TY - JOUR
T1 - Communicating the High Susceptible Zone of COVID-19 and its Exposure to Population Number through a Web-GIS Dashboard for Indonesia Cases
AU - Supriatna, null
AU - Zulkarnain, Faris
AU - Ardiansyah,
AU - Rizqihandari, Nurrokhmah
AU - Semedi, Jarot Mulyo
AU - Indratmoko, Satria
AU - Rahatiningtyas, Nurul Sri
AU - Nurlambang, Triarko
AU - Dimyati, Muhammad
N1 - Funding Information:
This study was funded by the Consortium of Ministry of Research and Technology/National Research and Innovation Agency and Indonesia Endowment Fund for Education, Ministry of Finance, The Republic of Indonesia. We want to thank PT Infimap Geospatial Sistem for providing the People in Pixels data and undergraduate students from the Department of Geography, Faculty of Mathematics and Natural Science, Universitas Indonesia, for their work in updating the location of COVID-19 cases daily, ESRI Indonesia for providing us ArcGIS Online facility, and Badan Nasional Penanggulangan Bencana for reviewing our dashboard.
Publisher Copyright:
© 2022,International Journal of Technology. All Rights Reserved.
PY - 2022
Y1 - 2022
N2 - The Medical Geographic Information System (Medical GIS) application during the COVID-19 pandemic crisis has become influential in communicating disease surveillance for health practitioners and society. The Johns Hopkins University has extensively used a well-known Web-GIS dashboard to track the COVID-19 cases since January 22 and illustrates the location and number of confirmed COVID-19 cases. Unfortunately, the dashboard particularly for Indonesian cases is only represented by one point (dot map) placed on the centroid of the Indonesian archipelago. Further research can fill the gap in downscaling the geographical location data of COVID-19 cases to the cities or even the village level in Indonesia and communicating the susceptible zoning to society. We uplift the point COVID-19 cases data to susceptible zoning gathered from official COVID-19 government websites, process it using Geographic Information System analysis, and communicate it to society through a Web-GIS dashboard. Five datasets, i.e., population data, administrative boundary, Landsat 8 OLI satellite imagery, COVID-19 cases geographic location, transportation infrastructure, and crowded places location, are used to analyze the susceptible area. Due to different standard data sources from each province in Indonesia, we only present provinces in Java Island with complete COVID-19 cases data on villages-scale. The technical challenges and future improvement in developing the national dashboard of Web-GIS-based susceptibility dashboard are also discussed. The dashboard information would further add some essential information for society to explore their zone status in adapting to the “New Normal” using the SICOVID-19 dashboard from their computers or gadgets during the pandemic crisis.
AB - The Medical Geographic Information System (Medical GIS) application during the COVID-19 pandemic crisis has become influential in communicating disease surveillance for health practitioners and society. The Johns Hopkins University has extensively used a well-known Web-GIS dashboard to track the COVID-19 cases since January 22 and illustrates the location and number of confirmed COVID-19 cases. Unfortunately, the dashboard particularly for Indonesian cases is only represented by one point (dot map) placed on the centroid of the Indonesian archipelago. Further research can fill the gap in downscaling the geographical location data of COVID-19 cases to the cities or even the village level in Indonesia and communicating the susceptible zoning to society. We uplift the point COVID-19 cases data to susceptible zoning gathered from official COVID-19 government websites, process it using Geographic Information System analysis, and communicate it to society through a Web-GIS dashboard. Five datasets, i.e., population data, administrative boundary, Landsat 8 OLI satellite imagery, COVID-19 cases geographic location, transportation infrastructure, and crowded places location, are used to analyze the susceptible area. Due to different standard data sources from each province in Indonesia, we only present provinces in Java Island with complete COVID-19 cases data on villages-scale. The technical challenges and future improvement in developing the national dashboard of Web-GIS-based susceptibility dashboard are also discussed. The dashboard information would further add some essential information for society to explore their zone status in adapting to the “New Normal” using the SICOVID-19 dashboard from their computers or gadgets during the pandemic crisis.
KW - Covid-19
KW - Population exposure
KW - Susceptible area
KW - Web-gis dashboard
UR - http://www.scopus.com/inward/record.url?scp=85139993692&partnerID=8YFLogxK
U2 - 10.14716/ijtech.v13i4.4116
DO - 10.14716/ijtech.v13i4.4116
M3 - Article
AN - SCOPUS:85139993692
SN - 2086-9614
VL - 13
SP - 706
EP - 716
JO - International Journal of Technology
JF - International Journal of Technology
IS - 4
ER -