Spatial Analysis of Dengue Virus in the Highland and Lowland Areas Using Remote Sensing Technology

被引:0
|
作者
Hasyim, Abdul Wahid [1 ]
Maulidi, Chairul [1 ]
Hernawan, Fendy Putra [1 ]
Harits, Akhmad [1 ]
机构
[1] Brawijaya Univ, Urban & Reg Dept, Fac Engn, Malang 65145, Indonesia
关键词
Dengue Hemorrhagic Fever (DHF); Remote Sensing; Crosstab Analysis;
D O I
10.1166/asl.2018.11067
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
East Java was endemic dengue area which often generates the extraordinary event. Health Depatment of East Java Province showed the number cases of dengue fever in 2015 about 20,832 cases. This shows an increase 124.31% if compared to the same month in 2014 with 9,287 cases. We analyzed and compared case of Dengue Hemorrhagic Fever (DHF) among the highland and lowland areas especially in Malang and Sumenep to determine the factors that influence dengue cases. Geographical information system, remote sensing images technology, and related data were used to classify city areas according to land cover, land surface temperature, rainfall, population density and bulding density. Dengue cases on both areas were dominated by high population density, high rainfall and low vegetation cover. Crosstab analysis on the highland showed population density and built up areas correlated significantly with dengue cases. On the lowland area, building density and rainfall affected with dengue cases.
引用
收藏
页码:2814 / 2818
页数:5
相关论文
共 50 条
  • [31] Remote Sensing Data Feature Analysis Using Spatial Linear Embedding (SLE)
    Xue, Lifang
    Yi, Xiushuang
    Liu, Xiumei
    Li, Jie
    [J]. PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON MECHATRONICS, MATERIALS, CHEMISTRY AND COMPUTER ENGINEERING 2015 (ICMMCCE 2015), 2015, 39 : 91 - 94
  • [32] Analysis on topological features in spatial distribution pattern using GIS and remote sensing
    Li, Bingxin
    Yu, Anbang
    Liu, Tong
    Guo, Sulin
    [J]. INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL, 2021, 38 (3-4) : 332 - 341
  • [33] Tropical cyclone disaster management using remote sensing and spatial analysis: A review
    Hoque, Muhammad Al-Amin
    Phinn, Stuart
    Roelfsema, Chris
    Childs, Iraphne
    [J]. INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION, 2017, 22 : 345 - 354
  • [34] SPATIAL SCALE EFFECT ON VEGETATION PHENOLOGICAL ANALYSIS USING REMOTE SENSING DATA
    Wang, Yiting
    Xie, Donghui
    Hu, Ronghai
    Yan, Guangjian
    [J]. 2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2016, : 1329 - 1332
  • [35] Classification and spatial analysis of eastern hemlock health using remote sensing and GIS
    Bonneau, LR
    Shields, KS
    Civco, DL
    Mikus, DR
    [J]. SYMPOSIUM ON SUSTAINABLE MANAGEMENT OF HEMLOCK ECOSYSTEMS IN EASTERN NORTH AMERICA, PROCEEDINGS, 2000, 267 : 176 - 176
  • [36] Spatial Modeling of Asthma-Prone Areas Using Remote Sensing and Ensemble Machine Learning Algorithms
    Razavi-Termeh, Seyed Vahid
    Sadeghi-Niaraki, Abolghasem
    Choi, Soo-Mi
    [J]. REMOTE SENSING, 2021, 13 (16)
  • [37] Spatial partitioning of biomass and diversity in a lowland Bolivian forest:: Linking field and remote sensing measurements
    Broadbent, Eben N.
    Asner, Gregory P.
    Pena-Claros, Marielos
    Palace, Michael
    Soriano, Marlene
    [J]. FOREST ECOLOGY AND MANAGEMENT, 2008, 255 (07) : 2602 - 2616
  • [38] Volumetric Analysis of Reservoirs in Drought-Prone Areas Using Remote Sensing Products
    Bhagwat, Tejas
    Klein, Igor
    Huth, Juliane
    Leinenkugel, Patrick
    [J]. REMOTE SENSING, 2019, 11 (17)
  • [39] Dengue early warning systems using environmental remote sensing data
    Rahman, Md Z.
    Roytman, Leonid
    Kadik, Abdelhamid
    Rosy, Dilara A.
    Nandi, Pradipta
    Shibli, Mohammed Shofiullah
    [J]. SITUATION AWARENESS IN DEGRADED ENVIRONMENTS 2020, 2020, 11424
  • [40] Environmental Data Analysis and Remote Sensing for Early Detection of Dengue and Malaria
    Rahman, Md Z.
    Roytman, Leonid
    Kadik, Abdelhamid
    Rosy, Dilara A.
    [J]. SENSING TECHNOLOGIES FOR GLOBAL HEALTH, MILITARY MEDICINE, AND ENVIRONMENTAL MONITORING IV, 2014, 9112