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Spatio-temporal assessment of aerosol optical depth from Himawari-8 satellite data over Malaysia

Kamarul Zaman, Nurul Amalin Fatihah and Kanniah, Kasturi Devi (2020) Spatio-temporal assessment of aerosol optical depth from Himawari-8 satellite data over Malaysia. In: 10th IGRSM International Conference and Exhibition on Geospatial and Remote, IGRSM 2020, 20 October 2020 - 21 October 2020, Kuala Lumpur, Malaysia.

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Official URL: http://dx.doi.org/10.1088/1755-1315/540/1/012053

Abstract

Aerosols, particulate matters and air pollution are significant atmospheric issues in the Southeast Asia (SEA) countries particularly Malaysia. Despite their importance, data to investigate their spatio-temporal variation, estimating their abundance and modelling the trend are not widely available due to financial constraints and technical expertise. Remote sensing data are alternative solution to the limited data available from ground stations. One of the latest remotely sensed Aerosol Optical depth (AOD) data available is from Himawari-8 satellite that provides high temporal resolution data (every 10 minutes) at moderate spatial resolution of 5 km. Nevertheless, the robustness of these data for the tropical region has not yet been validated yet. This study aimed at assessing the performance of Himawari-8 AOD L2 product by (i) comparing its absolute AOD values against AOD retrieved from AERONET stations and (ii) analysing the spatial and temporal patterns of the AOD data. The AERONET data were averaged for ±5 min of the Himawari-8 overpass and matched to each other using statistical measures i.e. Correlation, Root mean square error (RMSE), Relative bias (RB) and Mean Absolute Error (MAE). Preliminary results of the analysis provided a coefficient of determination (R2) value = 0.31, RMSE = 0.16, and MAE = 0.15. The Himawari-8 AOD product is found to be overestimated the AOD values by 24.19%. Nevertheless, Himawari-8 AOD L2 product is able to exhibit similar spatial and temporal patterns compared to other remotely sensed AOD data such as that of MODIS. The high temporal resolution of Himawari data will facilitate frequent monitoring of air pollution in this region.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:root mean square errors, spatial and temporal patterns, spatio-temporal variation, statistical measures
Subjects:Q Science > Q Science (General)
T Technology > TH Building construction > TH434-437 Quantity surveying
Divisions:Built Environment
ID Code:91261
Deposited By: Yanti Mohd Shah
Deposited On:30 Jun 2021 12:07
Last Modified:30 Jun 2021 12:07

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