气候变化领域集成服务门户(CCPortal): Mapping sugarcane plantation dynamics in Guangxi, China, by time series Sentinel-1, Sentinel-2 and Landsat images

CCPortal

DOI	10.1016/j.rse.2020.111951
	Mapping sugarcane plantation dynamics in Guangxi, China, by time series Sentinel-1, Sentinel-2 and Landsat images
	Wang J.; Xiao X.; Liu L.; Wu X.; Qin Y.; Steiner J.L.; Dong J.
发表日期	2020
ISSN	00344257
卷号	247
英文摘要	Sugarcane is a major crop for sugar and ethanol production and its area has increased substantially in tropical and subtropical regions in recent decades. Updated and accurate sugarcane maps are critical for monitoring sugarcane area and production and assessing its impacts on the society, economy and the environment. To date, no sugarcane mapping tools are available to generate annual maps of sugarcane at the field scale over large regions. In this study, we developed a pixel- and phenology-based mapping tool to produce an annual map of sugarcane at 10-m spatial resolution by analyzing time-series Landsat-7/8, Sentinel-2 and Sentinel-1 images (LC/S2/S1) during August 31, 2017 - July 1, 2019 in Guangxi province, China, which accounts for 65% of sugarcane production of China. First, we generated annual maps of croplands and other land cover types in 2018. Second, we delineated the cropping intensity (single, double and triple cropping in a year) for all cropland pixels in 2018. Third, we identified sugarcane fields in 2018 based on its phenological characteristics. The resultant 2018 sugarcane map has producer, user and overall accuracies of 88%, 96% and 96%, respectively. According to the annual sugarcane map in 2018, there was a total of 8940 km2 sugarcane in Guangxi, which was ~1% higher than the estimate from the Guangxi Agricultural Statistics Report. Finally, we identified green-up dates of those sugarcane fields in 2019, which could be used to support the sugarcane planting and management activities. Our study demonstrates the potential of the pixel- and phenology-based sugarcane mapping tool (both the algorithms and the LC/S2/S1 time series images) in identifying croplands, cropping intensity and sugarcane fields in the complex landscapes with diverse crop types, fragmented crop fields and frequent cloudy weather. The resultant annual maps from this study could be used to assist farms and sugarcane mills for sustainable sugarcane production and environment. © 2020 Elsevier Inc.
英文关键词	Agriculture; Crop mapping; Land cover; Phenology; Remote sensing; Vegetation indices
语种	英语
scopus关键词	Agricultural robots; Biology; Crops; Mapping; Pixels; Time series; Tropics; Ethanol production; Land-cover types; Landsat images; Large regions; Management activities; Overall accuracies; Spatial resolution; Subtropical regions; Sugar industry; algorithm; alternative agriculture; ethanol; land cover; Landsat; pixel; Sentinel; spatial resolution; sugar cane; time series; China; Guangxi Zhuangzu
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179236
作者单位	Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK 73019, United States; Guangdong Province Key Laboratory for Land Use and Consolidation, South China Agricultural University, Guangzhou, 510642, China; Agronomy Department, Kansas State University, Manhattan, Kansas, 66502, United States; Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
推荐引用方式 GB/T 7714	Wang J.,Xiao X.,Liu L.,et al. Mapping sugarcane plantation dynamics in Guangxi, China, by time series Sentinel-1, Sentinel-2 and Landsat images[J],2020,247.
APA	Wang J..,Xiao X..,Liu L..,Wu X..,Qin Y..,...&Dong J..(2020).Mapping sugarcane plantation dynamics in Guangxi, China, by time series Sentinel-1, Sentinel-2 and Landsat images.Remote Sensing of Environment,247.
MLA	Wang J.,et al."Mapping sugarcane plantation dynamics in Guangxi, China, by time series Sentinel-1, Sentinel-2 and Landsat images".Remote Sensing of Environment 247(2020).