太阳成8722(中国)有限公司-GREEN NO.1

标题：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

来源出版物：JOURNAL OF HOUSING AND THE BUILT ENVIRONMENT 卷：30 期：8页：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

文献类型：Article

语种：English

作者关键词：High-rise residential buildings, Geographic field model, Autologistic regression model, Akaike information criterion, Open space

扩展关键词：LOGISTIC-REGRESSION; PROPERTY-VALUES; CHINESE CITIES; OPEN SPACE; AUTOCORRELATION; PATTERNS; URBANIZATION; POPULATIONS; ECOLOGY

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

电子邮件地址：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

影响因子（2014）：0.657