Crop Classification Based on Red Edge Features Analysis of GF-6 WFV Data
A red edge band is a sensitive spectral band of crops, which helps to improve the accuracy of crop classification. In view of the characteristics of GF-6 WFV data with multiple red edge bands, this paper took Hengshui City, Hebei Province, China, as the study area to carry out red edge feature analy...
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MDPI AG
2021-06-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/13/4328 |
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| author | Yupeng Kang Qingyan Meng Miao Liu Youfeng Zou Xuemiao Wang |
| author_facet | Yupeng Kang Qingyan Meng Miao Liu Youfeng Zou Xuemiao Wang |
| author_sort | Yupeng Kang |
| collection | DOAJ |
| description | A red edge band is a sensitive spectral band of crops, which helps to improve the accuracy of crop classification. In view of the characteristics of GF-6 WFV data with multiple red edge bands, this paper took Hengshui City, Hebei Province, China, as the study area to carry out red edge feature analysis and crop classification, and analyzed the influence of different red edge features on crop classification. On the basis of GF-6 WFV red edge band spectral analysis, different red edge feature extraction and red edge indices feature importance evaluation, 12 classification schemes were designed based on GF-6 WFV of four bands (only including red, green, blue and near-infrared bands), stepwise discriminant analysis (SDA) and random forest (RF) method were used for feature selection and importance evaluation, and RF classification algorithm was used for crop classification. The results show the following: (1) The red edge 750 band of GF-6 WFV data contains more information content than the red edge 710 band. Compared with the red edge 750 band, the red edge 710 band is more conducive to improving the separability between different crops, which can improve the classification accuracy; (2) According to the classification results of different red edge indices, compared with the SDA method, the RF method is more accurate in the feature importance evaluation; (3) Red edge spectral features, red edge texture features and red edge indices can improve the accuracy of crop classification in different degrees, and the red edge features based on red edge 710 band can improve the accuracy of crop classification more effectively. This study improves the accuracy of remote sensing classification of crops, and can provide reference for the application of GF-6 WFV data and its red edge bands in agricultural remote sensing. |
| first_indexed | 2024-03-10T10:05:29Z |
| format | Article |
| id | doaj.art-55b28d02fd624d31ac09257b68c1e5e4 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T10:05:29Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-55b28d02fd624d31ac09257b68c1e5e42023-11-22T01:35:52ZengMDPI AGSensors1424-82202021-06-012113432810.3390/s21134328Crop Classification Based on Red Edge Features Analysis of GF-6 WFV DataYupeng Kang0Qingyan Meng1Miao Liu2Youfeng Zou3Xuemiao Wang4School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, ChinaSchool of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, ChinaA red edge band is a sensitive spectral band of crops, which helps to improve the accuracy of crop classification. In view of the characteristics of GF-6 WFV data with multiple red edge bands, this paper took Hengshui City, Hebei Province, China, as the study area to carry out red edge feature analysis and crop classification, and analyzed the influence of different red edge features on crop classification. On the basis of GF-6 WFV red edge band spectral analysis, different red edge feature extraction and red edge indices feature importance evaluation, 12 classification schemes were designed based on GF-6 WFV of four bands (only including red, green, blue and near-infrared bands), stepwise discriminant analysis (SDA) and random forest (RF) method were used for feature selection and importance evaluation, and RF classification algorithm was used for crop classification. The results show the following: (1) The red edge 750 band of GF-6 WFV data contains more information content than the red edge 710 band. Compared with the red edge 750 band, the red edge 710 band is more conducive to improving the separability between different crops, which can improve the classification accuracy; (2) According to the classification results of different red edge indices, compared with the SDA method, the RF method is more accurate in the feature importance evaluation; (3) Red edge spectral features, red edge texture features and red edge indices can improve the accuracy of crop classification in different degrees, and the red edge features based on red edge 710 band can improve the accuracy of crop classification more effectively. This study improves the accuracy of remote sensing classification of crops, and can provide reference for the application of GF-6 WFV data and its red edge bands in agricultural remote sensing.https://www.mdpi.com/1424-8220/21/13/4328GF-6 WFV datared edge featurescrop classificationspectral analysisred edge indicesfeature evaluation |
| spellingShingle | Yupeng Kang Qingyan Meng Miao Liu Youfeng Zou Xuemiao Wang Crop Classification Based on Red Edge Features Analysis of GF-6 WFV Data Sensors GF-6 WFV data red edge features crop classification spectral analysis red edge indices feature evaluation |
| title | Crop Classification Based on Red Edge Features Analysis of GF-6 WFV Data |
| title_full | Crop Classification Based on Red Edge Features Analysis of GF-6 WFV Data |
| title_fullStr | Crop Classification Based on Red Edge Features Analysis of GF-6 WFV Data |
| title_full_unstemmed | Crop Classification Based on Red Edge Features Analysis of GF-6 WFV Data |
| title_short | Crop Classification Based on Red Edge Features Analysis of GF-6 WFV Data |
| title_sort | crop classification based on red edge features analysis of gf 6 wfv data |
| topic | GF-6 WFV data red edge features crop classification spectral analysis red edge indices feature evaluation |
| url | https://www.mdpi.com/1424-8220/21/13/4328 |
| work_keys_str_mv | AT yupengkang cropclassificationbasedonrededgefeaturesanalysisofgf6wfvdata AT qingyanmeng cropclassificationbasedonrededgefeaturesanalysisofgf6wfvdata AT miaoliu cropclassificationbasedonrededgefeaturesanalysisofgf6wfvdata AT youfengzou cropclassificationbasedonrededgefeaturesanalysisofgf6wfvdata AT xuemiaowang cropclassificationbasedonrededgefeaturesanalysisofgf6wfvdata |