The air quality indicator approximated by satellite measurements is known as an atmospheric particulate loading, which is evaluated in terms of the columnar optical thickness of aerosol scattering. The effect brought by particulate pollution has gained interest among researchers to study aerosol and particulate matter. In this study we presents the potentiality of retrieving concentrations of particulate matter with diameters less than ten micrometer (PM10) in the atmosphere using the Landsat 7 ETM+ slc-off satellite images over Makkah, Mina and Arafah. A multispectral algorithm is developed by assuming that surface condition of study area are lambertian and homogeneous. In situ PM10 measurements were collected using DustTrak aerosol monitor 8520 and their locations were determined by a handheld global positioning system (GPS). The multispectral algorithm model shows that PM10 high during Hajj season compared to other season. The retrieval dataset gives the accuracy > 0.8 of R coefficient value over Makkah, Mina and Arafah. These results provide confidence that the multispectral algorithm PM10 models can make accurate predictions of the concentrations of PM10.

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Penang Island is an important economic center in Malaysia and most of its population live in the coastal areas. Although previous studies have shown that it is vulnerable to rising sea levels, the combination of sea-level rise and local land subsidence would be devastating. Therefore, the objective of this study is to apply the local land subsidence model to estimate the inundated areas which relate to sea level rise by 2100. Land subsidence is quantified by the SBAS-InSAR technique on the basis of Sentinel-1 radar images for both ascending and descending tracks. For the first time, the geostatistical analyst method is used to merge the different track results and create the land subsidence models, the results show this method can maximize land deformation fields and minimize deformation errors. According to the land deformation results, all of the coastlines in the east of the island have differing medium levels of subsidence, especially in reclaimed lands and building areas. Lastly, the bathtub model is used to quantify the inundated areas by combing regional sea-level rise projection and local land subsidence models under CoastalDEM in 2100 projections. The results of this study indicate land subsidence that would increase 2.0% and 5.9% of the inundated area based on the different scenarios by 2100 projections.

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Environmental monitoring through the method of traditional ship sampling is time consuming and requires a high survey cost. This study uses an empirical model, based on actual water quality of total suspended solids (TSS) measurements from the Prai River estuary Penang, Malaysia, to predict TSS based on optical properties of digital camera imagery. 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 constituent's concentrations. Water samples were simultaneously collected with the airborne image acquisition and analyzed later in the laboratory. These locations were determined by using a handheld GPS. The digital numbers for each band were extracted corresponding to the sea-truth locations and were later used for calibration of the water quality algorithm. The efficiency of the proposed algorithm was investigated, based on the observations of correlation coefficient (R) and root-mean-square deviations (RMS) with the sea-truth data. This algorithm was then used to map the TSS concentration in Prai River estuary, Penang, Malaysia. The TSS map was color-coded and geometrically corrected for visual interpretation. This study indicates that TSS mapping can be carried out using digital camera imageries.