Journal of Geo-information Science ›› 2019, Vol. 21 ›› Issue (6): 918-927.doi: 10.12082/dqxxkx.2019.180424
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Fuyou TIAN1,2(), Bingfang WU1,2,*(
), Hongwei ZENG1, Zhaoxin HE1,2, Miao ZHANG1, Bofana José1,2
Received:
2018-08-30
Revised:
2018-12-27
Online:
2019-06-15
Published:
2019-06-15
Contact:
Bingfang WU
E-mail:tianfy@radi.ac.cn;wubf@radi.ac.cn
Supported by:
Fuyou TIAN, Bingfang WU, Hongwei ZENG, Zhaoxin HE, Miao ZHANG, Bofana José. Identifying Soybean Cropped Area with Sentinel-2 Data and Multi-Layer Neural Network[J].Journal of Geo-information Science, 2019, 21(6): 918-927.DOI:10.12082/dqxxkx.2019.180424
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Tab. 1
The detailed information of Sentinel-2 sensor"
波段 | Sentinel-2A | Sentinel-2B | ||||
---|---|---|---|---|---|---|
中心波长/nm | 波宽/nm | 中心波长/nm | 波宽/nm | 分辨率/m | ||
B2-蓝光 | 496.6 | 98 | 492.1 | 98 | 10 | |
B3-绿光 | 560.0 | 45 | 559 | 46 | 10 | |
B4-红光 | 664.5 | 38 | 665 | 39 | 10 | |
B5-红边1 | 703.9 | 19 | 703.8 | 20 | 20 | |
B6-红边2 | 740.2 | 18 | 739.1 | 18 | 20 | |
B7-红边3 | 782.5 | 28 | 779.7 | 28 | 20 | |
B8-近红外 | 835.1 | 145 | 833 | 133 | 10 | |
B8A-窄边近红外 | 864.8 | 33 | 864 | 32 | 20 |
Tab. 3
Comparison of four methods' accuracy (%)"
分类方法 | 其他作物 | 大豆 | 总体精度 | |||||
---|---|---|---|---|---|---|---|---|
用户精度 | 生产者精度 | F1-Score | 用户精度 | 生产者精度 | F1-Score | |||
随机森林 | 96.24 | 89.73 | 92.87 | 91.86 | 95.01 | 93.41 | 92.37 | |
支持向量机 | 94.37 | 92.66 | 93.51 | 92.15 | 94.36 | 93.24 | 93.51 | |
决策树 | 94.67 | 90.68 | 92.63 | 91.38 | 94.41 | 92.87 | 92.55 | |
神经网络 | 95.56 | 92.39 | 93.95 | 91.63 | 95.51 | 93.53 | 93.95 |
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