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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Main Authors: Rodrigo Moura Pereira, Derblai Casaroli, Lucas Melo Vellame, José Alves Júnior, Adão Wagner Pêgo Evangelista
Format: Article
Language:English
Published: Universidade Federal de Goiás 2016-06-01
Series:Pesquisa Agropecuária Tropical
Subjects:
Online Access:https://www.revistas.ufg.br/pat/article/view/39303/21157
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spelling 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
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AT lucasmelovellame sugarcaneleafareaestimateobtainedfromthecorrectednormalizeddifferencevegetationindexndvi
AT josealvesjunior sugarcaneleafareaestimateobtainedfromthecorrectednormalizeddifferencevegetationindexndvi
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