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Examining rice distribution and cropping intensity in a mixed single- and double-cropping region in South China using all available Sentinel 1/ 2 images
He, Yingli1,2; Dong, Jinwei1; Liao, Xiaoyong1; Sun, Li3; Wang, Zhipan4; You, Nanshan1,2; Li, Zhichao1; Fu, Ping5,6
2021-09-01
Source PublicationINTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
ISSN1569-8432
Volume101Pages:15
Corresponding AuthorDong, Jinwei(dongjw@igsnrr.ac.cn)
AbstractPaddy rice agriculture in Southern China, especially Hunan Province, has been suffered from soil contamination. Several policies including rice fallow and decreasing cropping intensity have been implemented for food safety here. It is thus important to monitor rice planting area and cropping intensity to understand the effectiveness of those land-use policies. However, it is challenging to map rice planting areas due to the complex cropping systems (mixed single- and double-cropping), persistent cloud covers, small crop fields, let alone cropping intensity. Here we used all the available Sentinel-2 and all-weather Sentinel-1 imagery to generate a time series data cube to extract paddy rice planting areas and the rice cropping intensity in the Changsha, Zhuzhou, and Xiangtan areas, which is a traditional rice-growing region with small farms in China. Specifically, we investigated the performances of different features (i.e., spectral, seasonal, polarization backscatter) by comparing five scenarios with different combinations of sensors and features, and identified the most suitable features for certain rice types (early, middle, and late rice). The random forest classifier was used for the classification in the Google Earth Engine (GEE) platform, and a reference map in 2017 based on visual interpretation on the GaoFen-2 images were used for collecting the training and validation samples. The results showed the combined data from Sentinel-1/2 generally outperformed classifications using only a single sensor (Sentinel-1/2), but the contribution of different sensors to certain rice types varied. The early, middle and late rice with the highest accuracies within the five scenarios had the overall accuracies of 85%, 95%, and 95%, respectively (F1 = 0.55, 0.85, and 0.85). The compositing of different types of rice allowed us to generate the rice cropping intensity map with an overall accuracy of 81%, which to our limited knowledge is the first effort to map cropping intensity at 10-m resolution in such a fragmented subtropical region. The result showed the single cropping dominated the rice cropping system in the study area 88%, which used to be a typical area with double cropping of rice. Our study demonstrates the potential of mapping rice cropping intensity in a cloudy and highly fragmented region in South China using all the available Sentinel-1/2 data, which would advance our understanding of regional rice production and mitigation of soil contamination.
KeywordRice mapping Cropping intensity Sentinel-1 2 Time series Google Earth Engine
DOI10.1016/j.jag.2021.102351
WOS KeywordGROSS PRIMARY PRODUCTION ; TIME-SERIES ; MEKONG DELTA ; LAND-USE ; CLASSIFICATION ; INDEX ; WATER ; RED ; FOREST ; AREA
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[41871349] ; Chinese Academy of Sciences the Strategic Priority Research Program[XDA19040301] ; Key Research Program of Frontier Sciences[QYZDB-SSW-DQC005]
Funding OrganizationNational Natural Science Foundation of China ; Chinese Academy of Sciences the Strategic Priority Research Program ; Key Research Program of Frontier Sciences
WOS Research AreaRemote Sensing
WOS SubjectRemote Sensing
WOS IDWOS:000658897800001
PublisherELSEVIER
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/164071
Collection中国科学院地理科学与资源研究所
Corresponding AuthorDong, Jinwei
Affiliation1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Chinese Acad Agr Engn, Remote Sensing Applicat Ctr, Beijing 100125, Peoples R China
4.Inst Land & Resources Planning Hunan Prov, Changsha 410007, Peoples R China
5.Univ Nottingham Ningbo China, Fac Sci & Engn, Sch Geog Sci, Ningbo 315100, Peoples R China
6.Univ Nottingham Ningbo China, Fac Sci & Engn, Geospatial Res Grp, Ningbo 315100, Peoples R China
Recommended Citation
GB/T 7714
He, Yingli,Dong, Jinwei,Liao, Xiaoyong,et al. Examining rice distribution and cropping intensity in a mixed single- and double-cropping region in South China using all available Sentinel 1/ 2 images[J]. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,2021,101:15.
APA He, Yingli.,Dong, Jinwei.,Liao, Xiaoyong.,Sun, Li.,Wang, Zhipan.,...&Fu, Ping.(2021).Examining rice distribution and cropping intensity in a mixed single- and double-cropping region in South China using all available Sentinel 1/ 2 images.INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,101,15.
MLA He, Yingli,et al."Examining rice distribution and cropping intensity in a mixed single- and double-cropping region in South China using all available Sentinel 1/ 2 images".INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 101(2021):15.
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