Study on the driving forces and prediction of built-up area for urban expansion in Kunming

Yulian Hong; Jianhua Xu; Zhanyong Wang

doi:10.1109/RSETE.2011.5965098

Study on the driving forces and prediction of built-up area for urban expansion in Kunming

Yulian Hong^*
, Jianhua Xu
, Zhanyong Wang

^*Corresponding author for this work

School of Geographic Sciences

East China Normal University
Xiamen University of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Based on the analysis of driving forces of urban land expansion by Principal component analysis (PCA), this paper established a predicting model of urban built-up area for future by using socio-economical data. Being good at the performance of nonlinear approximation, artificial neural network (ANN), especially the back propagation algorithm (BP), is applied in the prediction of bulit-up land and had attained satisfactory results. Taking Kunming for example, the results showed that the urbanization is the decisive factor influencing urban land expansion, and a predicting model combined PCA and BP-ANN used to predict urban built-up area in the year of 2009-2015. The method employed in this paper can provide a reference to study on urban land expansion for urban development and planning in the inland cities lacking of multi-sources data.

Original language	English
Title of host publication	2011 International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2011 - Proceedings
Pages	3569-3572
Number of pages	4
DOIs	https://doi.org/10.1109/RSETE.2011.5965098
State	Published - 2011
Event	2011 International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2011 - Nanjing, China Duration: 24 Jun 2011 → 26 Jun 2011

Publication series

Name	2011 International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2011 - Proceedings

Conference

Conference	2011 International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2011
Country/Territory	China
City	Nanjing
Period	24/06/11 → 26/06/11

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

Keywords

BP neural network
Built-up area
Driving forces
Kunming
PCA
Urban land expansion

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10.1109/RSETE.2011.5965098

Cite this

Hong, Y., Xu, J., & Wang, Z. (2011). Study on the driving forces and prediction of built-up area for urban expansion in Kunming. In 2011 International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2011 - Proceedings (pp. 3569-3572). Article 5965098 (2011 International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2011 - Proceedings). https://doi.org/10.1109/RSETE.2011.5965098

Hong, Yulian ; Xu, Jianhua ; Wang, Zhanyong. / Study on the driving forces and prediction of built-up area for urban expansion in Kunming. 2011 International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2011 - Proceedings. 2011. pp. 3569-3572 (2011 International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2011 - Proceedings).

@inproceedings{4a2b2c9bda0a43b8b23882c4781b0c95,

title = "Study on the driving forces and prediction of built-up area for urban expansion in Kunming",

abstract = "Based on the analysis of driving forces of urban land expansion by Principal component analysis (PCA), this paper established a predicting model of urban built-up area for future by using socio-economical data. Being good at the performance of nonlinear approximation, artificial neural network (ANN), especially the back propagation algorithm (BP), is applied in the prediction of bulit-up land and had attained satisfactory results. Taking Kunming for example, the results showed that the urbanization is the decisive factor influencing urban land expansion, and a predicting model combined PCA and BP-ANN used to predict urban built-up area in the year of 2009-2015. The method employed in this paper can provide a reference to study on urban land expansion for urban development and planning in the inland cities lacking of multi-sources data.",

keywords = "BP neural network, Built-up area, Driving forces, Kunming, PCA, Urban land expansion",

author = "Yulian Hong and Jianhua Xu and Zhanyong Wang",

year = "2011",

doi = "10.1109/RSETE.2011.5965098",

language = "英语",

isbn = "9781424491711",

series = "2011 International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2011 - Proceedings",

pages = "3569--3572",

booktitle = "2011 International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2011 - Proceedings",

note = "2011 International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2011 ; Conference date: 24-06-2011 Through 26-06-2011",

}

Hong, Y, Xu, J & Wang, Z 2011, Study on the driving forces and prediction of built-up area for urban expansion in Kunming. in 2011 International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2011 - Proceedings., 5965098, 2011 International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2011 - Proceedings, pp. 3569-3572, 2011 International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2011, Nanjing, China, 24/06/11. https://doi.org/10.1109/RSETE.2011.5965098

Study on the driving forces and prediction of built-up area for urban expansion in Kunming. / Hong, Yulian; Xu, Jianhua; Wang, Zhanyong.
2011 International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2011 - Proceedings. 2011. p. 3569-3572 5965098 (2011 International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2011 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Study on the driving forces and prediction of built-up area for urban expansion in Kunming

AU - Hong, Yulian

AU - Xu, Jianhua

AU - Wang, Zhanyong

PY - 2011

Y1 - 2011

N2 - Based on the analysis of driving forces of urban land expansion by Principal component analysis (PCA), this paper established a predicting model of urban built-up area for future by using socio-economical data. Being good at the performance of nonlinear approximation, artificial neural network (ANN), especially the back propagation algorithm (BP), is applied in the prediction of bulit-up land and had attained satisfactory results. Taking Kunming for example, the results showed that the urbanization is the decisive factor influencing urban land expansion, and a predicting model combined PCA and BP-ANN used to predict urban built-up area in the year of 2009-2015. The method employed in this paper can provide a reference to study on urban land expansion for urban development and planning in the inland cities lacking of multi-sources data.

AB - Based on the analysis of driving forces of urban land expansion by Principal component analysis (PCA), this paper established a predicting model of urban built-up area for future by using socio-economical data. Being good at the performance of nonlinear approximation, artificial neural network (ANN), especially the back propagation algorithm (BP), is applied in the prediction of bulit-up land and had attained satisfactory results. Taking Kunming for example, the results showed that the urbanization is the decisive factor influencing urban land expansion, and a predicting model combined PCA and BP-ANN used to predict urban built-up area in the year of 2009-2015. The method employed in this paper can provide a reference to study on urban land expansion for urban development and planning in the inland cities lacking of multi-sources data.

KW - BP neural network

KW - Built-up area

KW - Driving forces

KW - Kunming

KW - PCA

KW - Urban land expansion

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DO - 10.1109/RSETE.2011.5965098

M3 - 会议稿件

AN - SCOPUS:80052205629

SN - 9781424491711

T3 - 2011 International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2011 - Proceedings

SP - 3569

EP - 3572

BT - 2011 International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2011 - Proceedings

T2 - 2011 International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2011

Y2 - 24 June 2011 through 26 June 2011

ER -

Hong Y, Xu J, Wang Z. Study on the driving forces and prediction of built-up area for urban expansion in Kunming. In 2011 International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2011 - Proceedings. 2011. p. 3569-3572. 5965098. (2011 International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2011 - Proceedings). doi: 10.1109/RSETE.2011.5965098

Study on the driving forces and prediction of built-up area for urban expansion in Kunming

Abstract

Publication series

Conference

UN SDGs

Keywords

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