Mohsin Jamil Butt

Estimation of Light Pollution Using Satellite Remote Sensing and Geographic Information System Techniques

The primary focus of this research is to estimate light pollution in the urban and suburban regions of Pakistan with the help of satellite remote sensing (SRS) and geographic information system (GIS) techniques. Analog maps and multi-temporal nighttime images of the Defense Meteorological Satellite Program (DMSP) onboard Operational Linescan System (OLS) sensor were used in this study. A series of direct and indirect light pollution maps of the study area were generated and analyzed. The results of the study show that in the urban environment, light pollution is mainly due to artificial nightlight sources.

Assessment of AOD variability over Saudi Arabia using MODIS Deep Blue products

The aim of this study is to investigate the variability of aerosol over The Kingdom of Saudi Arabia. For this analysis, Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue (DB) Aerosol Optical Depth (AOD) product from Terra and Aqua satellites for the years 2000-2013 is used. The product is validated using AERONET data from ground stations, which are situated at Solar Village Riyadh and King Abdullah University of Science and Technology (KAUST) Jeddah. The results show that both Terra and Aqua satellites exhibit a tendency to show the spatial variation of AOD with Aqua being better than Terra to represent the ground based AOD measurements over the study region. The results also show that the eastern, central, and southern regions of the country have a high concentration of AOD during the study period. The validation results show the highest correlation coefficient between Aqua and KAUST data with a value of 0.79, whilst the Aqua and Solar Village based AOD indicates the lowest Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) values which are, 0.17 and 0.12 respectively. Furthermore, the Relative Mean Bias (RMB) based analysis show that the DB algorithm overestimates the AOD when using Terra and Solar Village data, while it underestimates the AOD when using Aqua with Solar Village and KAUST data. The RMB value for Aqua and Solar Village data indicates that the DB algorithm is close to normal in the study region.

MODIS satellite data evaluation for sand and dust storm monitoring in Saudi Arabia

ABSTRACT The impacts of wind-blown desert sand and dust are a major concern of environmental and climate study due to their global extent. This article investigates the sand and dust storms detection in Saudi Arabia using Moderate Resolution Imaging Spectroradiometer (MODIS) data, both from Terra and Aqua satellite systems for the years 2002–2011. Normalized Difference Dust Index (NDDI) is applied for the detection of sand and dust storms whilst MODIS band 31 is applied to discriminate atmospheric sand and dust from that present on the ground. In addition, the data from Meteosat satellite, AERONET station, and meteorological stations are used to validate NDDI-based sand and dust storm events. The results of the study show that NDDI can successfully identify and differentiate sand and dust storms from clouds whilst MODIS band 31 can discriminate aerial and surface sand and dust over Saudi Arabia. The results also show that the multi-source data, that is MODIS, Meteosat, AERONET, and meteorological stations, can be very valuable for tracking sand and dust storm events. As no such attempt in the past has been made in Saudi Arabia, it is envisaged that the results of this study will be helpful in planning remote-sensing data for the climate change study in the region.

Application of geographical information system for mapping/monitoring seismological hazards in Pakistan

This study attempts to use the geographic information system (GIS) technique to map and understand the tectonics and crustal structures of Pakistan. Maps of surficial tectonic features and seismological parameters including Moho depth, Pn velocity and Pg velocity are complied. Based on the seismological data-set of the country the earthquake hazard map of Pakistan is also presented by applying regression technique on seismological, geological and topographical parameters. A case study of 8 October 2005 earthquake is used to validate the hazard map. It is envisaged that the developed GIS database would help policy-makers and scientists in natural hazard evaluation, seismic risk assessment and understanding of earthquake occurrences in Pakistan.

Exploitation of Landsat data for snow zonation mapping in the Hindukush, Karakoram and Himalaya (HKH) region of Pakistan

Abstract In the Hindukush, Karakoram and Himalaya (HKH) region of Pakistan, many glaciological variables are still not known due to the remoteness and harsh weather conditions of the area. A remote sensing technique is therefore applied to map the snow zonation in the HKH region. Landsat 7 ETM+ data for the year 2003 are used in this study. Image classification and image processing techniques are applied to map, for the first time, the major snow zones in the HKH region. Six classes are identified: the results show that the area covered by the highest-altitude snow (Snow I), lower-altitude snow (Snow II), bare ice, debris-covered ice, wet snow and shadow is 21 529.42, 22 472.58, 8696.41, 8038.75, 12 159.37 and 7322.30 km2, respectively. The study also indicates that the equilibrium line altitude (ELA) lies between 5000 and 5500 m above sea level, with an accumulation area ratio (AAR) of 0.60. Citation Butt, M.J., 2013. Exploitation of Landsat data for snow zonation mapping in the Hindukush, Karakoram and Himalaya (HKH) region of Pakistan. Hydrological Sciences Journal, 58 (5), 1088–1096.