Urban sprawl trend analysis using statistical and remote sensing approach Case Study: Mashhad City

Document Type: Original Article


1 Department of urbanism, Mashhad Branch, Islamic Azad University, Mashhad, Iran

2 Assistant Professor, Depatment of urbanism, Mashhad branch, Islamic Azad univesity, Mashhad, Iran


Urban sprawl is a significant challenge in urban areas and considered as the most influential drivers of land
use and land cover change associated with growth of populations and economy. Iran's cities have been faced
with the urban sprawl phenomenon, especially since the 1970s. More recently, scientific studies have been
proved negative impacts of urban sprawl in Iran's cities including the destruction of landscapes and natural
resources around the city and coastal areas. Mashhad is a metropolis which has faced urban sprawl in recent
decades. The present study aims to generate an urban sprawl model using statistical and remote sensing
approach by the integration of geographic information system (GIS) in Mashhad city, northeastern Iran.
For this purpose, various temporal LANDSAT satellite datasets were used to map land use/land cover
characteristics and to evaluate built-up growth in Mashhad in 1996, 2006 and 2016. Maximum likelihood
classification method (MLC) mapped the land cover for the Mashhad using Landsat TM datasets. The
ability of MLC in minimizing misclassification errors by allowing variable weight specifications during the
classification process and use of training data made it a suitable method for this study. After MLC proses,
Shannon’s Entropy based on the land use classification result is used to measure urban sprawl. Results
indicated a significant increase of urban built-up area during the last two decades. During the two time
periods of this study the Shannon entropy increased in all of the two time periods that showing the City of
Mashhad continue to have a problem with urban sprawl.