Application of Remote Sensing and GIS for Malaria Disease Susceptibility Area Mapping in Padang Cermin Sub-District, District of Pesawaran, Lampung Province

3rd International Conference of Indonesia Society for Remote Sensing

地球科学;计算机科学

Hanifati, Adhina Azdah^1 ; Permata, Anggi^1 ; Mustofa, Dian^1 ; Wulandari, Dita Eko^1 ; Ratnasari, Intan Dewi^1 ; Ekafitri, Nabila Anggita^1 ; Ridho, Yusron Hidayat^1 ; Widayani, Prima^1

Cartography and Remote Sensing, Departement of Science Information Geography, Faculty of Geography, Gadjah Mada University, Yogyakarta

55281, Indonesia^1

关键词: Disease susceptibility;    Environmental factors;    Infectious disease;    Remote sensing and GIS;    Remote sensing data;    research methods;    Spatial parameters;    Vegetation density;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/165/1/012012/pdf
DOI  :  10.1088/1755-1315/165/1/012012

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

Malaria is epidemiologically a specific local infectious disease and can be studied spatially by taking into account the characteristics of malaria vector habitat. Padang Cermin Sub-District, District of Pesawaran, Lampung Province is one of the endemic areas of malaria which is geographically a coastal area dominated by water-flooded land use. That area supports the breeding and living place of Anopheles sp mosquitoes. The objectives of this study were mapping the malaria disease susceptibility area in Padang Cermin sub-district by using Landsat 8 imagery, identified the influence of physical environmental factors on the spread of malaria disease, and analyzed the spread of malaria disease based on environmental factors. The research method used scoring and overlay spatial analysis of spatial parameters supporting the breeding of malaria vector. Some parameters that can be extracted through Landsat 8 imagery for identification of malaria susceptibility, i.e. land use, soil texture, vegetation density with overall mapping accuracy of vegetation density, land use, and soil texture are 83.2%, 88.7%, and 83.7%, while other parameters resulted from spatial analysis of non-remote sensing data, i.e. temperature, rainfall, slope, altitude, and distance to river. These parameters are environmental factors that influence the spread of malaria disease. The results of the identification of malaria susceptibility showed that the areas with high levels of susceptibility are Sidodadi, Sukajaya Lempasing, Gebang, Padang Cermin, Hanau Berak, Way Urang, Tambangan, Hanura, Banjaran and Sanggi Village. This study showed that areas which are located on the coast are prone to malaria disease.