In recent decades, the migration rates of the large cities of Punjab have been risen up to a considerable level due to the lack of employment opportunities as well as lack of facilities in the rural areas of the province. It has caused an unprecedented and unplanned urbanization across the urban areas of the province. This study has been undertaken to perform fractal analysis about the sprawl in rapidly growing city. GIS and remote sensing data have been used in this study as an emerging technology which is cost effective as well as accurate at the same time. Landsat images have been taken for the study and the sprawl has been calculated with the analysis of the data of each decade for past more than 40 years. It has been observed that the built up area is 47.8 to 141.12 Sq. Km whereas the pattern of urban settlement has been classified as clustered and linear, following the roads network. The temporal population growth also seconded these results. The population growth rate and population density increase, are based on the pixel based extraction of the data from satellite imagery for the period of 2000 to 2014, which is taken as a decision support tool. In 2000, the population of the district increased from 2,071,694 (1981 census) to 2,939,907 and then in 2013, it became 4,384,191 at a rate to 2.93% upturn per annum. Moreover, the study also reveals the extent of the growth of other land uses as well which may be taken as a reference that in an agricultural country like Pakistan, the natural resources are being wasted (by urbanization of the fertile land). There must be some master planning to avoid such things in the other cities as well.
This research study predominantly emphases on spatiotemporal extensions of urban area of Peshawar; its adverse impacts and contributions to climate and environment during 1931 to 2011. To probe these interventions, meteorological data, Satellite's temporal imagery of Landsat ETM+ and TM, anthropogenic and demographic secondary data were congregated. In relation to map out land cover changes, maximum likelihood classification algorithm and followed by change detection techniques were applied to study area. The outcome of this process was further subjected through Geographic Information System (GIS) overlay analysis which suggested a clear straggle in urban area. Auxiliary data (Population growth rate, transportation, electricity connections, etc.) also support the fact of urban area extension. This study proposes that severs contributions of massive heat energy and CO2 have been added to local climate and environment ensuing substantial increment in temperature drawn out from the trends. Consequently, Remote Sensing, GIS and allied data were found to be effective to gauge such variations. To eliminate anomalies in sprawl and environment, few suggestions and recommendation are made in latter part of this study.
Last couple of decades witnessed a rapid escalation in urban temperature of Peshawar city and its neighboring localities. This alarming condition gave birth to climatic term Urban Heat Island (UHI) created drastic alteration in surface temperatures. In this study, thermal infrared remote sensing data has been employed to map out and monitor such micro-climatic variation in temperatures in land use/land cover exposed surface to the environment. To assess these outcomes resulting from human activities, Landsat TM data band 6 was subjected through ERDAS Imagine 2013. For further processing, ARC GIS helped a lot in making maps to pinpoint the heat island in and around the city. Moreover, a relationship of land surface temperature with urban sprawl, environmental and industrialization was established. This study has shown a substantial upsurge in temperature about 1 to 3 degrees. Urban sprawl and industrialization at the edges are accounting for these conditions. Urban and industrial data has also reinforced the fact being drawn from remotely sensed data. Hence, evaluation of Land surface temperature data captured through remote satellite has proven to be effective tool not only for monitoring and analyzing temperature but also for assessing its adverse impacts on the environment and climate.
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