A moving window-based spatial assessment method for dynamic urban growth simulations

被引：2

作者：

Feng, Yongjiu ^{[1
,2
]}

Gao, Chen ^{[1
,2
]}

Wang, Rong ^{[1
,2
]}

Li, Pengshuo ^{[1
,2
]}

Xi, Mengrong ^{[1
,2
]}

Jin, Yanmin ^{[1
,2
]}

Tong, Xiaohua ^{[1
,2
]}

机构：

[1] Tongji Univ, Coll Surveying & Geoinformat, Shanghai, Peoples R China

[2] Tongji Univ, Shanghai Key Lab Space Mapping & Remote Sensing P, Shanghai, Peoples R China

来源：

GEOCARTO INTERNATIONAL | 2022年 / 37卷 / 27期

基金：

国家重点研发计划; 中国国家自然科学基金;

关键词：

Single-number assessment; spatial assessment; moving window analysis; cellular automata; urban growth; generalized additive model; ADDITIVE-MODEL GAM; CELLULAR-AUTOMATA; LAND; DISTRIBUTIONS; CALIBRATION; SCALE;

D O I：

10.1080/10106049.2022.2097319

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

This study proposes a spatial evaluation method for urban growth simulation based on moving windows, where the metrics measured within each window are considered to be those of the central cell. We also applied the generalized additive model to identify the quantitative relationship between the urban growth drivers and the spatial assessment metrics. A case study in Jiaxing city shows that the single-number overall accuracies (OAs) are above 94% and the figure-of-merits (FOMs) are above 27% in both 2010 and 2015. Most regions of the study area yield very high OAs and low FOMs while the regions around the administration centres yield low OAs and high FOMs. The spatial method can well indicate the model's effects on the urban simulations in different regions. The spatial assessment can report the assessment metrics of each cell to produce assessment maps as well as quantify the relationship between drivers and assessment metrics.

引用

页码：15282 / 15301

页数：20

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