Next Article in Journal
A New Fluorescence Quantum Yield Efficiency Retrieval Method to Simulate Chlorophyll Fluorescence under Natural Conditions
Previous Article in Journal
Correction: Xu, M., et al. A Modified Geometrical Optical Model of Row Crops Considering Multiple Scattering Frame. Remote Sensing 2020, 12, 3600
Article

Crop Classification Using Multi-Temporal Sentinel-2 Data in the Shiyang River Basin of China

by 1,2, 1 and 1,*
1
State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
2
University of Chinese Academy of Sciences, Beijing 100101, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(24), 4052; https://doi.org/10.3390/rs12244052
Received: 22 October 2020 / Revised: 2 December 2020 / Accepted: 9 December 2020 / Published: 11 December 2020
(This article belongs to the Section Remote Sensing in Agriculture and Vegetation)
Timely and accurate crop classification is of enormous significance for agriculture management. The Shiyang River Basin, an inland river basin, is one of the most prominent water resource shortage regions with intensive agriculture activities in northwestern China. However, a free crop map with high spatial resolution is not available in the Shiyang River Basin. The European Space Agency (ESA) satellite Sentinel-2 has multi-spectral bands ranging in the visible-red edge-near infrared-shortwave infrared (VIS-RE-NIR-SWIR) spectrum. Understanding the impact of spectral-temporal information on crop classification is helpful for users to select optimized spectral bands combinations and temporal window in crop mapping when using Sentinel-2 data. In this study, multi-temporal Sentinel-2 data acquired in the growing season in 2019 were applied to the random forest algorithm to generate the crop classification map at 10 m spatial resolution for the Shiyang River Basin. Four experiments with different combinations of feature sets were carried out to explore which Sentinel-2 information was more effective for higher crop classification accuracy. The results showed that the augment of multi-spectral and multi-temporal information of Sentinel-2 improved the accuracy of crop classification remarkably, and the improvement was firmly related to strategies of feature selections. Compared with other bands, red-edge band 1 (RE-1) and shortwave-infrared band 1 (SWIR-1) of Sentinel-2 showed a higher competence in crop classification. The combined application of images in the early, middle and late crop growth stage is significant for achieving optimal performance. A relatively accurate classification (overall accuracy = 0.94) was obtained by utilizing the pivotal spectral bands and dates of image. In addition, a crop map with a satisfied accuracy (overall accuracy > 0.9) could be generated as early as late July. This study gave an inspiration in selecting targeted spectral bands and period of images for acquiring more accurate and timelier crop map. The proposed method could be transferred to other arid areas with similar agriculture structure and crop phenology. View Full-Text
Keywords: crop classification; sentinel-2; random forest; red-edge band; short-wave infrared crop classification; sentinel-2; random forest; red-edge band; short-wave infrared
Show Figures

Graphical abstract

MDPI and ACS Style

Yi, Z.; Jia, L.; Chen, Q. Crop Classification Using Multi-Temporal Sentinel-2 Data in the Shiyang River Basin of China. Remote Sens. 2020, 12, 4052. https://doi.org/10.3390/rs12244052

AMA Style

Yi Z, Jia L, Chen Q. Crop Classification Using Multi-Temporal Sentinel-2 Data in the Shiyang River Basin of China. Remote Sensing. 2020; 12(24):4052. https://doi.org/10.3390/rs12244052

Chicago/Turabian Style

Yi, Zhiwei; Jia, Li; Chen, Qiting. 2020. "Crop Classification Using Multi-Temporal Sentinel-2 Data in the Shiyang River Basin of China" Remote Sens. 12, no. 24: 4052. https://doi.org/10.3390/rs12244052

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop