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Malik A.,Pakistan Space and Upper Atmosphere Research Commission SUPARCO
Proceedings of the International Astronautical Congress, IAC | Year: 2013

Free Space Optics (FSO) is a line-of-sight technology that transmits a modulated beam of visible or infrared light using an LED or LASER point source. Any communication that could be done through optic fiber is possible using FSO with an advantage that it avoids excessive deployment expenditure without requiring trenching. Lastly, due to extremely narrow laser beam wavelengths of the order of 1550 nm, multiple free space optical links can be installed in a given locality. However their reliability factor due to variations in atmospheric channel makes them the least deployed solutions so far. The main design challenge in FSO communications is Scintillation which pertains to random variation in the irradiance of received optical laser beam caused by environmental turbulence. For weak atmospheric turbulence, the variation can be approximated as a Lognormal distributed process. In this paper we propose softwarebased framing and forward error-correction scheme using rate-1/4 Low-Density Parity Check codes. Results suggest that significant performance gains in terms of Bit Error Rate/Frame Error Rate and Signal-to-Noise ratio could be achieved through the use of rate-1/4 regular LDPC codes in a lognormal distributed atmospheric fading channel. ©2013 by the International Astronautical Federation. All rights reserved. Source


Ali A.,University of Twente | Ali A.,Pakistan Space and Upper Atmosphere Research Commission SUPARCO | de Bie C.A.J.M.,University of Twente | Skidmore A.K.,University of Twente
International Journal of Applied Earth Observation and Geoinformation | Year: 2013

Cloud contamination impacts on the quality of hyper-temporal NDVI imagery and its subsequent interpretation. Short-duration cloud impacts are easily removed by using quality flags and an upper envelope filter, but long-duration cloud contamination of NDVI imagery remains. In this paper, an approach that goes beyond the use of quality flags and upper envelope filtering is tested to detect when and where long-duration clouds are responsible for unreliable NDVI readings, so that a user can flag those data as missing. The study is based on MODIS Terra and the combined Terra-Aqua 16-day NDVI product for the south of Ghana, where persistent cloud cover occurs throughout the year. The combined product could be assumed to have less cloud contamination, since it is based on two images per day. Short-duration cloud effects were removed from the two products through using the adaptive Savitzky-Golay filter. Then for each 'cleaned' product an unsupervised classified map was prepared using the ISODATA algorithm, and, by class, plots were prepared to depict changes over time of the means and the standard deviations in NDVI values. By comparing plots of similar classes, long-duration cloud contamination appeared to display a decline in mean NDVI below the lower limit 95% confidence interval with a coinciding increase in standard deviation above the upper limit 95% confidence interval. Regression analysis was carried out per NDVI class in two randomly selected groups in order to statistically test standard deviation values related to long-duration cloud contamination. A decline in seasonal NDVI values (growing season) were below the lower limit of 95% confidence interval as well as a concurrent increase in standard deviation values above the upper limit of the 95% confidence interval were noted in 34 NDVI classes. The regression analysis results showed that differences in NDVI class values between the Terra and the Terra-Aqua imagery were significantly correlated (p < 0.05) with the corresponding standard deviation values of the Terra imagery in case of all NDVI classes of two selected NDVI groups. The method successfully detects long-duration cloud contamination that results in unreliable NDVI values. The approach offers scientists interested in time series analysis a method of masking by area (class) the periods when pre-cleaned NDVI values remain affected by clouds. The approach requires no additional data for execution purposes but involves unsupervised classification of the imagery to carry out the evaluation of class-specific mean NDVI and standard deviation values over time. © 2013 Elsevier B.V. Source


Bashir S.M.A.,Institute of Space Technology | Bashir S.M.A.,Pakistan Space and Upper Atmosphere Research Commission SUPARCO | Ghouri F.A.K.,University of Karachi
PLoS ONE | Year: 2014

Perspective texture synthesis has great significance in many fields like video editing, scene capturing etc., due to its ability to read and control global feature information. In this paper, we present a novel example-based, specifically energy optimization-based algorithm, to synthesize perspective textures. Energy optimization technique is a pixel-based approach, so it's time-consuming. We improve it from two aspects with the purpose of achieving faster synthesis and high quality. Firstly, we change this pixel-based technique by replacing the pixel computation with a little patch. Secondly, we present a novel technique to accelerate searching nearest neighborhoods in energy optimization. Using k- means clustering technique to build a search tree to accelerate the search. Hence, we make use of principal component analysis (PCA) technique to reduce dimensions of input vectors. The high quality results prove that our approach is feasible. Besides, our proposed algorithm needs shorter time relative to other similar methods. © 2014 Bashir Ghouri. Source


Ali Z.,Pakistan Space and Upper Atmosphere Research Commission SUPARCO | Ali Z.,University of Twente | Tuladhar A.,University of Twente | Zevenbergen J.,University of Twente
International Journal of Applied Earth Observation and Geoinformation | Year: 2012

Updating cadastral information is crucial for recording land ownership and property division changes in a timely fashioned manner. In most cases, the existing cadastral maps do not provide up-to-date information on land parcel boundaries. Such a situation demands that all the cadastral data and parcel boundaries information in these maps to be updated in a timely fashion. The existing techniques for acquiring cadastral information are discipline-oriented based on different disciplines such as geodesy, surveying, and photogrammetry. All these techniques require a large number of manpower, time, and cost when they are carried out separately. There is a need to integrate these techniques for acquiring cadastral information to update the existing cadastral data and (re)produce cadastral maps in an efficient manner. To reduce the time and cost involved in cadastral data acquisition, this study develops an integrated approach by integrating global position system (GPS) data, remote sensing (RS) imagery, and existing cadastral maps. For this purpose, the panchromatic image with 0.6 m spatial resolution and the corresponding multispectral image with 2.4 m spatial resolution and 3 spectral bands from QuickBird satellite were used. A digital elevation model (DEM) was extracted from SPOT-5 stereopairs and some ground control points (GCPs) were also used for ortho-rectifying the QuickBird images. After ortho-rectifying these images and registering the multi-spectral image to the panchromatic image, fusion between them was attained to get good quality multi-spectral images of these two study areas with 0.6 m spatial resolution. Cadastral parcel boundaries were then identified on QuickBird images of the two study areas via visual interpretation using participatory-GIS (PGIS) technique. The regions of study are the urban and rural areas of Peshawar and Swabi districts in the Khyber Pakhtunkhwa province of Pakistan. The results are the creation of updated cadastral maps with a lot of cadastral information which can be used in updating the existing cadastral data with less time and cost. © 2012 Elsevier B.V. Source


Mukhtar K.,Pakistan Space and Upper Atmosphere Research Commission SUPARCO
2014 31th URSI General Assembly and Scientific Symposium, URSI GASS 2014 | Year: 2014

NeQuick2 is a well-known ionospheric model for electron density computation, utilizing the Epstein layer formulation originally proposed by G. Di Giovanni and S.M. Radicella. In this study, algorithm of NeQuick2 model has been employed for ionogram inversion using MATLAB. Critical frequencies of E-layer and F-layer (F2-layer during daytime), and, F-layer propagation factor have been used as ionogram input parameters to compute electron density profile. MATLAB gives more control in data analysis and development of model in advance language. The results have been demonstrated using the ionograms generated by DPS-4 installed at Multan Ionospheric Station (33N, 72E). Comparison of NeQuick2 and ARTIST generated electron density profiles has also been given. © 2014 IEEE. Source

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