| dc.contributor.author | Zhang, Shoujing | ru |
| dc.contributor.author | He, Runhai | ru |
| dc.contributor.author | Li, Fusheng | ru |
| dc.contributor.author | Zhang, Zhenxing | ru |
| dc.coverage.spatial | Минск | ru |
| dc.date.accessioned | 2025-04-21T07:31:25Z | |
| dc.date.available | 2025-04-21T07:31:25Z | |
| dc.date.issued | 2024 | |
| dc.identifier.citation | 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. | ru |
| dc.identifier.uri | https://rep.bntu.by/handle/data/154848 | |
| dc.description.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. | ru |
| dc.language.iso | en | ru |
| dc.publisher | БНТУ | ru |
| dc.title | Vegetation index methods: a comparative analysis of NDVI, EVI and SAVI | ru |
| dc.type | Article | ru |
