@MastersThesis{Simões:2021:VoZoMa,
author = "Sim{\~o}es, Gabriela Zoli",
title = "Sensoriamento remoto por VANT e orbital no estudo da
cana-de-a{\c{c}}{\'u}car: volumetria e zonas de manejo",
school = "Instituto Nacional de Pesquisas Espaciais (INPE)",
year = "2021",
address = "S{\~a}o Jos{\'e} dos Campos",
month = "2021-08-10",
keywords = "agricultura de precis{\~a}o, VANTs, zonas de manejo, sensores
orbitais, precision agriculture, UAVs, management zones, orbital
sensors.",
abstract = "O objetivo deste trabalho foi investigar o potencial de sensores
imageadores a bordo de um ve{\'{\i}}culo a{\'e}reo n{\~a}o
tripulado (VANT) e de sistemas sensores orbitais para o
monitoramento de vari{\'a}veis biof{\'{\i}}sicas e
bioqu{\'{\i}}micas da cana-de-a{\c{c}}{\'u}car na regi{\~a}o
de Ribeir{\~a}o Preto (SP). Para tanto, foram feitas estimativas
de altura dos doss{\'e}is e da produtividade dos talh{\~o}es,
avaliando a sua rela{\c{c}}{\~a}o com os {\'{\i}}ndices de
vegeta{\c{c}}{\~a}o (NDVI e EVI) em diferentes
resolu{\c{c}}{\~o}es espaciais (3 m, 10 m e 30 m) e
temperatura/emissividade do dossel. Para estimar a altura do
dossel, foram adquiridas imagens RGB de VANT ao longo do
per{\'{\i}}odo de crescimento da cana-de-a{\c{c}}{\'u}car na
safra de 2019/2020, as quais foram utilizadas para criar modelos
de superf{\'{\i}}cie e terreno por meio da t{\'e}cnica SfM. A
altura estimada foi obtida pela subtra{\c{c}}{\~a}o entre o MDS
e MDT e, a partir dela, calculou-se a taxa de crescimento da cana
nesse per{\'{\i}}odo. A produtividade e a produ{\c{c}}{\~a}o
total foram estimadas pelo m{\'e}todo da volumetria, para o qual
foi usada a altura estimada no {\'u}ltimo per{\'{\i}}odo
imageado. O c{\'a}lculo dos {\'{\i}}ndices foi efetuados com
imagens dos sat{\'e}lites PlanetScope, Sentinel-2 e Landsat 8,
adquiridas o mais pr{\'o}ximo poss{\'{\i}}vel da data do
imageamento com o VANT. Para a an{\'a}lise de
correla{\c{c}}{\~a}o espacial, o coeficiente de Pearson foi
calculado entre as alturas estimadas, os {\'{\I}}ndices de
Vegeta{\c{c}}{\~a}o, e temperatura e emissividade, sendo um
ponto selecionado para avaliar se h{\'a} correla{\c{c}}{\~a}o
temporal entre a altura e os IVs. Os dados de temperatura e
emissividade foram obtidosdo sensor ASTER. Por fim, foram
constru{\'{\i}}dos mapas de zonas de manejo pelo m{\'e}todo de
McQuitty e k-means, usando, informa{\c{c}}{\~o}es da taxa de
crescimento e IVs. Os modelos de altura retrataram as fases de
crescimento da cana, permitindo a identifica{\c{c}}{\~a}o de
falhas no plantio e regi{\~o}es com menor crescimento, no
entanto, o uso de GCP ou RTK poderiam minimizar os erros e
melhorar a qualidade dos modelos. A altura estimada n{\~a}o
apresentou correla{\c{c}}{\~a}o espacial com os IVs. Nem a
temperatura ou a emissividade apresentaram correla{\c{c}}{\~a}o
com a altura, todavia dados com maior resolu{\c{c}}{\~a}o
espacial poderiam trazer melhores resultados. Quanto {\`a}s Zonas
de Manejo, todos os sensores orbitais tiveram bons resultados.
Tanto o m{\'e}todo, quantos as vari{\'a}veis de entrada
influenciaram nos resultados, sendo recomendada o uso de duas ZMs,
tendo como vari{\'a}veis o NDVI e a taxa de crescimento e o
m{\'e}todo de k-means, que possibilitou criar zonas mais
homog{\^e}neas, sendo a valida{\c{c}}{\~a}o com dados de campo
fundamental para uma avalia{\c{c}}{\~a}o mais precisa dos
resultados. Concluimos que o desenvolvimento de metodologias,
integrando o uso de dados obtidos por VANTs e sensores orbitais,
permitem identificar caracter{\'{\i}}sticas nas {\'a}reas
agr{\'{\i}}colas que podem ser aplicadas no gerenciamento de
culturas. ABSTRACT: This work aimed to investigate the potential
of imaging sensors on board unmanned aerial vehicles (UAVs) and
orbital sustems to monitor biophysical and biochemical variables
of sugarcane in SE Brazil. For this purpose, estimates of the
height of the canopies and the yield were made, evaluating their
relationship with vegetation indices (NDVI and EVI) in different
spatial resolutions (3 m, 10 m and 30 m) and
temperature/emissivity of the canopy. To estimate canopy height,
RGB images of UAV were acquired during the sugarcane growth period
in the 2019/2020 harvest, which were used to create surface and
ground models using the SfM technique. The estimated height was
obtained by subtraction between the DSM and DTM. The estimated
height in each period allowed to calculate the growth rate of the
sugarcane in this period. Yield and the total production were
estimated by the volumetric method, which used the height
estimated in the last imaged period. In order to calculate the
indices, images from the PlanetScope, Sentinel-2 and Landsat 8
satellites were used, acquired as close as possible to the date of
the UAV flight. For spatial correlation analysis, Pearson's
coefficient was calculated between the estimated heights, the VIs
and temperature and emissivity. A point was selected in order to
evaluate the existence of a temporal correlation between height
and VIs. Temperature and emissivity data were obtained from the
temperature and emissivity products of the ASTER sensor. Finally,
maps of management zones were constructed using the McQuitty and
k-means method, using information on growth rate and vegetation
indices. The height models portrayed the growth phases of
sugarcane, allowing the identification of failures in the
plantation and regions with lower growth, however, the use of GCP
or RTK could minimize errors and improve the quality of the
models. The estimated height did not present a spatial correlation
with the Vis. Neither temperature nor emissivity showed
correlation with height, however data with higher spatial
resolution could improve the results. As for the Management Zones,
all spatial resolutions showed good results. Both methods, as well
as the input variables influenced the results, recommending the
use of two MZs, considering as variables the NDVI and growth rate
and the k-means method, which created more homogeneous zones.
However, the validation with field data is of fundamental
importance for a more accurate evaluation of the results.
Therefore, we conclude that it is possible to develop
methodologies, integrating the use of data from UAVs and orbital
sensors data, which are capable of identifying characteristics of
agricultural areas that can be applied to crop management.",
committee = "Almeida, Cl{\'a}udia Maria de (presidente) and Kux, Hermann
Johann Heinrich (orientador) and Breunig, F{\'a}bio Marcelo
(orientador) and Sanches, Ieda Del'Arco and Pereira, Luiz
Henrique",
englishtitle = "Remote sensing by UAV and orbital in the study of sugarcane:
volumetry and management zones",
language = "pt",
pages = "68",
ibi = "8JMKD3MGP3W34T/458LTA2",
url = "http://urlib.net/ibi/8JMKD3MGP3W34T/458LTA2",
targetfile = "publicacao.pdf",
urlaccessdate = "11 jun. 2024"
}