Urbanization dynamics of Tehran city (1975–2015) using artificial neural networks
Authors:
Open Access
- 1 January 2017
- journal article
- research article
- Published by Taylor & Francis in Journal of Maps
- Vol. 13 (1) , 24-30
Abstract
Land-use dynamic is a major challenge for town and country planners especially in developing countries such as Iran. Iran has been under rapid urban expansion and population growth for past three decades which led to lack of resources, environmental deterioration and haphazard landscape development. In this paper, an attempt has been made to map the urbanization dynamics of Tehran in 40 years based on remote sensing imagery and by means of artificial neural networks. The presented scheme could be taken into consideration when planning initiatives aimed at surveying, monitoring, managing and sustainable development of the territory. Moreover, it can serve the experts in the fields of geography, urban studies and planning as a background for number of geographical analyses.Keywords
This publication has 50 references indexed in Scilit:
- SAR polarimetric change detection for flooded vegetationInternational Journal of Digital Earth, 2013
- Landsat analysis of urban growth: How Tokyo became the world's largest megacity during the last 40 yearsRemote Sensing of Environment, 2012
- Updating Land-Cover Maps by Classification of Image Time Series: A Novel Change-Detection-Driven Transfer Learning ApproachIEEE Transactions on Geoscience and Remote Sensing, 2012
- Object-based analysis and change detection of major wetland cover types and their classification uncertainty during the low water period at Poyang Lake, ChinaRemote Sensing of Environment, 2011
- Tracking dynamic land-use change using spatially explicit Markov Chain based on cellular automata: the case of TehranInternational Journal of Image and Data Fusion, 2011
- Urbanization in developing countries: Current trends, future projections, and key challenges for sustainabilityTechnology in Society, 2006
- Improved Understanding of Urban Sprawl Using Neural Networks2004
- Supervised classification of types of glaciated landscapes using digital elevation dataGeomorphology, 1998
- Introduction Neural networks in remote sensingInternational Journal of Remote Sensing, 1997
- Early detection program for prostate cancer: results and identification of high-risk patient populationUrology, 1991