Urban sprawl pattern and land-use change detection in Yazd, Iran

Shahraki, Saeed Zanganeh; Pujol, David Saurí i; Serra, Pere; Modugno, Sirio; Seifolddini, Faranak; Ahmad, Pourahmad

doi:10.1016/j.habitatint.2011.02.004

Cited by 119 publications

(31 citation statements)

References 23 publications

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“…A peri-urban area is generally defined as the transition zone between urban and rural areas possessing some characteristics of the both (Shi, Sun, Zhu, Li, & Mei, 2012). However, urban and peri-urban areas have their own trajectories and patterns of urbanization (Zanganeh Shahraki et al, 2011). Moreover, the factors governing land management and growth in peri-urban areas are somewhat different compared to the urban areas, and thus cannot be simultaneously used to understand the dynamics of the both.…”

Section: Introductionmentioning

confidence: 99%

“…A number of techniques are available for mapping the built-up areas (Bhatti & Tripathi, 2014;Lo & Choi, 2004;Powell, Roberts, Dennison, & Hess, 2007), and one of the basic methods to study the urban sprawl is to examine the temporal variations in the land across heterogeneous geographical areas (Wilson, Clay, Martin, Stuckey, & Vedder-Risch, 2003;Zeng, Sui, & Li, 2005). The land managers also take help from the simulation models that assist is estimating the future urban growth (Zanganeh Shahraki et al, 2011). However, urban sprawl varies in different areas depending upon the land conversion patterns, which involves a number of factors.…”

Section: Introductionmentioning

confidence: 99%

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A multi-scale modeling approach for simulating urbanization in a metropolitan region

Bhatti

Tripathi

Nitivattananon

et al. 2015

Habitat International

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a b s t r a c tMetropolitan regions worldwide are experiencing rapid urban growth and the planners often employ prediction models to forecast the future expansion for improving the land management policies and practices. These regions are a mix of urban, peri-urban and rural areas where each sector has its unique expansion properties. This study examines the differences in urban and peri-urban growth characteristics, and their impact at different stages of prediction modeling, in city district Lahore, Pakistan. The analysis of multi-temporal land use/land cover maps revealed that the associations between major land transitions and the factors governing land changes were unique at city district, urban and peri-urban scales. A multilayer perceptron neural network was employed for modeling urbanization, and it was found that the sub-models developed for urban and peri-urban subsets returned better accuracies than those produced at the city district scale. The prediction maps of 2021 and 2035 were also produced through this approach.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A multi-scale modeling approach for simulating urbanization in a metropolitan region

Bhatti

Tripathi

Nitivattananon

et al. 2015

Habitat International

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“…4;2014 urban development plans which is conclusive for all Iranian cities. However, the implementation of master plans for most Iranian cities should solve most of the problems within four decades, although a large amount of literature has given ample evidence that the achievements of master plans hardly correspond to the original goals and objectives when they are put into practice (Mashhoudi, 2001;Panahandeh et al, 2009;Zanganeh et al, 2011). In this case, such a situation is considered as a failure.…”

Section: Assessment Of Urban Development Plans In Iranmentioning

confidence: 99%

Improving the Preparation of Iranian Urban Development Plans: Lessons Learned from Other Experiences

Tilaki¹,

Bahauddin²,

Abdullah³

et al. 2014

MAS

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The rapid urbanization process all over the world has raised the need to employ more satisfactory urban development approaches; these are especially recognized and declared in developing countries. This paper attempts to indicate what achievable ways may improve the current urban development plans based on the comprehensive planning method in Iran. In order to achieve this objective, this paper reviews qualitatively the urban planning in Iran and assesses its urban development plans. Ultimately, appropriate measures are presented in order to suggest how the defects found in the current Iranian urban development plans may be corrected by employing the lessons learned from practical examples recorded in other selected countries. The primary data was collected by means of semi-structured interviews from decision making and decision taking processes in Iran. In conclusion, this article suggests that the identified defects of urban development plans in Iran may be improved by adapting to the most recent universal concepts of urban planning. In other words, Iranian urban planning should be distanced from political decisions and instead motivated as a technical process in the government structure.

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“…Land cover change detection (LCCD), which is a classic problem, has recently been a hot topic in remote sensing [1][2][3][4][5][6][7][8], because LCCD plays an increasingly important role in making decisions to promote sustainable urban development, such as urban expansion [9,10], city temperature change analysis [11,12], urban air quality analysis [13], man-made target change detection [14], and urban landscape change [15][16][17], etc. In addition, LCCD has a positive effect in natural resource management on Earth's surface, for example, in forest deformation monitoring [18,19] and land use monitoring [20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Land Cover Change Detection Based on Adaptive Contextual Information Using Bi-Temporal Remote Sensing Images

Liu

Zhang

et al. 2018

Remote Sensing

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Land cover change detection (LCCD) based on bi-temporal remote sensing images plays an important role in the inventory of land cover change. Due to the benefit of having spatial dependency properties within the image space while using remote sensing images for detecting land cover change, many contextual information-based change detection methods have been proposed in past decades. However, there is still a space for improvement in accuracies and usability of LCCD. In this paper, a LCCD method based on adaptive contextual information is proposed. First, an adaptive region is constructed by gradually detecting the spectral similarity surrounding a central pixel. Second, the Euclidean distance between pairwise extended regions is calculated to measure the change magnitude between the pairwise central pixels of bi-temporal images. All the bi-temporal images are scanned pixel by pixel so the change magnitude image (CMI) can be generated. Then, the Otsu or a manual threshold is employed to acquire the binary change detection map (BCDM). The detection accuracies of the proposed approach are investigated by three land cover change cases with Landsat bi-temporal remote sensing images and aerial images with very high spatial resolution (0.5 m/pixel). In comparison to several widely used change detection methods, the proposed approach can produce a land cover change inventory map with a competitive accuracy.

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Urban sprawl pattern and land-use change detection in Yazd, Iran

Cited by 119 publications

References 23 publications

A multi-scale modeling approach for simulating urbanization in a metropolitan region

A multi-scale modeling approach for simulating urbanization in a metropolitan region

Improving the Preparation of Iranian Urban Development Plans: Lessons Learned from Other Experiences

Land Cover Change Detection Based on Adaptive Contextual Information Using Bi-Temporal Remote Sensing Images

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