Open AccessSpatial modelling of particular matter 10 distribution in Bandung City
Author(s) -
Faza Arista,
Ratna Saraswati,
Adi Wibowo
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/561/1/012047
Subject(s) - normalized difference vegetation index , metropolitan area , environmental science , vegetation (pathology) , correlation coefficient , regression analysis , spatial distribution , index (typography) , geography , enhanced vegetation index , air quality index , physical geography , statistics , vegetation index , leaf area index , mathematics , meteorology , remote sensing , ecology , medicine , archaeology , pathology , world wide web , computer science , biology
Air pollution is a significant problem that occurs in urban areas. Bandung city, as a metropolitan city, continues to experience an increase in population growth, which has led to an increase in the built-up area. The increased built-up area will lead to a decrease in the area of green, which was causing a decrease in air quality. The study aims to analyze the spatial distribution of PM 10 in Bandung city and its relationship with the distribution of land surface temperature, building density, and vegetation density. The research used pollutant levels data and Landsat 8 Imagery in the dry month of 2018. The analysis used were IDW interpolation, LST, NDBI, NDVI, correlation, and statistical regression tests. This research concluded that PM 10 distribution model in the dry month of 2018, high pollutant levels are in the characteristics of the region with high surface temperature and index density, and a low index of vegetation density while low pollutant levels are in the characteristics of the region with surface temperature and density index value low buildings, and a high index value of vegetation density. Correlation results indicate an association with each variable. Based on the Pearson coefficient, the relationship between variables is at a moderate level. The regression results state that there is a significant influence between land surface temperature, vegetation index, and building index on the distribution patterns PM 10 in the Bandung city.