N. M. Saleh

Multispectral absorption algorithm for retrieving TSS concentrations in water

The environmental problems caused by the increase of pollutant. It is the result of industrial waste and environmental accidents. One of the main sources of water pollution is suspended solids. When these suspended particles settle to the bottom of a water body, they become sediments. Optical methods offer two possibilities: scattering and transmission. The design of optical sensor systems is based on the interaction between the photons of the electromagnetic radiation and suspended particles in water. Pollution usually results in higher total suspended solids (TSS) concentrations or turbidity. Water pollution is caused by any chemical, physical or biological change in the quality of water. Suspended solids are small particles of solid pollutants that float on the surface of, or are suspended in waters. Water pollution has become increasingly critical in this present-day, whether in the developed or the developing countries. Total suspended solids (TSS) in water can be detected by a number of optical sensing techniques, which involve light interaction with suspended particles in water. The measurements of the transmittance give a method for determining the concentration of the particles. The objectives of this study are to derive multispectral absorption algorithm and to develop an optical system, which is based on absorption measurements for measuring the concentration of total suspended solids,TSS in water. The multispectral absorption algorithm has been developed and a new multispectral optical sensor system designed for measuring total suspended solids TSS concentrations in polluted water. The development of the optical algorithm was based on the Beer-Lambert law. Firstly, the water samples used for calibration were filtered and dried to obtain the TSS values. In this study, three light emitting diodes were used as sensing emitters (sources) and a silicon phototransistor as radiations detector. The radiation values were determined from the output voltage readings of the sensor system. An electronic circuit was designed and the readings were measured by using a digital multimeter. The major advantages in using an LED as the light sources are its relatively low power consumption and ability to be modulated electronically at rapid rates. Standard polluted samples were prepared for sensors calibration. As the concentration of total suspended solids P was increased, the intensity of the transmitted light decreased. The level of the photocurrent was linearly proportional to the pollutants concentration. The proposed multispectral algorithm was calibrated using the measured parameters. Its accuracy was determined based on correlation coefficient,R and the value of the root-mean square errors,RMSE. The results showed a good correlation between the radiation values and the total suspended solids concentrations. This optical system provides various advantages over the current portable turbidity meter, which uses a single infrared source. The main advantage is its capability provide water pollution levels accurately (i.e. total suspended solids concentration). It only requires inexpensive components and can be assembled easily. The proposed algorithm produced a high correlation coefficient and low root mean square error value. This new methodology is very important for measuring and monitoring TSS in polluted water areas.

Algorithm for TSS Mapping Using Satellite Data for Penang Island, Malaysia

The traditional sampling method for environmental monitoring of aerosols is time consuming and expensive. Remote sensing data have been widely used in environmental studies like land cover change, flood observation, environmental pollution monitoring. This study is dealing with obtaining water pollution using Landsat TM data over Penang Strait, Malaysia. With the availability of remotely sensed and in situ data sets the derivable geophysical parameters is sediment (suspended matter) concentration. The proposed algorithm is based on the reflectance model that is a function of the inherent optical properties of water, which can be related to its constituents concentrations. Regression and accuracy analysis is performed using SPSS analysis software. Water samples locations were determined using a handheld GPS. The digital numbers were extracted corresponding to the ground-truth locations for each band was converted into radiance and reflectance and later used for the calibration of the developed algorithm. The efficiency of the present proposed algorithm, in comparison to other forms of algorithm, was also investigated. Based on the values of the correlation coefficient (R) and root-mean-square deviation (RMS), the proposed algorithm is considered superior. The proposed algorithm is considered superior to other tested algorithms based on the values of the correlation coefficient, R=0.94 and root-mean-square error, RMS=5 mg/l. The calibrated TSS algorithm was used to generate the water quality map. The TSS map was color-coded and geometrically corrected for visual interpretation.

Air Quality Derivation utilizing Landsat TM image over Penang, Malaysia

This paper outlines recent developments in optical remote sensing of Landsat TM data for air quality monitoring for atmospheric particulate matter having a diameter less than 10-micro meter (PM10). The objective of this study is to evaluate the performance of the developed algorithm and suitability of remote sensing data for PM10 mapping. We used a DustTrak Aerosol Monitor 8520 to collect in situ data. The PM10 data were collected simultaneously during the satellite Landsat overpass the study area. An algorithm has been developed based on the optical aerosol characteristic in the atmosphere to estimate PM10 over Penang Island, Malaysia. The digital numbers were determined corresponding to the ground-truth locations for each band and then converted to radiance and reflectance values. The atmospheric reflectance values was extracted from the satellite observed reflectance values subtracters by the amount given by the surface reflectance. The surface refleatance values were retrieved using ATCOR2 in the PCI Geomatica 9.1 image processing software. The atmospheric reflectance values were later used for PM10 mapping using the calibrated algorithm. Results from this research have indicated that PM10 data have positive correlation with atmospheric reflectance in two visible bands (Red and Blue band). Finally, the map of pollution concentration generated from the satellite image using the proposed algorithm to illustrate spatial distribution pattern of air pollution for the study area. The proposed algorithm produced high correlation coefficient, R, and low root-mean-square, RMS, values. The concentrations of PM10 are high in the industrial zones and urban areas of Penang, Malaysia.

Application of Remote Sensing for Land surface temperature retrieval over Mecca

A method to retrieve the land surface temperature (LST) over Mecca, Saudi Arabia are developed using band 6 of the Landsat TM thermal channel. The objective of this study was to focus on the estimation of the LST from Landsat TM 5 imageries. The data used was captured by Thematic Mapper (TM) sensor onboard the Landsat 5 satellite. Landsat TM has only one thermal band, and therefore the spilt-window algorithm cannot be used for the retrieval of LST. In this study, we are proposed a single channel algorithm for retrieving LST. The land surface emissivity and solar angle values are needed in order to apply these in the proposed algorithm. The surface emissivity values were computed based on the NDVI values. The correlation between the LST and the brightness temperature had increased significantly after the surface emissivity and solar zenith angle were included in the algorithm. The reference values LST were determined using ATCOR2_T in the PCI Geomatica image 9.1 processing software for algorithm calibration. The results indicate that the single channel algorithm was suitable for retrieving LST values from remotely sensed data.

Aerosol Characterization over Penang, Malaysia Using Aerosol Robotic Network (AERONET)

Ground-based solar photometer measurements were utilized in the ambiance of Universiti Sains Malaysia (USM) Penang and Universiti Teknologi MARA (UiTM) Penang during September-November 2013 with a specific end goal to portray the characteristics of the local atmospheric environment. This both sites were established as being component of the collaborative work of the Seven South East Asian Studies (7SEAS) regional aerosol measurement project. This study concentrates on the Angstrom exponent (α), that is the gradient of the logarithm of the aerosol optical depth (AOD) against the logarithm of the wavelength as well as being commonly used to characterize the wavelength reliance of AOD and to furnish some critical data on the aerosol size distribution. In most situations fine mode aerosols appear to be the predominant category with marginally substantial contributions of coarse mode particles resulting from the particle growing, blending processes with other aerosol types, precipitation factors and relative distance to the seashore.

Modeling of aerosol and cloud optical depth

We have applied regression model together with statistical test, Pearson Correlation, to examine the relationships between aerosol optical depth (AOD), cloud optical depth (COD) and water vapor retrieved by Moderate Resolution Imaging Spectrometer (MODIS) in 2009 over Malaysia. It is shown that the relationship between water vapor in clear sky and AOD mean showed the highest significant compared to the others. Pearson Correlation showed that AOD and Water Vapor (Clear sky) have positive correlation but COD and water vapor (cloudy) have negative correlation, which both have significant correlation (p<0.01). Such regression model and correlation play an essential part in order to quantify the contributions in influencing climate change and global warming. However, analysis of the complex connection of AOD, COD and water vapor should be made with great care and further work is needed.

Atmospheric transmittance modeling in urban and rural area

The properties of atmospheric spectral transmittance over Malaysia are studied using MODTRAN. The atmospheric propagation is being treated as electromagnetic radiation which ranged from 100–50000 cm−1 with a spectral resolution of 1 cm−1. Based on the study area factor, tropical model is being used in this study. The results demonstrated the characteristics of atmospheric transmittance obtained using MODTRAN which showed the absorption and absorptive properties in the atmospheric layer.

Aerosol optical thickness retrieval by using a handheld spectroradiometer over Penang Island, Malaysia

Atmospheric components (aerosol and molecules) scatter and absorb solar radiation. This study investigated the used of a handheld spectroradiometer for the retrieval of atmospheric optical thickness (AOT) values over Penang Island derives this period. The objective of this study is to introduce a new technique for retrieval of aerosol optical thickness (AOT) for air quality determination. Measured spectroradiometer data was used to calculate the aerosol optical thickness (AOT) values at the earth surface. The transmittance values were measured using a handheld spectroradiometer over Penang Island. Particulate matters of size less than 2.5 micron (PM2.5) were collected simultaneously with the acquisition of the transmittance measurements. The results of the calculated AOT were used to retrieve the air quality at Penang, Malaysia. The retrieved AOT data were linearly correlated with the particulate matter of less than 2.5 micro meter (PM2.5). An AOT map and PM10 map were generated using interpolation technique. The relationship between AOT and PM10 was investigated and we obtained a linear relationship between these two parameters. Finally, an interpolating technique was used to generate a PM2.5 map over Penang Island.

EASI Modelling Algorithms for Aerosol-Cloud Distribution Analysis

Algorithms to distinguish between clouds and aerosols are important in the environmental and remote sensing study. The colour-modulated image from cloud aerosol lidar and infrared pathfinder satellite observation (CALIPSO) has been analysed in this study. CALIPSO is currently obtaining global aerosol and cloud measurements from space. We study the possibility to apply EASI modelling algorithms to differentiate aerosols and clouds in the CALIPSO image. This image processing method has shown good outcome for visualization analysis.

Algorithm for PM2.5 Mapping over Penang Island, Malaysia, Using SPOT Satellite Data

Air pollution is an important issue being monitored and regulated in industrial and developing cities. In this study, we explored the relationship between particulate matters of size less than 2.5 micron (PM 2.5) derived from the SPOT using regression technique. The aim of this study was to evaluate the high spatial resolution satellite data for air quality mapping by using FLAASH software. The corresponding PM 2.5 data were measured simultaneously with the acquired satellite scene and their locations were determined using a handheld Global Positioning System (GPS). Due to the fact that the current commercial aerosol retrieval method (FLAASH) was designed to work reasonably well over land, but is not accurate for water applications, adjustments had to be made to the software to optimize it for reflectance retrieval over water. In-situ reflectance spectra will be plot against spectra derived from the atmospherically corrected images. In this study, we ensure that all the atmospherically corrected spectra match reasonably with the in-situ spectra. We have developed a new algorithm that can effectively estimate the spatial distribution of atmospheric aerosols and retrieve surface reflectance from remotely sensed imagery under general atmospheric and surface conditions. The algorithm was developed base on the aerosol characteristics in the atmosphere. The efficiency of the developed algorithm, in comparison to other forms of algorithm, will be investigated in this study. Results indicate that there is a good correlation between the satellites derived PM 2.5 and the measured PM 2.5. This study shows the potential of using the thermal infrared data for air quality mapping. The finding obtained by this study indicates that the FLAASH can be used to retrieve air quality information for remotely sensed data.