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- Title
GF-7卫星多角度特征作物识别.
- Authors
孙, 智虎; 张, 锦水; 洪, 友堂; 杨, 珺雯; 朱, 爽
- Abstract
Multiangle remote sensing can provide richer, multidirectional features for ground object observation, improve the distinguishability between land types, and lay a solid data foundation for the accurate identification of ground cover. GF-7 is the first domestic sub meter surveying and mapping satellite after ZY-3 satellite, which brings an opportunity to solve the problem of "foreign matter homospectrum" using multiangle characteristics and to improve the identification accuracy of crops. In this paper, GF-7 forward-looking and backward-looking panchromatic and backward-looking multispectral data are used, and various features combinations are input to the support vector machine classifier to analyze the influence of multiangle features on crop recognition accuracy relative to the spectral and texture features. Results show that compared with only spectral features, with the addition of the angle difference feature, the production accuracy of garlic and winter wheat increased by 4.07% and 3.15%, respectively, and the user accuracy increased by 6.73% and 2.12%, respectively. Compared with the combination of spectral and texture features, with the addition of the angle difference feature, the production accuracy of garlic and winter wheat increased by 3.14% and 1.01%, respectively, and the user accuracy increased by 5.11% and 0.67%, respectively. Through the analysis of McNemar test, the improvement of classification accuracy is stable, angle difference feature can effectively improve the identification accuracy of crops. Tracing it to its cause, the multiangle characteristics of GF-7 satellite have unique differences in the spectral response of different crop types during multiangle observation. The difference improves the separability between crops to ensure the accuracy of crop remote sensing mapping.
- Subjects
WINTER wheat; REMOTE sensing; GARLIC; AGRICULTURE; ANGLES
- Publication
Journal of Remote Sensing, 2023, Vol 27, Issue 9, p2127
- ISSN
1007-4619
- Publication type
Article
- DOI
10.11834/jrs.20221644