Adaptation of SAVI to estimate the leaf area index considering different land covers in a Brazilian atlantic forest area
dc.contributor.author | Nery, Liliane Moreira [UNESP] | |
dc.contributor.author | Gomes, Gabriela [UNESP] | |
dc.contributor.author | de Moura, Anderson Trindade [UNESP] | |
dc.contributor.author | dos Santos, Arthur Pereira [UNESP] | |
dc.contributor.author | Toniolo, Bruno Pereira [UNESP] | |
dc.contributor.author | da Cunha e Silva, Darllan Collins [UNESP] | |
dc.contributor.institution | Universidade Estadual Paulista (UNESP) | |
dc.date.accessioned | 2025-04-29T18:49:16Z | |
dc.date.issued | 2025-04-01 | |
dc.description.abstract | This study discusses the relationship between the spectral behavior of vegetation and vegetation indexes, using Landsat satellite images to estimate the Leaf Area Index (LAI) in a protected area in the state of São Paulo, Brazil. We calculated the Normalized Difference Vegetation Index (NDVI) for different types of land cover and found specific correction coefficients (L) from the Soil Adjusted Vegetation Index (SAVI) to mitigate LAI saturation. The areas without vegetation presented mostly negative NDVI values or values lower than 0.5. Therefore, we assume that these areas should correspond to a correction coefficient of L equal to 0. Based on the analysis of each year, we assume that the areas of low vegetation cover should correspond to a correction coefficient of L equal to 1. The positive correlation between SAVI and LAI indicates that SAVI can be used to estimate LAI in the study area following the proposed methodology. Therefore, by exploring the possibility of using the adjustment factor L regarding the zonal statistics of NDVI to mitigate the effects of saturation, it is possible to adopt a local model for calculating LAI. The study highlights the importance of adapting vegetation indexes to local characteristics and the need to establish specific algorithms for calculating LAI in different regions. | en |
dc.description.affiliation | São Paulo State University (UNESP) Institute of Science and Technology, Três de Março, 511, São Paulo | |
dc.description.affiliationUnesp | São Paulo State University (UNESP) Institute of Science and Technology, Três de Março, 511, São Paulo | |
dc.description.sponsorship | Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) | |
dc.description.sponsorshipId | CAPES: Finance Code 001 | |
dc.identifier | http://dx.doi.org/10.1007/s40808-025-02300-7 | |
dc.identifier.citation | Modeling Earth Systems and Environment, v. 11, n. 2, 2025. | |
dc.identifier.doi | 10.1007/s40808-025-02300-7 | |
dc.identifier.issn | 2363-6211 | |
dc.identifier.issn | 2363-6203 | |
dc.identifier.scopus | 2-s2.0-85218100466 | |
dc.identifier.uri | https://hdl.handle.net/11449/300333 | |
dc.language.iso | eng | |
dc.relation.ispartof | Modeling Earth Systems and Environment | |
dc.source | Scopus | |
dc.subject | Itupararanga EPA | |
dc.subject | Spatial analysis | |
dc.subject | Statistical analysis | |
dc.subject | Vegetation indexes | |
dc.title | Adaptation of SAVI to estimate the leaf area index considering different land covers in a Brazilian atlantic forest area | en |
dc.type | Artigo | pt |
dspace.entity.type | Publication | |
unesp.author.orcid | 0000-0002-5352-5316[1] | |
unesp.campus | Universidade Estadual Paulista (UNESP), Instituto de Ciência e Tecnologia, Sorocaba | pt |