IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i12p4509-d375269.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/12/4509/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/17/12/4509/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Syed Ali Asad Naqvi & Muhammad Sajjad & Liaqat Ali Waseem & Shoaib Khalid & Saima Shaikh & Syed Jamil Hasan Kazmi, 2021. "Integrating Spatial Modelling and Space–Time Pattern Mining Analytics for Vector Disease-Related Health Perspectives: A Case of Dengue Fever in Pakistan," IJERPH, MDPI, vol. 18(22), pages 1-30, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shuli Zhou & Suhong Zhou & Lin Liu & Meng Zhang & Min Kang & Jianpeng Xiao & Tie Song, 2019. "Examining the Effect of the Environment and Commuting Flow from/to Epidemic Areas on the Spread of Dengue Fever," IJERPH, MDPI, vol. 16(24), pages 1-13, December.
    2. Zhichao Li, 2022. "Forecasting Weekly Dengue Cases by Integrating Google Earth Engine-Based Risk Predictor Generation and Google Colab-Based Deep Learning Modeling in Fortaleza and the Federal District, Brazil," IJERPH, MDPI, vol. 19(20), pages 1-16, October.
    3. Shi Yin & Chao Ren & Yuan Shi & Junyi Hua & Hsiang-Yu Yuan & Lin-Wei Tian, 2022. "A Systematic Review on Modeling Methods and Influential Factors for Mapping Dengue-Related Risk in Urban Settings," IJERPH, MDPI, vol. 19(22), pages 1-20, November.
    4. Thomas C. McHale & Claudia M. Romero-Vivas & Claudio Fronterre & Pedro Arango-Padilla & Naomi R. Waterlow & Chad D. Nix & Andrew K. Falconar & Jorge Cano, 2019. "Spatiotemporal Heterogeneity in the Distribution of Chikungunya and Zika Virus Case Incidences during their 2014 to 2016 Epidemics in Barranquilla, Colombia," IJERPH, MDPI, vol. 16(10), pages 1-21, May.
    5. Daniel Adyro Martínez-Bello & Antonio López-Quílez & Alexander Torres Prieto, 2018. "Spatio-Temporal Modeling of Zika and Dengue Infections within Colombia," IJERPH, MDPI, vol. 15(7), pages 1-18, June.
    6. Yuqi Zhang & Hongyan Ren & Runhe Shi, 2022. "Influences of Differentiated Residence and Workplace Location on the Identification of Spatiotemporal Patterns of Dengue Epidemics: A Case Study in Guangzhou, China," IJERPH, MDPI, vol. 19(20), pages 1-19, October.
    7. Villi Dane M. Go, 2023. "Communicable disease surveillance through predictive analysis: A comparative analysis of prediction models," HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE - ENGINEERING AND TECHNOLOGY, HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE, HO CHI MINH CITY OPEN UNIVERSITY, vol. 13(2), pages 45-54.
    8. Zhao, Xinxing & Li, Kainan & Ang, Candice Ke En & Cheong, Kang Hao, 2023. "A deep learning based hybrid architecture for weekly dengue incidences forecasting," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    9. Nicholas G. Reich & Justin Lessler & Krzysztof Sakrejda & Stephen A. Lauer & Sopon Iamsirithaworn & Derek A. T. Cummings, 2016. "Case Study in Evaluating Time Series Prediction Models Using the Relative Mean Absolute Error," The American Statistician, Taylor & Francis Journals, vol. 70(3), pages 285-292, July.
    10. 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.
    11. Fredrik Ødegaard & Sudipendra Nath Roy, 2021. "Heuristic-based allocation of supply constrained blood platelets in emerging economies," Journal of Heuristics, Springer, vol. 27(5), pages 719-745, October.
    12. Shin-Yueh Liu & Tsair-Wei Chien & Ting-Ya Yang & Yu-Tsen Yeh & Willy Chou & Julie Chi Chow, 2021. "A Bibliometric Analysis on Dengue Outbreaks in Tropical and Sub-Tropical Climates Worldwide Since 1950," IJERPH, MDPI, vol. 18(6), pages 1-15, March.
    13. Kun Wang & Zhihao Sun & Meng Cai & Lingbo Liu & Hao Wu & Zhenghong Peng, 2022. "Impacts of Urban Blue-Green Space on Residents’ Health: A Bibliometric Review," IJERPH, MDPI, vol. 19(23), pages 1-21, December.
    14. Johnny A. Uelmen & Charles Brokopp & Jonathan Patz, 2020. "A 15 Year Evaluation of West Nile Virus in Wisconsin: Effects on Wildlife and Human Health," IJERPH, MDPI, vol. 17(5), pages 1-24, March.
    15. 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.
    16. Vicente Navarro Valencia & Yamilka Díaz & Juan Miguel Pascale & Maciej F. Boni & Javier E. Sanchez-Galan, 2021. "Assessing the Effect of Climate Variables on the Incidence of Dengue Cases in the Metropolitan Region of Panama City," IJERPH, MDPI, vol. 18(22), pages 1-18, November.
    17. Luba Pascoe & Thomas Clemen & Karen Bradshaw & Devotha Nyambo, 2022. "Review of Importance of Weather and Environmental Variables in Agent-Based Arbovirus Models," IJERPH, MDPI, vol. 19(23), pages 1-24, November.
    18. Liang Cheng & Long Li & Longqian Chen & Sai Hu & Lina Yuan & Yunqiang Liu & Yifan Cui & Ting Zhang, 2019. "Spatiotemporal Variability and Influencing Factors of Aerosol Optical Depth over the Pan Yangtze River Delta during the 2014–2017 Period," IJERPH, MDPI, vol. 16(19), pages 1-25, September.
    19. Supreet Kaur & Sandeep Sharma & Ateeq Ur Rehman & Elsayed Tag Eldin & Nivin A. Ghamry & Muhammad Shafiq & Salil Bharany, 2022. "Predicting Infection Positivity, Risk Estimation, and Disease Prognosis in Dengue Infected Patients by ML Expert System," Sustainability, MDPI, vol. 14(20), pages 1-20, October.
    20. Andrea L. Araujo Navas & Frank Osei & Lydia R. Leonardo & Ricardo J. Soares Magalhães & Alfred Stein, 2019. "Modeling Schistosoma japonicum Infection under Pure Specification Bias: Impact of Environmental Drivers of Infection," IJERPH, MDPI, vol. 16(2), pages 1-17, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:17:y:2020:i:12:p:4509-:d:375269. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.