Vegetation index methods: a comparative analysis of NDVI, EVI and SAVI
Bibliographic entry
Vegetation index methods: a comparative analysis of NDVI, EVI and SAVI / Shoujing Zhang, Runhai He, Fusheng Li, Zhenxing Zhang // Новые горизонты – 2024 : сборник материалов XI Белорусско-китайского молодежного инновационного форума, 21-22 ноября 2024 года / Белорусский национальный технический университет. – Минск : БНТУ, 2024. – Т. 1. – С. 87-88.
Abstract
This study emphasizes the importance of monitoring and predicting plant functional traits for ecological and agricultural research, particularly in the context of climate change. Hyperspectral remote sensing is a key tool for studying vegetation health and ecosystem dynamics due to its efficiency and wide coverage. Common modeling methods include vegetation indices, partial least squares regression, and process-based models. This paper compares the advantages and disadvantages of three vegetation indices: NDVI, EVI, and SAVI.