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Towards a Remote Sensing and GIS-Based Technique to Study Population and Urban Growth: A Case Study of Multan 被引量:1
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作者 Atif Ali Anam Khalid +10 位作者 Muhammad Atif Butt Rashid Mehmood Syed Amer Mahmood Javed Sami Jahanzeb Qureshi Kashif Shafique Asdullah Khan Ghalib rizwan waheed Farhan Ali Rais Mukhtar Muhammad Azhar 《Advances in Remote Sensing》 2018年第3期245-258,共14页
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 provi... 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. 展开更多
关键词 URBAN SPRAWL POPULATION Growth SPATIO-TEMPORAL REMOTE Sensing LAND Use Pakistan
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Flood Frequency Analysis of Chenab River for Predicting Peak Flows during Late Monsoon Period
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作者 Muhammad Atif Butt Atif Ali +7 位作者 Sonia Ijaz Rashid Mehmood Syed Amer Mahmood Ghulam Jaffer Kashif Shafique Asadullah Khan Ghalib rizwan waheed Ali Iqtadar Mirza 《Advances in Remote Sensing》 2019年第1期1-29,共29页
The River Chenab is one of the main western rivers of the Indus River system in Pakistan, which undergoes intensive inundation almost every year during the late monsoon period. The present study performs flood frequen... The River Chenab is one of the main western rivers of the Indus River system in Pakistan, which undergoes intensive inundation almost every year during the late monsoon period. The present study performs flood frequency analyses for the river basin as well as simulates different levels of water flow in the system to speculate all kinds of inundation under different scenarios, i.e., to predict flood hazard and flood extended areas. Flood frequency analyses were performed at MARALA Headworks to Khanki Headworks. Data were collected from the Punjab Irrigation Department, Pakistan and from USGS and ASTER GDEM. The peak discharge of MARALA Headworks had been analyzed for 25 years. The preprocessing was performed in HEC Geo-RAS after preprocessing model run in HEC-RAS. After analysis the data were exported in HEC-RAS to ARCMAP to generate a floodplain and inundation map. Our analysis generated the result that different areas would be under water in different return periods. Flood hazards maps for different return periods 10, 20, 50 and 100 years were conducted using annual peaks flow of 35 years from 1980 to 2016. The maximum discharges at up and down stream for different periods were obtained using Gumbel distribution model results which showed that different areas were predicted under water in different return periods and affected areas after five years’ return period. 展开更多
关键词 ASTER GDEM HEC Geo-RAS ARCMAP Gumbel Distribution Model
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