Sugarcane leaf area estimate obtained from the corrected Normalized Difference Vegetation Index (NDVI)
Large farmland areas and the knowledge on the interaction between solar radiation and vegetation canopies have increased the use of data from orbital remote sensors in sugarcane monitoring. However, the constituents of the atmosphere affect the reflectance values obtained by imaging sensors. This st...
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doaj-052c735aa1fb4326bb8fb5f2679af3d62020-11-24T22:47:42ZengUniversidade Federal de Goiás Pesquisa Agropecuária Tropical1983-40632016-06-0146214014810.1590/1983-40632016v4639303Sugarcane leaf area estimate obtained from the corrected Normalized Difference Vegetation Index (NDVI)Rodrigo Moura Pereira0Derblai Casaroli1Lucas Melo Vellame2José Alves Júnior3Adão Wagner Pêgo Evangelista4Universidade Federal de GoiásUniversidade Federal de GoiásUniversidade Federal do Recôncavo da BahiaUniversidade Federal de GoiásUniversidade Federal de GoiásLarge farmland areas and the knowledge on the interaction between solar radiation and vegetation canopies have increased the use of data from orbital remote sensors in sugarcane monitoring. However, the constituents of the atmosphere affect the reflectance values obtained by imaging sensors. This study aimed at improving a sugarcane Leaf Area Index (LAI) estimation model, concerning the Normalized Difference Vegetation Index (NDVI) subjected to atmospheric correction. The model generated by the NDVI with atmospheric correction showed the best results (R2 = 0.84; d = 0.95; MAE = 0.44; RMSE = 0.55), in relation to the other models compared. LAI estimation with this model, during the sugarcane plant cycle, reached a maximum of 4.8 at the vegetative growth phase and 2.3 at the end of the maturation phase. Thus, the use of atmospheric correction to estimate the sugarcane LAI is recommended, since this procedure increases the correlations between the LAI estimated by image and by plant parameters.https://www.revistas.ufg.br/pat/article/view/39303/21157Saccharum spp.vegetal growthimage analysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Rodrigo Moura Pereira Derblai Casaroli Lucas Melo Vellame José Alves Júnior Adão Wagner Pêgo Evangelista |
spellingShingle |
Rodrigo Moura Pereira Derblai Casaroli Lucas Melo Vellame José Alves Júnior Adão Wagner Pêgo Evangelista Sugarcane leaf area estimate obtained from the corrected Normalized Difference Vegetation Index (NDVI) Pesquisa Agropecuária Tropical Saccharum spp. vegetal growth image analysis |
author_facet |
Rodrigo Moura Pereira Derblai Casaroli Lucas Melo Vellame José Alves Júnior Adão Wagner Pêgo Evangelista |
author_sort |
Rodrigo Moura Pereira |
title |
Sugarcane leaf area estimate obtained from the corrected Normalized Difference Vegetation Index (NDVI) |
title_short |
Sugarcane leaf area estimate obtained from the corrected Normalized Difference Vegetation Index (NDVI) |
title_full |
Sugarcane leaf area estimate obtained from the corrected Normalized Difference Vegetation Index (NDVI) |
title_fullStr |
Sugarcane leaf area estimate obtained from the corrected Normalized Difference Vegetation Index (NDVI) |
title_full_unstemmed |
Sugarcane leaf area estimate obtained from the corrected Normalized Difference Vegetation Index (NDVI) |
title_sort |
sugarcane leaf area estimate obtained from the corrected normalized difference vegetation index (ndvi) |
publisher |
Universidade Federal de Goiás |
series |
Pesquisa Agropecuária Tropical |
issn |
1983-4063 |
publishDate |
2016-06-01 |
description |
Large farmland areas and the knowledge on the interaction between solar radiation and vegetation canopies have increased the use of data from orbital remote sensors in sugarcane monitoring. However, the constituents of the atmosphere affect the reflectance values obtained by imaging sensors. This study aimed at improving a sugarcane Leaf Area Index (LAI) estimation model, concerning the Normalized Difference Vegetation Index (NDVI) subjected to atmospheric correction. The model generated by the NDVI with atmospheric correction showed the best results (R2 = 0.84; d = 0.95; MAE = 0.44; RMSE = 0.55), in relation to the other models compared. LAI estimation with this model, during the sugarcane plant cycle, reached a maximum of 4.8 at the vegetative growth phase and 2.3 at the end of the maturation phase. Thus, the use of atmospheric correction to estimate the sugarcane LAI is recommended, since this procedure increases the correlations between the LAI estimated by image and by plant parameters. |
topic |
Saccharum spp. vegetal growth image analysis |
url |
https://www.revistas.ufg.br/pat/article/view/39303/21157 |
work_keys_str_mv |
AT rodrigomourapereira sugarcaneleafareaestimateobtainedfromthecorrectednormalizeddifferencevegetationindexndvi AT derblaicasaroli sugarcaneleafareaestimateobtainedfromthecorrectednormalizeddifferencevegetationindexndvi AT lucasmelovellame sugarcaneleafareaestimateobtainedfromthecorrectednormalizeddifferencevegetationindexndvi AT josealvesjunior sugarcaneleafareaestimateobtainedfromthecorrectednormalizeddifferencevegetationindexndvi AT adaowagnerpegoevangelista sugarcaneleafareaestimateobtainedfromthecorrectednormalizeddifferencevegetationindexndvi |
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1725680899392012288 |