Urban green space classification and water consumption analysis with remote-sensing technology: a case study in Beijing, China

doi:10.1080/01431161.2018.1479798

	Urban green space classification and water consumption analysis with remote-sensing technology: a case study in Beijing, China
	Di, Suchuang 1,2; Li, Zhao-Liang 3,4,5; Tang, Ronglin 3; Pan, Xingyao 1,2; Liu, Honglu 1,2; Niu, Yong 6
刊名	INTERNATIONAL JOURNAL OF REMOTE SENSING
	2019
卷号	40 期号:5-6 页码:1909-1929
ISSN号	0143-1161
DOI	10.1080/01431161.2018.1479798
通讯作者	Tang, Ronglin(trl_wd@163.com)
英文摘要	The water consumption of green space in a large region is difficult to attain through traditional methods. In this article, a practical method is developed using different sources of remote-sensing data. The green space was first derived from a high spatial resolution RapidEye image using the stratified classification method. Then the primary vegetation types of green space were identified using the object-oriented classification method. Afterwards regional green space evapotranspiration was inversed based on multi-temporal Landsat 8 images using the Surface Energy Balance Algorithm for Land model. Finally, water consumption patterns for different types of vegetation were analysed, and regional water consumption was estimated. The method was applied to the northwest region of Beijing City with an area of 147.5km(2) where the green space area was 56.87km(2), and the deciduous broadleaf forest area was the largest among six vegetation types. The total quantity of water consumption for green space in the growing period in the study region was 41.52x10(6)m(3) (Mm(3)). The quantity of water consumed by different types of vegetation in an order from high to low were deciduous broadleaf forest, mixed green space, grassland, evergreen needleleaf forest, golf course, and aquatic vegetation, ranging from 17.43 to 0.79Mm(3). The results are helpful for identifying vegetation types, monitoring vegetation growth status, managing green space, and optimizing green space ecological functions in the Beijing region. The method presented in this article, having higher accuracy and more convenience, has great potential to be applied to other areas across the world.
资助项目	Beijing Natural Science Foundation[8184075] ; Beijing Municipal Science and Technology Commission[D161100005916003] ; Beijing Municipal Science and Technology Commission[Z161100001116104] ; Beijing Water Authority Outstanding Young Talent Project ; Beijing Municipal Organization Department Young Talent Project ; Beijing Nova Programme[Z161100004916085] ; International Science and Technology Cooperation Programme of China[2014DFE10220]
WOS关键词	EVAPOTRANSPIRATION ESTIMATION ; MODIS ; ALGORITHM
WOS研究方向	Remote Sensing ; Imaging Science & Photographic Technology
语种	英语
出版者	TAYLOR & FRANCIS LTD
WOS记录号	WOS:000464043900020
资助机构	Beijing Natural Science Foundation ; Beijing Municipal Science and Technology Commission ; Beijing Water Authority Outstanding Young Talent Project ; Beijing Municipal Organization Department Young Talent Project ; Beijing Nova Programme ; International Science and Technology Cooperation Programme of China
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/48243]
专题	中国科学院地理科学与资源研究所
通讯作者	Tang, Ronglin
作者单位	1.Beijing Water Sci & Technol Inst, Dept Water Hazard Res, Beijing, Peoples R China 2.Beijing Engn Res Ctr Nonconvent Water Resources U, Beijing, Peoples R China 3.Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China 4.CNRS, ICube, UdS, Illkirch Graffenstaden, France 5.Chinese Acad Agr Sci, Key Lab Agriinformat, Minist Agr, Inst Agr Resources & Reg Planning, Beijing, Peoples R China 6.Shandong Agr Univ, Coll Forestry, Tai An, Shandong, Peoples R China
推荐引用方式 GB/T 7714	Di, Suchuang,Li, Zhao-Liang,Tang, Ronglin,et al. Urban green space classification and water consumption analysis with remote-sensing technology: a case study in Beijing, China[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2019,40(5-6):1909-1929.
APA	Di, Suchuang,Li, Zhao-Liang,Tang, Ronglin,Pan, Xingyao,Liu, Honglu,&Niu, Yong.(2019).Urban green space classification and water consumption analysis with remote-sensing technology: a case study in Beijing, China.INTERNATIONAL JOURNAL OF REMOTE SENSING,40(5-6),1909-1929.
MLA	Di, Suchuang,et al."Urban green space classification and water consumption analysis with remote-sensing technology: a case study in Beijing, China".INTERNATIONAL JOURNAL OF REMOTE SENSING 40.5-6(2019):1909-1929.