首页> 中文期刊> 《测绘学报(英文)》 >T-S Fuzzy Remote Sensing Monitoring Model of Snail Distribution by Landsat 8 and Sentinel 2 Data

T-S Fuzzy Remote Sensing Monitoring Model of Snail Distribution by Landsat 8 and Sentinel 2 Data

         

摘要

Approximately half of the world’s population is at the risk of at least one vector-borne parasitic disease.The survival of intermediate hosts of vector-borne parasitic diseases is governed by various environmental factors,and remote sensing can be used to characterize and monitor environmental factors related to intermediate host breeding and reproduction,and become a powerful means to monitor the vector-borne parasitic diseases.Schistosomiasis is a parasitic disease that menaces human health.Oncomelaniahupensis(snail)is the unique intermediate host of Schistosoma,so monitoring and controlling the number of snail is key to reduce the risk of schistosomiasis transmission.In this paper,Landsat 8 OLI and Sentinel 2 MSI data had been used to obtain the environmental factors(vegetation,soil,temperature,terrain et al.),which are related to the multiplying and transmission of intermediate host.Then this study used T-S(Takagi-Sugeno)Fuzzy RS model to establish a new suitable index membership function due to the different RS data,and a long time series monitoring of snail distribution in Dongting Lake from 2014 to 2018 was achieved.A comparative analysis was performed to validate the predicted results against the field survey data.The results demonstrated the accuracy of the developed model in predicting the distribution of snails.

著录项

  • 来源
    《测绘学报(英文)》 |2020年第004期|118-125|共8页
  • 作者单位

    Key Laboratory of Quantitative Remote Sensing Information Technology Academy of Opto-Electronics Chinese Academy of Sciences Beijing 100094 China;

    Key Laboratory of Quantitative Remote Sensing Information Technology Academy of Opto-Electronics Chinese Academy of Sciences Beijing 100094 China;

    Key Laboratory of Quantitative Remote Sensing Information Technology Academy of Opto-Electronics Chinese Academy of Sciences Beijing 100094 China;

    National Institute of Parasitic Diseases Chinese Center for Diseases Control and Prevention Shanghai 200025 China;

    Chinese Center for Tropical Diseases Research Shanghai 200025 China;

    Key Laboratory of Par-asite and Vector Biology National Commission of Health Shanghai 200025 China;

    WHO Collaborating Centre for Tropical Diseases Shanghai 200025 China;

    National Institute of Parasitic Diseases Chinese Center for Diseases Control and Prevention Shanghai 200025 China;

    Chinese Center for Tropical Diseases Research Shanghai 200025 China;

    Key Laboratory of Par-asite and Vector Biology National Commission of Health Shanghai 200025 China;

    WHO Collaborating Centre for Tropical Diseases Shanghai 200025 China;

    National Institute of Parasitic Diseases Chinese Center for Diseases Control and Prevention Shanghai 200025 China;

    Chinese Center for Tropical Diseases Research Shanghai 200025 China;

    Key Laboratory of Par-asite and Vector Biology National Commission of Health Shanghai 200025 China;

    WHO Collaborating Centre for Tropical Diseases Shanghai 200025 China;

    National Institute of Parasitic Diseases Chinese Center for Diseases Control and Prevention Shanghai 200025 China;

    Chinese Center for Tropical Diseases Research Shanghai 200025 China;

    Key Laboratory of Par-asite and Vector Biology National Commission of Health Shanghai 200025 China;

    WHO Collaborating Centre for Tropical Diseases Shanghai 200025 China;

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