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

doi:10.11947/j.JGGS.2020.0412

Journal of Geodesy and Geoinformation Science ›› 2020, Vol. 3 ›› Issue (4): 118-125.doi: 10.11947/j.JGGS.2020.0412

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

Zhaoyan LIU¹(),Lingli TANG¹(),Chuanrong LI¹,Shang XIA^2,^3,^4,⁵,Jingbo XUE^2,^3,^4,⁵,Shizhu LI^2,^3,^4,⁵,Xiaonong ZHOU^2,^3,^4,⁵

1. Key Laboratory of Quantitative Remote Sensing Information Technology, Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing 100094, China
2. National Institute of Parasitic Diseases, Chinese Center for Diseases Control and Prevention, Shanghai 200025, China
3. Chinese Center for Tropical Diseases Research, Shanghai 200025, China
4. Key Laboratory of Parasite and Vector Biology, National Commission of Health, Shanghai 200025, China
5. WHO Collaborating Centre for Tropical Diseases, Shanghai 200025, China

Received:2020-10-11 Accepted:2020-11-20 Online:2020-12-20 Published:2021-01-15
Contact: Lingli TANG E-mail:zyliu@aoe.ac.cn;lltang@aoe.ac.cn
About author:Zhaoyan LIU(1983—), female, associate professor, majors in spatial-temporal transmission model of vector-borne diseases.E-mail: zyliu@aoe.ac.cn
Supported by:
Dragon 4 ESA-MOST Cooperation programme(Project ID. 32260);National Natural Science Foundation of China(41301495)

Abstract

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. 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.

Key words: Schistosomiasis; snail; Landsat 8; Sentinel 2; T-S Fuzzy

Zhaoyan LIU,Lingli TANG,Chuanrong LI,Shang XIA,Jingbo XUE,Shizhu LI,Xiaonong ZHOU. T-S Fuzzy Remote Sensing Monitoring Model of Snail Distribution by Landsat 8 and Sentinel 2 Data[J]. Journal of Geodesy and Geoinformation Science, 2020, 3(4): 118-125.

Figures/Tables 7

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References 17

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Environment of snail	Biologic Characteristics
Types of distribution	Lake type
Influence of water distribution	Winter Land, Summer Water
Time of medication and field survey	Spring(April) and Autumn (September)
Temperature	Suitable breeding between 20℃ to 25℃
Elevation	20~35m(between lowest water lever to flood line)
Vegetation	Cover the sunshine, adjust humidity
Water	Necessity, too little or drown, it will die
Soil, Sunshine, food, oxygen	—

ID
1	2014.04.04	Lansat 8	30	Vegetation: NDVI Soil:TC_Brightness, TC_Wetness Water distribution: NDWI Distance to the water, etc.
2	2015.04.16	Lansat 8	30
3	2016.04.18	Lansat 8	30
4	2017.05.18	Sentinel 2	10/20/60
5	2018.04.18	Sentinel 2	10/20/60
6	—	ASTER DEM	30	Elevation

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

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Year	Number of survey	Right predict	Accuracy
2014	22	18	81%
2015	108	93	86%