气候变化领域集成服务门户(CCPortal): Combination of Sentinel-2 and PALSAR-2 for Local Climate Zone Classification: A Case Study of Nanchang, China

CCPortal

DOI	10.3390/rs13101902
	Combination of Sentinel-2 and PALSAR-2 for Local Climate Zone Classification: A Case Study of Nanchang, China
	Chen, Chaomin; Bagan, Hasi; Xie, Xuan; La, Yune; Yamagata, Yoshiki
通讯作者	Bagan, H (通讯作者)，Shanghai Normal Univ, Sch Environm & Geog Sci, Shanghai 200234, Peoples R China. ; Bagan, H (通讯作者)，Natl Inst Environm Studies, Ctr Global Environm Res, Ibaraki 3058506, Japan.
发表日期	2021
EISSN	2072-4292
卷号	13 期号:10
英文摘要	Local climate zone (LCZ) maps have been used widely to study urban structures and urban heat islands. Because remote sensing data enable automated LCZ mapping on a large scale, there is a need to evaluate how well remote sensing resources can produce fine LCZ maps to assess urban thermal environments. In this study, we combined Sentinel-2 multispectral imagery and dual-polarized (HH + HV) PALSAR-2 data to generate LCZ maps of Nanchang, China using a random forest classifier and a grid-cell-based method. We then used the classifier to evaluate the importance scores of different input features (Sentinel-2 bands, PALSAR-2 channels, and textural features) for the classification model and their contribution to each LCZ class. Finally, we investigated the relationship between LCZs and land surface temperatures (LSTs) derived from summer nighttime ASTER thermal imagery by spatial statistical analysis. The highest classification accuracy was 89.96% when all features were used, which highlighted the potential of Sentinel-2 and dual-polarized PALSAR-2 data. The most important input feature was the short-wave infrared-2 band of Sentinel-2. The spectral reflectance was more important than polarimetric and textural features in LCZ classification. PALSAR-2 data were beneficial for several land cover LCZ types when Sentinel-2 and PALSAR-2 were combined. Summer nighttime LSTs in most LCZs differed significantly from each other. Results also demonstrated that grid-cell processing provided more homogeneous LCZ maps than the usual resampling methods. This study provided a promising reference to further improve LCZ classification and quantitative analysis of local climate.
关键词	LAND-SURFACE TEMPERATURE URBAN HEAT-ISLAND RANDOM FOREST CLASSIFICATION COVER CLASSIFICATION LIDAR DATA MULTISPECTRAL DATA SAR PERFORMANCE CITIES IMAGES
英文关键词	local climate zone; random forest; feature importance; land surface temperature; grid cells; Sentinel-2; PALSAR-2; ASTER
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:000662637400001
来源期刊	REMOTE SENSING
来源机构	中国科学院西北生态环境资源研究院
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/254821
作者单位	[Chen, Chaomin; Bagan, Hasi; Xie, Xuan] Shanghai Normal Univ, Sch Environm & Geog Sci, Shanghai 200234, Peoples R China; [Bagan, Hasi; Yamagata, Yoshiki] Natl Inst Environm Studies, Ctr Global Environm Res, Ibaraki 3058506, Japan; [La, Yune] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resource, State Key Lab Cryospher Sci, Cryosphere Res Stn Qinghai Tibetan Plateau, Lanzhou 730000, Peoples R China; [La, Yune] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Chen, Chaomin,Bagan, Hasi,Xie, Xuan,et al. Combination of Sentinel-2 and PALSAR-2 for Local Climate Zone Classification: A Case Study of Nanchang, China[J]. 中国科学院西北生态环境资源研究院,2021,13(10).
APA	Chen, Chaomin,Bagan, Hasi,Xie, Xuan,La, Yune,&Yamagata, Yoshiki.(2021).Combination of Sentinel-2 and PALSAR-2 for Local Climate Zone Classification: A Case Study of Nanchang, China.REMOTE SENSING,13(10).
MLA	Chen, Chaomin,et al."Combination of Sentinel-2 and PALSAR-2 for Local Climate Zone Classification: A Case Study of Nanchang, China".REMOTE SENSING 13.10(2021).