Image-based atmosphere correction using dark pixel subtraction technique in Penang Island, Malaysia / Wan Noni Afida Ab Manan, Arnis Asmat and Noordin Ahmad

Lack of study has found in emphasizing the appropriate chosen of atmospheric models with specific atmospheric condition. This study is attempting to answer whether selection of atmospheric models is based on regional atmospheric condition or geographic location. The proposed method is a combination of the radiative transfer equation and dark target subtraction technique. Two important atmospheric parameters in the radiative transfer equation which are visibility and aerosol loading are estimated from the image itself to be as an input in atmospheric modelling. ATCOR-2 was used to perform different atmospheric models (maritime and urban) which can represent regional climatic condition in Penang Island, Malaysia. By relating the determined aerosol optical thickness with visibility values, urban model at the visible (blue band) on image 2005 showed a high correlation coefficient which is r2 = 0.8896. It has been shown that determined the aerosol is highly correlated to the visibility range from 10 to 50 km. Study also found that optical satellite remotely sensed image data (Landsat TM blue band) can be used to determine the visibility value through the darkest pixel atmospheric correction algorithms

Determination Of Aerosol Optical Thickness From Spectral Sky Transmittance.

The objective of this study is to test the feasibility of the proposed technique for retrieving spectral aerosol optical thickness (AOT) from the spectral transmittance measurements. The measurements have been acquired around Penang Island, Malaysia. Ground-based measurements were made with a handheld spectroradiometer. The measured spectral transmittance data were then converted to AOT values 6 spectral bands between 400 and 900 nm. Spectral AOT maps were generated using Kriging interpolation method for the 6 spectral bands. Air quality map was produced using this technique

Application of Remote Sensing Instruments in Air Quality Monitoring in Malaysia

The use of remote sensing in detecting aerosol or air pollution is not widely applied in Malaysia. The large area of coverage provided by remote sensing satellite may well be the solution to the lack of spatial coverage by the local ground air quality monitoring stations. This article discusses the application of remote sensing instruments in air quality monitoring of Malaysia. The remote sensing data is validated using ground truths either from local ground air monitoring stations or the Aerosol Robotic Network (AERONET). The correlation between remote sensing is relatively good with R from 0.5 to 0.9 depending on the satellite used. The correlation is much improved using the mixed effects algorithm applied on MODIS Aerosol Optical Depth (AOD) data. Accuracy of predicted air quality data by remote sensing is generally tested using the Root Mean Squared Error (RMSE) against the ground truths data. Besides the Geographic Information System (GIS) tools are used in manipulating the data from both remote sensing and ground stations so as to produce meaningful results such as spatio-temporal pattern mapping of air pollution. Overall the results showed that the application of remote sensing instruments in air quality monitoring in Malaysia is very useful and can be improved further

Evaluation of aerosol optical thickness over Malaysia based on multi-source ground and satellite data

This study evaluates the spatiotemporal distribution of aerosol optical thickness (AOT) over Malaysia. The significance of aerosols in regional and global climate change assessment has become a pressing topic in recent climate discussions. Two different approaches are used in measuring AOT; satellite imagery and ground measurement approaches. However, the satellite approach is deemed the best way for monitoring the patterns and transport of aerosols largely due to its extensive spatial coverage and reliable repetitive measurements. The data in this study were obtained from a Sea-viewing Wide Field-of-view Sensor (SeaWiFS), a Multi-angle Imaging Spectroradiometer (MISR), and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors based on a NASA-operated Giovanni portal. Ground-based Aerosol Robotic Network (AERONET) datasets from two sites over the study area were also used. The results show that the highest AOT ground values of 1.93 and 2.00 were recorded in September 2015, at USM station and Kuching station, respectively. Throughout the 15 years of recorded data, the monthly average value of AOT reached its highest values in September, October, and November. In these months, the value of AOT went above 0.40, unlike in other months of the year. Significantly, the results indicate that Malaysian air quality can be evaluated based on AOT values, as these show the variation in optical properties of aerosol

An overview of mesoscale aerosol processes, comparisons, and validation studies from DRAGON networks

Over the past 24 years, the AErosol RObotic NETwork (AERONET) program has provided highly accurate remote-sensing characterization of aerosol optical and physical properties for an increasingly extensive geographic distribution including all continents and many oceanic island and coastal sites. The measurements and retrievals from the AERONET global network have addressed satellite and model validation needs very well, but there have been challenges in making comparisons to similar parameters from in situ surface and airborne measurements. Additionally, with improved spatial and temporal satellite remote sensing of aerosols, there is a need for higher spatial-resolution ground-based remote-sensing networks. An effort to address these needs resulted in a number of field campaign networks called Distributed Regional Aerosol Gridded Observation Networks (DRAGONs) that were designed to provide a database for in situ and remote-sensing comparison and analysis of local to mesoscale variability in aerosol properties. This paper describes the DRAGON deployments that will continue to contribute to the growing body of research related to meso- and microscale aerosol features and processes. The research presented in this special issue illustrates the diversity of topics that has resulted from the application of data from these networks