Urban environmental and land cover change analysis using the scatter plot, kernel, and neural network methods

被引:0
作者
Ali Akbar Jamali
Reza Ghorbani Kalkhajeh
机构
[1] Islamic Azad University,Department of GIS and Watershed Management, Maybod Branch
[2] Islamic Azad University,Department of Remote Sensing and GIS, Yazd Branch
来源
Arabian Journal of Geosciences | 2019年 / 12卷
关键词
Iran; Kernel; Land use change; Scatter; Spatial modeling; Urban environment;
D O I
暂无
中图分类号
学科分类号
摘要
This study simulates and predicts the urban environment growth in the Tehran, capital of Iran, using the remote sensing data, multi-layer perceptron neural network, zonal, trend, and profile modeling. A spatial-temporal modeling was used for the analysis and prediction of the urban environment development. After building the probability map of the land changes, random points scatter and kernel analysis (RPSKA) was used. The pixel values of all the maps was extracted to the random points for the scatter plot and kernel analysis. The results obtained by developing the change transition model using multi-layer perceptron neural network showed high accuracy in most of the sub-models. The area of the open lands and green spaces was reduced, and urban areas, agricultural lands, and clay plains were increased. Most of the land use and land cover (LULC) changes during the period 1990–2000 were observed in the north, while the most land use and land cover changes during the period 2000–2016 were observed in the west. The results of RPSKA were shown the direct and inverse relationship between the probability of land changes and the other factor maps. Sever changes have occurred from the open lands to the urban areas. The slope and the population density had more effect on the changes. Modeling of future LULC change showed that the urban areas would be increased, while open lands and green spaces would be decreased. These land changes have taken place in the north and west of the city that these regions were most popular and had suitable infrastructures for developments.
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[1]  
Ashfaq RAR(2017)Fuzziness based semi-supervised learning approach for intrusion detection system Inf Sci 378 484-497
[2]  
Wang XZ(2005)Land resource sustainability for urban development: spatial decision support system prototype Environ Manag 36 282-296
[3]  
Huang JZ(2011)Sprawl and blight J Urban Econ 69 205-213
[4]  
Abbas H(2013)The SLEUTH environmental and land cover change model: a review Environ Resour Res 1 88-105
[5]  
He YL(1982)Statistical method for selecting landsat MSS J Appl Photogr Eng 8 23-30
[6]  
Banai R(2009)Environmental and land cover change in greater Dhaka, Bangladesh: using remote sensing to promote sustainable urbanization Appl Geogr 29 390-401
[7]  
Brueckner JK(2018)Determination of the urban heat island intensity in villages and its connection to land cover in three European climate zones Clim Res 76 1-15
[8]  
Helsley RW(2011)Land use and land cover change detection in the western Nile delta of Egypt using remote sensing data Appl Geogr 31 483-494
[9]  
Chaudhuri G(2013)Modeling urban evolution using neural networks, fuzzy logic and GIS: the case of the Athens metropolitan area Cities 30 193-203
[10]  
Clarke K(2017)Analyses the driving forces for urban growth by using IDRISI® Selva models Abouelreesh-Aswan as a case study Int J Eng Technol 9 226-232