Research on vegetation cover extraction method of summer maize based on UAV visible light image

Haiyu Xu, Yubin Lan, Shuailing Zhang, Bingquan Tian, Hailin Yu, Xiaoli Wang, Shengli Zhao, Zesheng Wang, Dongjian Yang, Jing Zhao

Abstract


Abstract: The vegetation coverage is the most important indicator to measure the surface vegetation status.  In order to effectively extract the vegetation coverage of crops and achieve fast and accurate acquisition of the vegetation coverage information during the small bell mouth period of summer corn.  The visible light images of the unmanned farm was obtained using the unmanned aerial vehicle remote sensing technology, and four visible light vegetation indexes, including the Visible-band difference vegetation index (VDVI), Excess green (EXG), Normalized green-blue difference index (NGBDI) and Red-green-blue ratio vegetation index (RGBRI), were extracted from the image.  Using three methods: maximum entropy threshold method based on vegetation index, threshold method based on vegetation index, and pixel binary method based on vegetation index, extract vegetation coverage information of summer maize during the small horn mouth period in the experimental area.  Using the supervised classification results of Support Vector Machine (SVM) as the true values, evaluate the accuracy of vegetation coverage extracted by the three methods separately.  The results showed that the maximum entropy threshold method based on the NGBDI vegetation index image had the best extraction effect and the highest accuracy of vegetation coverage at the small bell mouth stage of summer corn in the experimental area, the coverage was 0.597602, and the extraction error (EF) was 1.26% compared with the true value; In the vegetation index threshold method, the vegetation coverage extraction effect of EXG is the second, the coverage is 0.558811, and the extraction error (EF) compared with the true value is 7.67%; The pixel dichotomy based on vegetation index combined with EXG has a good effect on vegetation coverage extraction, the coverage is 0.456506, and the extraction error (EF) is 24.58% compared with the true value.  The NGBDI vegetation index image based on the visible light image of UAV can realize the rapid and accurate extraction of the vegetation coverage of summer corn at the small bell mouth stage using the maximum entropy threshold method, which can provide a reference for UAV remote sensing monitoring.

Keywords: unmanned farm; UAV; visible light shadow image; vegetation index; vegetation coverage

DOI: 10.33440/j.ijpaa.20230601.197

 

Citation: Xu H Y?Lan Y B?Zhang S L?Tian B Q?Yu H L?Wang X L?Zhao S L?Wang Z S?Yang D J?Zhao J.  Research on vegetation cover extraction method of summer maize based on UAV visible light image.  Int J Precis Agric Aviat, 2023; 6(1): 44–51.


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