Assessment of the effectiveness of unmanned aerial system data post-processing algorithms to improve the accuracy of RGB vegetation indices

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Specific data post-processing algorithms for unmanned aerial systems can improve the accuracy of RGB vegetation indices such as NGRDI, VARI, ExG, TGI, and VEG. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

М. В. Тихонова; Yaroslava Zhigaleva; Nikita Aleksandrov; Alexey Buzylev; Alexis Yaroslavtsev

doi:10.21046/2070-7401-2025-22-5-29-37

January 1, 2025Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosaOpen Access

Assessment of the effectiveness of unmanned aerial system data post-processing algorithms to improve the accuracy of RGB vegetation indices

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Abstract

() , . , , RGB- (.Red, Green, Blue). . : NGRDI (.Normalized Green Red Difference Index), VARI (.Visible Atmospherically Resistant Index), ExG (.Excess Green Vegetation Index), TGI (.Triangular Greenness Index), VEG (.Vegetativen Index), . NDVI (.

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Тихонова et al. (2025) studied this question.

synapsesocial.com/papers/6a6af9e278a09e5ab7b39a24 https://doi.org/10.21046/2070-7401-2025-22-5-29-37

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Assessment of the effectiveness of unmanned aerial system data post-processing algorithms to improve the accuracy of RGB vegetation indices

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Assessment of the effectiveness of unmanned aerial system data post-processing algorithms to improve the accuracy of RGB vegetation indices

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