TY - JOUR
T1 - Spatial model of Particulate Matter PM10in Bekasi City, West Java Province using Landsat-8
AU - Tamara, D.
AU - Wibowo, A.
AU - Shidiq, I. P.A.
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2023
Y1 - 2023
N2 - Bekasi was the city with the largest population in West Java Province. In Bekasi, movement mainly used vehicles. This research aims to analyze PM10 spatial pattern in Bekasi City and validity spatial model of PM10 from vehicle volume and Landsat 8 with PM10 from passive sampler as validator. This research used descriptive spatial and statistical root mean square error (RMSE) analysis. Based on PM10 from vehicle volume, large capacity arterial roads covered poorer air quality index. Based on PM10 from Landsat 8, it happened in opposite phenomena. Regarding congestion traffic on small-capacity arterial roads, some points of vehicle volume measurement were congested, and others were not. PM10 with an unhealthy air quality index also could be sourced from residential, commercial & services, and industrial buildings. Then, RMSE spatial model of PM10 from vehicle volume had lowered error than a spatial model of PM10 from Landsat 8. However, if a further analysis was done by considering spatial characteristics (such as land used), several area models were located on the same land used. This research showed that a combination of model errors and their relation to spatial characteristics could be a new approach to assessing model performance.
AB - Bekasi was the city with the largest population in West Java Province. In Bekasi, movement mainly used vehicles. This research aims to analyze PM10 spatial pattern in Bekasi City and validity spatial model of PM10 from vehicle volume and Landsat 8 with PM10 from passive sampler as validator. This research used descriptive spatial and statistical root mean square error (RMSE) analysis. Based on PM10 from vehicle volume, large capacity arterial roads covered poorer air quality index. Based on PM10 from Landsat 8, it happened in opposite phenomena. Regarding congestion traffic on small-capacity arterial roads, some points of vehicle volume measurement were congested, and others were not. PM10 with an unhealthy air quality index also could be sourced from residential, commercial & services, and industrial buildings. Then, RMSE spatial model of PM10 from vehicle volume had lowered error than a spatial model of PM10 from Landsat 8. However, if a further analysis was done by considering spatial characteristics (such as land used), several area models were located on the same land used. This research showed that a combination of model errors and their relation to spatial characteristics could be a new approach to assessing model performance.
UR - http://www.scopus.com/inward/record.url?scp=85164736532&partnerID=8YFLogxK
U2 - 10.1088/1755-1315/1190/1/012002
DO - 10.1088/1755-1315/1190/1/012002
M3 - Conference article
AN - SCOPUS:85164736532
SN - 1755-1307
VL - 1190
JO - IOP Conference Series: Earth and Environmental Science
JF - IOP Conference Series: Earth and Environmental Science
IS - 1
M1 - 012002
T2 - 2022 International Conference on Anthropocene, Global Environmental Change and Powerful Geography, ICoAGPG 2022
Y2 - 27 September 2022
ER -