Abstract
With the increasing environmental awareness of the country and the people and the implementation of strong environmental protection measures, China’s atmospheric quality was improved obviously, but local atmospheric pollution events still occurred frequently. In order to make up for the missing detection of local atmospheric pollution events caused by sparse fixed State-controlled monitoring stations, the paper proposed a spatialization method for atmospheric quality public opinion information based on natural language processing. Using Chinese word segmentation, part of speech tagging and other methods, the paper extracted addresses from public atmospheric pollution complaints data. Through an effective combination of those addresses, the paper realized address matching of those complaint points, and spatialized those key complaint areas in Shandong Province in the form of heat map. Through comparison and analyzing with the atmospheric quality monitoring data of national control stations, it showed that the key areas of public complaints were highly consistent with the key pollution areas which were monitored by national control stations. The research result showed that the public could perceive the atmospheric quality directly, and reflect the local atmospheric pollution at a smaller space-time scale effectively, which was a robust supplementation to the monitoring data of the national control station.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Greene, J.S., Kalkstein, L.S., Ye, H., et al.: Relationships between synoptic climatology and atmospheric pollution at 4 US cities. Theoret. Appl. Climatol. 62(3–4), 163–174 (1999). https://doi.org/10.1007/s007040050081
Pantavou, K., Lykoudis, S., Psiloglou, B.: Air quality perception of pedestrians in an urban outdoor Mediterranean environment: a field survey approach. Sci. Total Environ. 574, 663–670 (2017)
Song, J.G., Guo, M.Y., Yin, G.B.: Urban air quality management satisfaction evaluation method and case study. Environ. Pollut. Control 33(09), 81–86 (2011)
Chen, S.: The development of government service under the era of “Internet +” [J/OL]. Electr. Technol. Softw. Eng. (22), 19 (2018)
Wang, M.M., Wang, J.L.: Spatialization of township-level population based on nighttime light and land use data in Shandong Province. J. Geo-Inf. Sci. 21(05), 699–709 (2019)
Yin, Y.J., Liu, H., Ye, L.: Application of data cleaning and spatial visualization in floating car data processing. Geosp. Inf. 17(05), 116–119+6 (2019)
Xu, Y.L.: Review of natural language processing based on deep learning. In: The 22nd Network New Technology and Application Annual Conference Proceedings. China Computer User Association Network Application Branch, Beijing Union University Beijing Information Service Engineering Key Laboratory, p. 4 (2018)
Li, S.: Research and development of natural language processing. J. Yanshan Univ. 37(05), 377–384 (2013)
Ma, L.B., Gong, J.Y.: Application of spatial information natural language query interface. Editor. Board Geomatics Inf. Sci. Wuhan Univ. (03), 301–305 (2003)
Matci, K., Dilek, A.U.: Address standardization using the natural language process for improving geocoding results. Comput. Environ. Urban Syst. S0198971517300455 (2018)
Xu, P.L., Wang, Y., Huang, Y.K.: Chinese place-name address matching method based on large data analysis and Bayesian decision. Comput. Sci. 44(09), 266–271 (2017)
Cheng, C.X., Yu, B.: A rule-based segmenting and matching method for fuzzy Chinese addresses. Geogr. Geo-Inf. Sci. 27(03), 26–29 (2011)
Li, X.F., Song, Z.L., Chen, X.Y.: Research and implementation of fuzzy matching for K-tree address. Bull. Surv. Mapp. (09), 126–129+155 (2018)
Xu, M.H.: User comments data model and information processing. Inf. Technol. Inf. (03), 147–149 (2019)
Xu, W.: Research and implementation for Chinese Lexicon analysis system based on neural network. Harbin Institute of Technology (2017)
Zong, C.Q.: Statistical Natural Language Processing, 2nd edn, p. 135. Tsinghua University Press, Beijing (2013)
Chegn, Y.S., Shi, Y.T.: Domain specific Chinese word segmentation. Comput. Eng. Appl. 54(17), 30–34+109 (2018)
Zheng, J.: Principles and practice of NLP Chinese natural language processing. Publishing House of Electroni2017 Air Quality Ranking of Cities in Shandong Provinces Industry, Beijing, p. 196 (2017)
Wang, X., Sun, W.W., Hui, Z.F.: Research on Chinese semantic role labeling based on shallow parsing. J. Chin. Inf. Process. 25(01), 116–122 (2011)
Acknowledgments
This work was supported in part by a grant from the Major Science and Technology Innovation Projects of Shandong Province (2019JZZY020103) and the National Science Foundation of China (41471330).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Sun, Y., Song, P., Ji, M., Zheng, Y., Zhang, L. (2020). Spatialization Method of Atmospheric Quality Public Opinion Based on Natural Language Processing. In: Xie, Y., Li, Y., Yang, J., Xu, J., Deng, Y. (eds) Geoinformatics in Sustainable Ecosystem and Society. GSES GeoAI 2019 2019. Communications in Computer and Information Science, vol 1228. Springer, Singapore. https://doi.org/10.1007/978-981-15-6106-1_23
Download citation
DOI: https://doi.org/10.1007/978-981-15-6106-1_23
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-6105-4
Online ISBN: 978-981-15-6106-1
eBook Packages: Computer ScienceComputer Science (R0)