Spatiotemporal Dynamics of the Northern Limit of Winter Wheat in China Using MODIS Time Series Images
Abstract
:1. Introduction
2. Study Area and Datasets
2.1. Study Area
2.2. Datasets and Preprocessing
2.2.1. MODIS EVI2 Datasets
2.2.2. Landsat Images
2.2.3. Sampling Point Data
2.2.4. Other Data Sources
3. Methodology
3.1. Winter Wheat Extraction
3.2. Accuracy Assessment
3.3. Dynamic Degree Model of Winter Wheat Planting Area Change
3.4. Extraction of the NLWW Using Kernel Density Estimation
3.5. Spatiotemporal Dynamics of the NLWW
4. Results
4.1. Accuracy Evaluation of MODIS-Derived Winter Wheat Maps
4.2. Spatiotemporal Dynamics of Winter Wheat Planting Area
4.3. Latitudinal Dynamics of the NLWW during the Period 2001–2019
4.4. Elevational Gradient Distributions of the NLWW during the Period 2001–2019
5. Discussion
5.1. Analysis of Driving Factors for the Gap Between the Potential NLWW and the Actual NLWW
5.2. Uncertainties in MODIS-Derived Winter Wheat Maps
6. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Year | Data Type | Acquisition Dates (yyyymmdd) | Cloud Cover (%) |
---|---|---|---|
2001 | ETM+ (Enhanced Thematic Mapper Plus) | 20001210, 20010401, 20010417 | 0.01, 0.10, 0.00 |
2007 | TM (Thematic Mapper) | 20061203, 20070410, 20070512 | 0.02, 0.00, 0.00 |
2014 | OLI (Operational Land Imager) | 20131120, 20140429, 20140819 | 0.94, 0.35, 0.11 |
2019 | OLI (Operational Land Imager) | 20181204, 20190513, 20190614 | 0.07, 0.11, 0.72 |
Classified Results | Field Survey Data (Sites) in 2019 | |||
---|---|---|---|---|
Winter Wheat | Non-Winter Wheat | Classified Sites | UA | |
Winter wheat | 549 | 34 | 583 | 94.17% |
Non-winter wheat | 29 | 589 | 618 | 95.31% |
Field survey sites | 578 | 623 | 1201 | OA = 94.75% |
PA | 94.98% | 94.54% | Kappa = 0.895 |
Accuracy | Year | |||
---|---|---|---|---|
2001 | 2007 | 2014 | 2019 | |
UA (Winter wheat) | 73.93% | 82.08% | 79.42% | 80.05% |
PA (Winter wheat) | 72.03% | 69.73% | 72.31% | 75.90% |
UA (Non-winter wheat) | 95.75% | 97.17% | 97.41% | 96.77% |
PA (Non-winter wheat) | 96.13% | 98.56% | 98.23% | 97.45% |
Overall | 92.93% | 96.06% | 96.00% | 94.88% |
kappa | 0.689 | 0.733 | 0.735 | 0.750 |
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Chen, S.; Fan, L.; Liang, S.; Chen, H.; Sun, X.; Hu, Y.; Liu, Z.; Sun, J.; Yang, P. Spatiotemporal Dynamics of the Northern Limit of Winter Wheat in China Using MODIS Time Series Images. Remote Sens. 2020, 12, 2382. https://doi.org/10.3390/rs12152382
Chen S, Fan L, Liang S, Chen H, Sun X, Hu Y, Liu Z, Sun J, Yang P. Spatiotemporal Dynamics of the Northern Limit of Winter Wheat in China Using MODIS Time Series Images. Remote Sensing. 2020; 12(15):2382. https://doi.org/10.3390/rs12152382
Chicago/Turabian StyleChen, Shi, Lingling Fan, Shefang Liang, Hao Chen, Xiao Sun, Yanan Hu, Zhenhuan Liu, Jing Sun, and Peng Yang. 2020. "Spatiotemporal Dynamics of the Northern Limit of Winter Wheat in China Using MODIS Time Series Images" Remote Sensing 12, no. 15: 2382. https://doi.org/10.3390/rs12152382