首頁  >  科研動态  >  正文
科研動态
博士生周鵬的論文在JOURNAL OF HOUSING AND THE BUILT ENVIRONMENT刊出
發布時間:2015-09-08 15:57:39     發布者:yz     浏覽次數:

标題:Prediction of the spatial distribution of high-rise residential buildings by the use of a geographic field based autologistic regression model作者:Zhou, Peng; Liu, Yanfang; Chen, Yiyun; Zeng, Chen; Wang, Zhouyuan

來源出版物:JOURNAL OF HOUSING AND THE BUILT ENVIRONMENT 卷:30 期:8頁:487-508 DOI:10.1007/s10901-014-9426-1 出版年:SEP 2015

摘要:As an indicator of urbanization, high-rise residential buildings, can meet the space requirements of an increasing population and improve land use efficiency. Such buildings are continuously built in the central areas of cities worldwide despite residential suburbanization. To predict high-rise residential building location, this study employs a geographic field model-based autologistic regression model (GFM-autologistic model). In line with this goal, a model is determined using both the value of the area under the receiver operating characteristic curve (ROC) and the Akaike information criterion (AIC) for GFM-autologistic, Euclidean distance (ED)-logistic and ED-autologistic models. The minimum AIC and the maximum ROC values of the GFM-autologistic model indicate that this model has the best fit. The GFM defines the external effect of ecological elements and locational factors, and it also quantifies distance decay through a linear intensity function with an influence threshold, thereby avoiding the bias caused by ED. Moreover, land prices are positive related to building height. High-rise residential development also considers open public spaces, such as rivers and city plazas. In summary, the spatial distribution of high-rise residential buildings displays a distance decay in the effect of ecological elements such as open spaces. Thus, this manuscript provides a theoretical basis for modern-city development planning and modern high-rise residential development.

入藏号:WOS:000359404500007

文獻類型:Article

語種:English

作者關鍵詞:High-rise residential buildings, Geographic field model, Autologistic regression model, Akaike information criterion, Open space

擴展關鍵詞:LOGISTIC-REGRESSION; PROPERTY-VALUES; CHINESE CITIES; OPEN SPACE; AUTOCORRELATION; PATTERNS; URBANIZATION; POPULATIONS; ECOLOGY

通訊作者地址:Liu, Yanfang; Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

電子郵件地址:zhouwhu1987@163.com

地址:

[Zhou, Peng; Liu, Yanfang; Chen, Yiyun] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

[Zeng, Chen] Huazhong Agr Univ, Sch Land Resources Management, Wuhan 430070, Peoples R China.

[Wang, Zhouyuan] Changjiang Water Resources Commiss, Bur Hydrol, Hanjiang Water Environm Monitoring Ctr, Xiangyan 441022, Peoples R China.

研究方向:Environmental Sciences & Ecology; Urban Studies

ISSN:1566-4910

eISSN:1573-7772

影響因子(2014):0.657

信息服務
學院網站教師登錄 學院辦公電話 學校信息門戶登錄

版權所有 © 88858cc永利官网
地址:湖北省武漢市珞喻路129号 郵編:430079 
電話:027-68778381,68778284,68778296 傳真:027-68778893    郵箱:sres@whu.edu.cn

Baidu
sogou