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Semi-Supervised Text Classification Framework: An Overview of Dengue Landscape Factors and Satellite Earth Observation

Author

Listed:
  • Zhichao Li

    (Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System, Science, Tsinghua University, Beijing 100084, China)

  • Helen Gurgel

    (Department of Geography, University of Brasilia (UnB), Brasilia CEP 70910-900, Brazil
    International Joint Laboratory Sentinela, FIOCRUZ, UnB, IRD, Rio de Janeiro RJ-21040-900, Brazil)

  • Nadine Dessay

    (International Joint Laboratory Sentinela, FIOCRUZ, UnB, IRD, Rio de Janeiro RJ-21040-900, Brazil
    IRD, UM, UR, UG, UA, UMR ESPACE-DEV, 34090 Montpellier, France)

  • Luojia Hu

    (Qian Xuesen Laboratory of Space Technology, China Academy of Space Technology, Beijing 100094, China)

  • Lei Xu

    (Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System, Science, Tsinghua University, Beijing 100084, China)

  • Peng Gong

    (Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System, Science, Tsinghua University, Beijing 100084, China
    Center for Healthy Cities, Institute for China Sustainable Urbanization, Tsinghua University, Beijing 100084, China)

Abstract

In recent years there has been an increasing use of satellite Earth observation (EO) data in dengue research, in particular the identification of landscape factors affecting dengue transmission. Summarizing landscape factors and satellite EO data sources, and making the information public are helpful for guiding future research and improving health decision-making. In this case, a review of the literature would appear to be an appropriate tool. However, this is not an easy-to-use tool. The review process mainly includes defining the topic, searching, screening at both title/abstract and full-text levels and data extraction that needs consistent knowledge from experts and is time-consuming and labor intensive. In this context, this study integrates the review process, text scoring, active learning (AL) mechanism, and bidirectional long short-term memory (BiLSTM) networks, and proposes a semi-supervised text classification framework that enables the efficient and accurate selection of the relevant articles. Specifically, text scoring and BiLSTM-based active learning were used to replace the title/abstract screening and full-text screening, respectively, which greatly reduces the human workload. In this study, 101 relevant articles were selected from 4 bibliographic databases, and a catalogue of essential dengue landscape factors was identified and divided into four categories: land use (LU), land cover (LC), topography and continuous land surface features. Moreover, various satellite EO sensors and products used for identifying landscape factors were tabulated. Finally, possible future directions of applying satellite EO data in dengue research in terms of landscape patterns, satellite sensors and deep learning were proposed. The proposed semi-supervised text classification framework was successfully applied in research evidence synthesis that could be easily applied to other topics, particularly in an interdisciplinary context.

Suggested Citation

  • Zhichao Li & Helen Gurgel & Nadine Dessay & Luojia Hu & Lei Xu & Peng Gong, 2020. "Semi-Supervised Text Classification Framework: An Overview of Dengue Landscape Factors and Satellite Earth Observation," IJERPH, MDPI, vol. 17(12), pages 1-29, June.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:12:p:4509-:d:375269
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    References listed on IDEAS

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    1. Sair Arboleda & Nicolas Jaramillo-O. & A. Townsend Peterson, 2009. "Mapping Environmental Dimensions of Dengue Fever Transmission Risk in the Aburrá Valley, Colombia," IJERPH, MDPI, vol. 6(12), pages 1-16, December.
    2. Zheng Cao & Tao Liu & Xing Li & Jin Wang & Hualiang Lin & Lingling Chen & Zhifeng Wu & Wenjun Ma, 2017. "Individual and Interactive Effects of Socio-Ecological Factors on Dengue Fever at Fine Spatial Scale: A Geographical Detector-Based Analysis," IJERPH, MDPI, vol. 14(7), pages 1-14, July.
    3. Zhichao Li & Thibault Catry & Nadine Dessay & Helen Da Costa Gurgel & Cláudio Aparecido de Almeida & Christovam Barcellos & Emmanuel Roux, 2017. "Regionalization of a Landscape-Based Hazard Index of Malaria Transmission: An Example of the State of Amapá, Brazil," Data, MDPI, vol. 2(4), pages 1-11, November.
    4. Chi-Chieh Huang & Tuen Yee Tiffany Tam & Yinq-Rong Chern & Shih-Chun Candice Lung & Nai-Tzu Chen & Chih-Da Wu, 2018. "Spatial Clustering of Dengue Fever Incidence and Its Association with Surrounding Greenness," IJERPH, MDPI, vol. 15(9), pages 1-12, August.
    5. Mohamed F. Sallam & Chelsea Fizer & Andrew N. Pilant & Pai-Yei Whung, 2017. "Systematic Review: Land Cover, Meteorological, and Socioeconomic Determinants of Aedes Mosquito Habitat for Risk Mapping," IJERPH, MDPI, vol. 14(10), pages 1-15, October.
    6. Jiucheng Xu & Keqiang Xu & Zhichao Li & Fengxia Meng & Taotian Tu & Lei Xu & Qiyong Liu, 2020. "Forecast of Dengue Cases in 20 Chinese Cities Based on the Deep Learning Method," IJERPH, MDPI, vol. 17(2), pages 1-14, January.
    7. Yebin Chen & Zhigang Zhao & Zhichao Li & Weihong Li & Zhipeng Li & Renzhong Guo & Zhilu Yuan, 2019. "Spatiotemporal Transmission Patterns and Determinants of Dengue Fever: A Case Study of Guangzhou, China," IJERPH, MDPI, vol. 16(14), pages 1-14, July.
    8. Nicholas A S Hamm & Ricardo J Soares Magalhães & Archie C A Clements, 2015. "Earth Observation, Spatial Data Quality, and Neglected Tropical Diseases," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 9(12), pages 1-24, December.
    9. Chuan-Hung Chiu & Tzai-Hung Wen & Lung-Chang Chien & Hwa-Lung Yu, 2014. "A Probabilistic Spatial Dengue Fever Risk Assessment by a Threshold-Based-Quantile Regression Method," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-13, October.
    10. Thibault Catry & Zhichao Li & Emmanuel Roux & Vincent Herbreteau & Helen Gurgel & Morgan Mangeas & Frédérique Seyler & Nadine Dessay, 2018. "Wetlands and Malaria in the Amazon: Guidelines for the Use of Synthetic Aperture Radar Remote-Sensing," IJERPH, MDPI, vol. 15(3), pages 1-27, March.
    11. Renaud Marti & Zhichao Li & Thibault Catry & Emmanuel Roux & Morgan Mangeas & Pascal Handschumacher & Jean Gaudart & Annelise Tran & Laurent Demagistri & Jean-François Faure & José Joaquín Carvajal & , 2020. "A Mapping Review on Urban Landscape Factors of Dengue Retrieved from Earth Observation Data, GIS Techniques, and Survey Questionnaires," Post-Print hal-02682042, HAL.
    12. Olaf Horstick & Yesim Tozan & Annelies Wilder-Smith, 2015. "Reviewing Dengue: Still a Neglected Tropical Disease?," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 9(4), pages 1-18, April.
    13. Bernard Bett & Delia Grace & Hu Suk Lee & Johanna Lindahl & Hung Nguyen-Viet & Pham-Duc Phuc & Nguyen Huu Quyen & Tran Anh Tu & Tran Dac Phu & Dang Quang Tan & Vu Sinh Nam, 2019. "Spatiotemporal analysis of historical records (2001–2012) on dengue fever in Vietnam and development of a statistical model for forecasting risk," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-22, November.
    14. Anna L Buczak & Benjamin Baugher & Steven M Babin & Liane C Ramac-Thomas & Erhan Guven & Yevgeniy Elbert & Phillip T Koshute & John Mark S Velasco & Vito G Roque Jr & Enrique A Tayag & In-Kyu Yoon & S, 2014. "Prediction of High Incidence of Dengue in the Philippines," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 8(4), pages 1-13, April.
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