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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 Sau...

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.

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 ...

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.

For the development of passive microwave remote sensing techniques, brightness temperature information on the medium covering the Earth's surface under different conditions is required. An emission model is a useful tool for the estimation of the brightness temperature of the medium. If the medium is a snow pack, the microwave radiation emitted will depend on the physical temperature, crystal characteristics, stratification and density of the snow. The parameters of microwave emission models available for the retrieval of snow characteristics are highly dependent on local environmental and climatological conditions. The aim of this study was to compare the empirical Chang model with the semiempirical radiative transfer model of snow developed at Helsinki University of Technology (HUT) for snow depth (SD) retrieval for UK snow packs. In the first step we used the HUT model. The root mean square error (RMSE) was used to validate the accuracy of model estimates. The snow events from different days in 1995, 1...

Snow cover characteristics have significant effects on upwelling naturally emitted microwave radiation through processes of forward scattering. This study simulates numerically the electromagnetic responses from snow in the UK using the radiative transfer-based semiempirical model developed at the Helsinki University of Technology (HUT), which takes into account the influence of soil surface, forest canopy and atmosphere on space-borne observed brightness temperature by using empirical and semiempirical formulas. A sensitivity analysis of the HUT model was conducted to determine the most sensitive parameter affecting upwelling radiation from snow in the UK. The model-based results were compared with observed Special Sensor Microwave Imager (SSM/I) brightness temperatures to better understand the SSM/I response to snow. The available ensemble of data required for input to the HUT model comprise surface physical temperature, ground level pressure and water vapour content, forest stem volume and land cover water fraction. Based on the sensitivity analyses, numerical parameters representing physical snow pack quantities (e.g. snow grain size, snow moisture and snow depth (SD)) were varied and the method of root mean square error (RMSE) minimization was used to invert the SD. The HUT model was applied to different days in 3 months (23-31 January, 1-5 and 26-27 February and 1-7 March 1995) of records of daily SD and SSM/I observations. The results show that the HUT model both underestimates and overestimates SD prediction. For the month of January 1995, the HUT model underestimated SD with a bias of -0.59 cm, whereas for February and March 1995 the HUT model overestimated the SD with a bias of 1.89 cm and 1.64 cm, respectively. This study demonstrates that microwave remote sensing of snow can be used successfully in the UK, where most research on snow cover is conducted by using a visible and infrared radiometer. It is also evident from this work that application of algorithms to snow pack monitoring needs local calibration for effective and reasonable results.

Snow depth is one of the most important parameters for water resource management in those areas where snowfall is significant. Two different methods are applied here for snow monitoring using passive microwave data retrieved from the Special Sensor Microwave Imager (SSM/I). Since microwave sensors are least attenuated by the cloud cover, they have been widely used to retrieve snow cover data in a timely way. Passive microwave studies have shown that dry snow cover as well as mixed snow packs that contain free liquid water, affect naturally up-welling microwave radiation through forward scattering. In the first approach, brightness temperature (Tb) values at 18.7, 36.5 and 90 GHz vertical and horizontal frequencies for various snow packs are measured. In the second approach, the passive microwave response from snow packs of different physical conditions at 19, 37 and 85 GHz vertical and horizontal frequencies are modelled. Thus, various snow pack characteristics were estimated, the results indicat...