban Agglomerations","volume":"41","author":"Zhang","year":"2021","journal-title":"Sci. Geogr. Sin."},{"key":"ref_22","first-page":"50","article-title":"Region-wide Tourism under the Strategy of Regional Coordinated Development:An Exploration of the Paradigm of Interaction of Eastern Guangdong Urban Agglomeration","volume":"36","author":"Zhou","year":"2021","journal-title":"Soc. Sci."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Qiu, Y., Yin, J., Zhang, T., Du, Y., and Zhang, B. (2021). Spatiotemporal Dynamic Analysis of A-Level Scenic Spots in Guizhou Province, China. ISPRS Int. J. Geo-Inf.","DOI":"10.3390\/ijgi10080568"},{"key":"ref_24","first-page":"10","article-title":"The Spatial Distribution and Influence Factors of A-Level Scenic Spots in Shanxi Province","volume":"40","author":"Liu","year":"2020","journal-title":"Econ. Geogr."},{"key":"ref_25","unstructured":"Zhang, H., Shi, T., and Bao, H. (2019). The Spatial Structure Characteristics of China\u2019s 5A-Level Tourist Attractions. J. Huaqiao Univ. Soc. Sci., 80\u201390."},{"key":"ref_26","unstructured":"Cheng, Y., Hou, Z., Chen, J., Economics, S.O., University, P., School, H.B., University, P., School, B., and Technology, U.O. (2015). Sydney Distribution Features and Economic Effect of National 5A Tourist Attractions in China. Areal Res. Dev."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"408","DOI":"10.1016\/j.apgeog.2015.08.002","article-title":"Identification of Tourist Hot Spots Based on Social Networks: A Comparative Analysis of European Metropolises Using Photo-Sharing Services and GIS","volume":"63","year":"2015","journal-title":"Appl. Geogr."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2144","DOI":"10.1080\/13683500.2020.1828308","article-title":"Tourist Attractions and the Location of Campsites in Western Australia","volume":"24","author":"Podhorodecka","year":"2021","journal-title":"Curr. Issues Tour."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1231","DOI":"10.1080\/13658816.2022.2032081","article-title":"A Multi-View Bidirectional Spatiotemporal Graph Network for Urban Traffic Flow Imputation","volume":"36","author":"Wang","year":"2022","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"498","DOI":"10.1016\/j.tourman.2015.07.018","article-title":"Analysis of the Perceived Value of Online Tourism Reviews: Influence of Readability and Reviewer Characteristics","volume":"52","author":"Fang","year":"2016","journal-title":"Tour. Manag."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"104585","DOI":"10.1016\/j.tourman.2022.104585","article-title":"A Framework for Quantitative Analysis and Differentiated Marketing of Tourism Destination Image Based on Visual Content of Photos","volume":"93","author":"Xiao","year":"2022","journal-title":"Tour. Manag."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Liang, B. (2021). Development of Rural Community-Based Tourism with Local Customs from the View of Consumer Satisfaction. Ann. Oper. Res., 1\u201317.","DOI":"10.1007\/s10479-021-04302-x"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"618","DOI":"10.1609\/icwsm.v6i1.14228","article-title":"Composing Traveling Paths from Location-Based Services","volume":"6","author":"Hsieh","year":"2012","journal-title":"Proc. Int. AAAI Conf. Web Soc. Media"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Yan, R., Xia, Z., Xie, Y., Wang, X., and Song, Z. (2020). Research on Sentiment Classification Algorithms on Online Review. Complexity, 2020.","DOI":"10.1155\/2020\/5093620"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Baziotis, C., Pelekis, N., and Doulkeridis, C. (2017, January 3\u20134). Datastories at Semeval-2017 Task 4: Deep Lstm with Attention for Message-Level and Topic-Based Sentiment Analysis. Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), Vancouver, BC, Canada. Available online: https:\/\/aclanthology.org\/S17-2126\/.","DOI":"10.18653\/v1\/S17-2126"},{"key":"ref_36","first-page":"64","article-title":"Classification of Sentimental Polarity for Chinese Online Reviews Based on Sentence Level Sentiment","volume":"16","author":"Wang","year":"2013","journal-title":"J. Manag. Sci. China"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1007\/s12559-021-09831-y","article-title":"Incremental Word Vectors for Time-Evolving Sentiment Lexicon Induction","volume":"14","author":"Khanchandani","year":"2022","journal-title":"Cogn. Comput."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Ahmad, M., Aftab, S., Bashir, M.S., Hameed, N., Ali, I., and Nawaz, Z. (2018). SVM Optimization for Sentiment Analysis. Int. J. Adv. Comput. Sci. Appl., 9.","DOI":"10.14569\/IJACSA.2018.090455"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Mathapati, S., Nafeesa, A., Manjula, S.H., and Venugopal, K.R. (2018). OTAWE-Optimized Topic-Adaptive Word Expansion for Cross Domain Sentiment Classification on Tweets. Advances in Machine Learning and Data Science, Springer.","DOI":"10.1007\/978-981-10-8569-7_23"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Yin, D., Meng, T., and Chang, K.-W. (2020). Sentibert: A Transferable Transformer-Based Architecture for Compositional Sentiment Semantics. arXiv.","DOI":"10.18653\/v1\/2020.acl-main.341"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Dwivedi, R.K., Aggarwal, M., Keshari, S.K., and Kumar, A. (2018, January 5\u20136). Sentiment Analysis and Feature Extraction Using Rule-Based Model (RBM). Proceedings of the International Conference on Innovative Computing and Communications, New Delhi, India.","DOI":"10.1007\/978-981-13-2354-6_7"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Zhang, B., Xiao, P., and Yu, X. (2021). The Influence of Prosocial and Antisocial Emotions on the Spread of Weibo Posts: A Study of the COVID-19 Pandemic. Discrete Dyn. Nat. Soc., 2021.","DOI":"10.1155\/2021\/8462264"},{"key":"ref_43","first-page":"918","article-title":"Measurement of the driving capacity of tourism industry on indirect employment and its spatio-temporal differences in China","volume":"77","author":"Liu","year":"2022","journal-title":"Acta Geogr. Sin."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1080\/10941665.2020.1741411","article-title":"5A Tourist Attractions and China\u2019s Regional Tourism Growth","volume":"25","author":"Lin","year":"2020","journal-title":"Asia Pac. J. Tour. Res."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Tian, L., Pu, W., Su, C.-H., Chen, M.-H., and Lin, Y.-X. (2021). Asymmetric Effects of China\u2019s Tourism on the Economy at the City Level: A Moderating Role of Spatial Disparities in Top Level Tourist Attractions. Curr. Issues Tour., 1\u201317.","DOI":"10.1080\/13683500.2021.1987397"},{"key":"ref_46","first-page":"107","article-title":"A Cross-Platform Comparative Study of Reviews on Sharing Accommodation and Hotels Reservation Platform: Combined with LDA-SNA and Sentiment Analysis","volume":"65","author":"Chi","year":"2021","journal-title":"Libr. Inf. Serv."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Zhang, J., Zheng, Z., Zhang, L., Qin, Y., Duan, J., and Zhang, A. (2021). Influencing Factors of Environmental Risk Perception during the COVID-19 Epidemic in China. Int. J. Environ. Res. Public Health, 18.","DOI":"10.3390\/ijerph18179375"},{"key":"ref_48","first-page":"341","article-title":"Analysis of Public Opinion Evolution in COVID-19 Pandemic from a Perspective of Sentiment Variation","volume":"23","author":"Zhang","year":"2021","journal-title":"J. Geo-Inf. Sci."},{"key":"ref_49","first-page":"132","article-title":"Analysis of Space-Time Pattern of Robbery Crime Based on Space-Time Cube","volume":"9","author":"Zhu","year":"2019","journal-title":"Sci. Surv. Mapp."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Park, Y.M., Kearney, G.D., Wall, B., Jones, K., Howard, R.J., and Hylock, R.H. (2021). COVID-19 Deaths in the United States: Shifts in Hot Spots over the Three Phases of the Pandemic and the Spatiotemporally Varying Impact of Pandemic Vulnerability. Int. J. Environ. Res. Public. Health, 18.","DOI":"10.3390\/ijerph18178987"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Purwanto, P., Utaya, S., Handoyo, B., Bachri, S., Astuti, I.S., Utomo, K.S.B., and Aldianto, Y.E. (2021). Spatiotemporal Analysis of COVID-19 Spread with Emerging Hotspot Analysis and Space\u2013Time Cube Models in East Java, Indonesia. ISPRS Int. J. Geo-Inf., 10.","DOI":"10.3390\/ijgi10030133"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Allen, M.J., Allen, T.R., Davis, C., and McLeod, G. (2021). Exploring Spatial Patterns of Virginia Tornadoes Using Kernel Density and Space-Time Cube Analysis (1960\u20132019). ISPRS Int. J. Geo-Inf., 10.","DOI":"10.3390\/ijgi10050310"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1007\/s10291-014-0403-7","article-title":"Development of an Improved Empirical Model for Slant Delays in the Troposphere (GPT2w)","volume":"19","author":"Schindelegger","year":"2015","journal-title":"GPS Solut."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"118654","DOI":"10.1016\/j.jclepro.2019.118654","article-title":"Spatiotemporal Evolution Pattern Detection for Heavy-Duty Diesel Truck Emissions Using Trajectory Mining: A Case Study of Tianjin, China","volume":"244","author":"Cheng","year":"2020","journal-title":"J. Clean. Prod."},{"key":"ref_55","first-page":"8","article-title":"Spatio-Temporal Pattern Mining of the Last 40 Years of Drought in China Based on SPEI Index and Spatio-Temporal Cube","volume":"39","author":"Qi","year":"2021","journal-title":"Agric. Res. Arid Areas"},{"key":"ref_56","first-page":"95","article-title":"Time-space Pattern Evolution and Optimal Regulation of Scenic Crowding","volume":"40","author":"Ji","year":"2021","journal-title":"Areal Res. Dev."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/j.jort.2019.01.001","article-title":"Sustainable Safari Practices: Proximity to Wildlife, Educational Intervention, and the Quality of Experience","volume":"25","author":"Tarver","year":"2019","journal-title":"J. Outdoor Recreat. Tour."},{"key":"ref_58","first-page":"301","article-title":"A Study on the development characteristics of the national 5A tourist attractions in China","volume":"48","author":"Yuan","year":"2014","journal-title":"J. Huazhong Norm. Univ. Sci."},{"key":"ref_59","unstructured":"Li, H., Li, D., Dong, X., and Xu, N. (2019). Spatial Patterns of 5A-Level Tourist Attractions and Their Nework Attention Degrees in China. J. Arid Land Resour. Environ., 10."},{"key":"ref_60","first-page":"15","article-title":"Research on Spatial Distribution and Influencing Factors of Tourist Attractions in China\u2019s Three Major Urban Agglomerations","volume":"35","author":"Zhang","year":"2021","journal-title":"China Anc. City"},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Ettema, D., Friman, M., Olsson, L.E., and G\u00e4rling, T. (2017). Season and Weather Effects on Travel-Related Mood and Travel Satisfaction. Front. Psychol., 8.","DOI":"10.3389\/fpsyg.2017.00140"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/j.trf.2014.07.004","article-title":"The Happy Commuter: A Comparison of Commuter Satisfaction across Modes","volume":"26","author":"Manaugh","year":"2014","journal-title":"Transp. Res. Part F: Traffic Psychol. Behav."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Padilla, J.J., Kavak, H., Lynch, C.J., Gore, R.J., and Diallo, S.Y. (2018). Temporal and Spatiotemporal Investigation of Tourist Attraction Visit Sentiment on Twitter. PLoS ONE, 13.","DOI":"10.1371\/journal.pone.0198857"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Chen, M.M., Yu, P., Zhang, Y., Wu, K., and Yang, Y. (2021). Acoustic Environment Management in the Countryside: A Case Study of Tourist Sentiment for Rural Soundscapes in China. J. Environ. Plan. Manag., 1\u201323.","DOI":"10.1080\/09640568.2020.1862768"},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Cheng, Z., Jin, M., and Jiang, Q. (2019). Research into the Competitiveness of Scenic Areas from the Perspective of Tourists: A Case Study of the Jiuzhai Valley. Emerg. Mark. Financ. Trade, 1\u20139.","DOI":"10.1080\/1540496X.2019.1672530"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"103977","DOI":"10.1016\/j.landurbplan.2020.103977","article-title":"The Image of the City on Social Media: A Comparative Study Using \u201cBig Data\u201d and \u201cSmall Data\u201d Methods in the Tri-City Region in Poland","volume":"206","author":"Huang","year":"2021","journal-title":"Landsc. Urban Plan."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/11\/9\/492\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:33:39Z","timestamp":1760142819000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/11\/9\/492"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,17]]},"references-count":66,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2022,9]]}},"alternative-id":["ijgi11090492"],"URL":"https:\/\/doi.org\/10.3390\/ijgi11090492","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,17]]}}}