干旱区生态环境知识资源中心(Arid): Large Scale Agricultural Plastic Mulch Detecting and Monitoring with Multi-Source Remote Sensing Data: A Case Study in Xinjiang, China

Arid

DOI	10.3390/rs11182088
	Large Scale Agricultural Plastic Mulch Detecting and Monitoring with Multi-Source Remote Sensing Data: A Case Study in Xinjiang, China
	Xiong, Yuankang 1,2; Zhang, Qingling 1,3; Chen, Xi1 ; Bao, Anming1 ; Zhang, Jieyun 1; Wang, Yujuan 4
通讯作者	Zhang, Qingling
来源期刊	REMOTE SENSING
EISSN	2072-4292
出版年	2019
卷号	11 期号:18
英文摘要	Plastic mulching has been widely practiced in crop cultivation worldwide due to its potential to significantly increase crop production. However, it also has a great impact on the regional climate and ecological environment. More importantly, it often leads to unexpected soil pollution due to fine plastic residuals. Therefore, accurately and timely monitoring of the temporal and spatial distribution of plastic mulch practice in large areas is of great interest to assess its impacts. However, existing plastic-mulched farmland (PMF) detecting efforts are limited to either small areas with high-resolution images or coarse resolution images of large areas. In this study, we examined the potential of cloud computing and multi-temporal, multi-sensor satellite images for detecting PMF in large areas. We first built the plastic-mulched farmland mapping algorithm (PFMA) rules through analyzing its spectral, temporal, and auxiliary features in remote sensing imagery with the classification and regression tree (CART). We then applied the PFMA in the dry region of Xinjiang, China, where a water resource is very scarce and thus plastic mulch has been intensively used and its usage is expected to increase significantly in the near future. The experimental results demonstrated that the PFMA reached an overall accuracy of 92.2% with a producer's accuracy of 97.6% and a user's accuracy of 86.7%, and the F-score was 0.914 for the PMF class. We further monitored and analyzed the dynamics of plastic mulch practiced in Xinjiang by applying the PFMA to the years 2000, 2005, 2010, and 2015. The general pattern of plastic mulch usage dynamic in Xinjiang during the period from 2000 to 2015 was well captured by our multi-temporal analysis.
英文关键词	plastic-mulched farmland decision tree classification oasis agriculture facility agriculture agricultural plastic waste
类型	Article
语种	英语
国家	Peoples R China
开放获取类型	Green Submitted, gold
收录类别	SCI-E
WOS记录号	WOS:000489101500018
WOS关键词	DIFFERENCE VEGETATION INDEX ; CLASSIFICATION ; GREENHOUSE ; LANDCOVER ; ACCURACY ; BIOMASS ; FIELDS ; IMAGES ; COVER ; N2O
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
来源机构	中国科学院新疆生态与地理研究所
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/218416
作者单位	1.Chinese Acad Sci, Xinjiang Inst Ecol & Geog, State Key Lab Desert & Oasis Ecol, Urumqi 830011, Peoples R China; 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China; 3.Sun Yat Sen Univ, Sch Aeronaut & Astronaut, Guangzhou 510006, Guangdong, Peoples R China; 4.China Asean Environm Cooperat Ctr, Beijing 100875, Peoples R China
推荐引用方式 GB/T 7714	Xiong, Yuankang,Zhang, Qingling,Chen, Xi,et al. Large Scale Agricultural Plastic Mulch Detecting and Monitoring with Multi-Source Remote Sensing Data: A Case Study in Xinjiang, China[J]. 中国科学院新疆生态与地理研究所,2019,11(18).
APA	Xiong, Yuankang,Zhang, Qingling,Chen, Xi,Bao, Anming,Zhang, Jieyun,&Wang, Yujuan.(2019).Large Scale Agricultural Plastic Mulch Detecting and Monitoring with Multi-Source Remote Sensing Data: A Case Study in Xinjiang, China.REMOTE SENSING,11(18).
MLA	Xiong, Yuankang,et al."Large Scale Agricultural Plastic Mulch Detecting and Monitoring with Multi-Source Remote Sensing Data: A Case Study in Xinjiang, China".REMOTE SENSING 11.18(2019).