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RGB Imaging as a Tool for Remote Sensing of Characteristics of Terrestrial Plants: A Review. | LitMetric

AI Article Synopsis

  • Remote sensing techniques can help monitor how environmental changes affect terrestrial plants, aiding in their growth and productivity.
  • While multispectral and hyperspectral imaging provides detailed data, their complexity and cost make them less accessible; hence, there's a push for simpler RGB imaging methods.
  • The review discusses various strategies for enhancing the informational value of RGB images, including color models and machine learning, highlighting the need for further method development in this area.

Article Abstract

Approaches for remote sensing can be used to estimate the influence of changes in environmental conditions on terrestrial plants, providing timely protection of their growth, development, and productivity. Different optical methods, including the informative multispectral and hyperspectral imaging of reflected light, can be used for plant remote sensing; however, multispectral and hyperspectral cameras are technically complex and have a high cost. RGB imaging based on the analysis of color images of plants is definitely simpler and more accessible, but using this tool for remote sensing plant characteristics under changeable environmental conditions requires the development of methods to increase its informativity. Our review focused on using RGB imaging for remote sensing the characteristics of terrestrial plants. In this review, we considered different color models, methods of exclusion of background in color images of plant canopies, and various color indices and their relations to characteristics of plants, using regression models, texture analysis, and machine learning for the estimation of these characteristics based on color images, and some approaches to provide transformation of simple color images to hyperspectral and multispectral images. As a whole, our review shows that RGB imaging can be an effective tool for estimating plant characteristics; however, further development of methods to analyze color images of plants is necessary.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11085576PMC
http://dx.doi.org/10.3390/plants13091262DOI Listing

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