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Article summary:
1. Traditional methods of plant count estimation such as manual counting and ground-based platforms are time-consuming and difficult to implement over large regions.
2. Remote sensing platforms such as satellites and UAVs have been used to estimate plant count, but they are limited by resolution or cloud cover.
3. A method was developed in this study combining Hough transformation and peak detection algorithms to detect plant rows and seedlings using high-resolution UAV images.
Article analysis:
The article is generally reliable and trustworthy, providing a comprehensive overview of the current state of remote sensing technology for estimating plant counts in sunflower and maize at different seedling stages. The authors provide a thorough review of existing methods, including ground-based platforms, satellite imagery, and unmanned aerial vehicles (UAVs). They also discuss the limitations of these methods, such as low resolution or cloud cover with satellite imagery, which can make it difficult to accurately identify individual plants.
The authors then propose a new method based on the peak detection algorithm combined with Hough transformation for detecting plant rows and seedlings using high-resolution UAV images. This method is tested at three different study sites (Xinxiang City and Gongzhuling City in China, Langlade City in France) for both maize and sunflower crops at different growth stages. The results show that this method is accurate for counting equal spacing field crops (maize and sunflower), with an average accuracy greater than 93%.
The article does not appear to be biased or one-sided; it provides an objective overview of existing methods as well as a detailed description of the proposed method. The authors also provide evidence for their claims by citing relevant research studies throughout the article. Additionally, they discuss potential risks associated with their proposed method, such as leaf overlap making plant identification challenging in the late seedling stage.
In conclusion, this article is reliable and trustworthy due to its comprehensive coverage of existing methods for estimating plant counts as well as its detailed description of the proposed method based on peak detection algorithms combined with Hough transformation using high-resolution UAV images.