Next Article in Journal
A Multi-Sensor Fusion Framework Based on Coupled Residual Convolutional Neural Networks
Previous Article in Journal
Single-Pass Soil Moisture Retrievals Using GNSS-R: Lessons Learned
Previous Article in Special Issue
Detection of Crop Seeding and Harvest through Analysis of Time-Series Sentinel-1 Interferometric SAR Data
Article

Mapping Winter Wheat with Combinations of Temporally Aggregated Sentinel-2 and Landsat-8 Data in Shandong Province, China

1
College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China
2
School of Geography, Nanjing Normal University, Nanjing 210023, China
3
College of Agriculture, Nanjing Agricultural University, Nanjing 210095, China
4
Department of Geosciences and Natural Resource Management, University of Copenhagen, 1350 Copenhagen, Denmark
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(12), 2065; https://doi.org/10.3390/rs12122065
Received: 18 May 2020 / Revised: 22 June 2020 / Accepted: 24 June 2020 / Published: 26 June 2020
Winter wheat is one of the major cereal crops in China. The spatial distribution of winter wheat planting areas is closely related to food security; however, mapping winter wheat with time-series finer spatial resolution satellite images across large areas is challenging. This paper explores the potential of combining temporally aggregated Landsat-8 OLI and Sentinel-2 MSI data available via the Google Earth Engine (GEE) platform for mapping winter wheat in Shandong Province, China. First, six phenological median composites of Landsat-8 OLI and Sentinel-2 MSI reflectance measures were generated by a temporal aggregation technique according to the winter wheat phenological calendar, which covered seedling, tillering, over-wintering, reviving, jointing-heading and maturing phases, respectively. Then, Random Forest (RF) classifier was used to classify multi-temporal composites but also mono-temporal winter wheat development phases and mono-sensor data. The results showed that winter wheat could be classified with an overall accuracy of 93.4% and F1 measure (the harmonic mean of producer’s and user’s accuracy) of 0.97 with temporally aggregated Landsat-8 and Sentinel-2 data were combined. As our results also revealed, it was always good to classify multi-temporal images compared to mono-temporal imagery (the overall accuracy dropped from 93.4% to as low as 76.4%). It was also good to classify Landsat-8 OLI and Sentinel-2 MSI imagery combined instead of classifying them individually. The analysis showed among the mono-temporal winter wheat development phases that the maturing phase’s and reviving phase’s data were more important than the data for other mono-temporal winter wheat development phases. In sum, this study confirmed the importance of using temporally aggregated Landsat-8 OLI and Sentinel-2 MSI data combined and identified key winter wheat development phases for accurate winter wheat classification. These results can be useful to benefit on freely available optical satellite data (Landsat-8 OLI and Sentinel-2 MSI) and prioritize key winter wheat development phases for accurate mapping winter wheat planting areas across China and elsewhere. View Full-Text
Keywords: multi-temporal; winter wheat; temporal aggregation; Google earth engine; crop development phase multi-temporal; winter wheat; temporal aggregation; Google earth engine; crop development phase
Show Figures

Graphical abstract

MDPI and ACS Style

Xu, F.; Li, Z.; Zhang, S.; Huang, N.; Quan, Z.; Zhang, W.; Liu, X.; Jiang, X.; Pan, J.; Prishchepov, A.V. Mapping Winter Wheat with Combinations of Temporally Aggregated Sentinel-2 and Landsat-8 Data in Shandong Province, China. Remote Sens. 2020, 12, 2065. https://doi.org/10.3390/rs12122065

AMA Style

Xu F, Li Z, Zhang S, Huang N, Quan Z, Zhang W, Liu X, Jiang X, Pan J, Prishchepov AV. Mapping Winter Wheat with Combinations of Temporally Aggregated Sentinel-2 and Landsat-8 Data in Shandong Province, China. Remote Sensing. 2020; 12(12):2065. https://doi.org/10.3390/rs12122065

Chicago/Turabian Style

Xu, Feng, Zhaofu Li, Shuyu Zhang, Naitao Huang, Zongyao Quan, Wenmin Zhang, Xiaojun Liu, Xiaosan Jiang, Jianjun Pan, and Alexander V. Prishchepov 2020. "Mapping Winter Wheat with Combinations of Temporally Aggregated Sentinel-2 and Landsat-8 Data in Shandong Province, China" Remote Sensing 12, no. 12: 2065. https://doi.org/10.3390/rs12122065

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
Back to TopTop