T-S Fuzzy remote sensing monitoring model of snail distribution by Landsat 8 and Sentinel 2 data

LIU Zhaoyan; TANG Lingli; LI Chuanrong; XIA Shang; XUE Jingbo; LI Shizhu; ZHOU Xiaonong

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T-S Fuzzy remote sensing monitoring model of snail distribution by Landsat 8 and Sentinel 2 data
Vol. 24, Issue S1, Pages: 33-38(2020)
Received：21 October 2019，

Accepted：16 April 2020，

Published：07 June 2020
DOI：
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DOI：

format: Liu Z Y,Tang L L,Li C R,Xia S,Xue J B,Li S Z and Zhou X N. 2020. T-S Fuzzy remote sensing monitoring model of snail distribution by Landsat 8 and Sentinel 2 data. Journal of Remote Sensing(Chinese). 24(S1): 33-38 DOI：

摘要

Abstract

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. Oncomelania hupensis (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.

关键词

Keywords

references

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