Mapping and monitoring of urban sprawl to promote sustainable urbanization using geospatial techniques
Khan M.R. Amin M. Ahmad Z. Sagin J.
2021Corvinus University of Budapest
Applied Ecology and Environmental Research
2021#19Issue 64443 - 4457 pp.
Urbanization is a global phenomenon, but in undeveloped countries like Pakistan, urban sprawl ratio has proliferated. Non-systematic development, increased migration, and sharp population growth have been predominant factors. These variables boosted the population and resulted in quickly built-up areas in the Peshawar district. The present research was to investigate spatial and temporal change in the urban sprawl from 2000 to 2018. Remotely sensed data and Maximum Likelihood Classification were used to investigate the urban sprawl. Remotely sensed data is fundamentally appropriate for providing information and characteristics for urban land cover on spatial and temporal scales. The results show that the total urban built-up areas were 54.39 km2, 54.62 km2, 64.64 km2, 69.65 km2 and 77.39 km2 with annual growth rates of 0.084%, 3.06%, 1.43% and 3.3%, respectively, in 2000, 2005, 2010, 2015 and 2018. The overall accuracy of the classified imagery was 80 %. Our finding of analysis shows that major changes were detected in the built-up area of Peshawar during this 18-year time period. According to the Peshawar Development Authority report, in 2017 the total urban built-up area was 84km2 while our analysis shows that the total built area was 77 km2. The primary driving force for the development was education, health, and microeconomic centers, and the population shift to the Peshawar district from neighboring tribal regions because of military operations. It has been recommended that hyper spectral imagery would be useful for monitoring the urban expansion of larger cities.
Hyper spectral imagery , Maximum Likelihood Classification , Predominant factors , Remote sensing , Spatial and temporal
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School of Environmental Science, Charles Sturt University, Albury, Australia
Institute of Geo-Information & Earth Observation, PMAS Arid Agriculture University, Rawalpindi, Pakistan
The Environment & Resource Efficiency Cluster (EREC), Nazarbayev University, Nur-Sultan, Kazakhstan
School of Environmental Science
Institute of Geo-Information & Earth Observation
The Environment & Resource Efficiency Cluster (EREC)
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