Sensoriameno remoto com sensores de aeronaves remotamente pilotadas para aplicações de agricultura de precisão e gestão ambiental
Data
2019-09-13
Autores
Pessi, Dhonatan Diego
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Universidade Federal de Mato Grosso
Resumo
The objective of this research was to analyze whether the measurement of invasive species
height (CHIS) through images captured by remotely piloted aircraft (drone) could classify
with good assertiveness the areas with presence of invasive plants differenting from other
areas with vegetation remnant of cerrado. The text was divided in two chapters, the first
chapter highlights a first test of CHIS+GPS/GLONASS model, comparing to two other
common techniques used in the classification of invasive species: the unsupervised
classification k-means and vegetation index NGRDI. MDS and MDT elevation models were
produced from the drone images collected in field and posteriorly then processed in
PhotoScan software. The CHIS+GPS/GLONASS production was through the subtracting the
MDS and MDT models. The comparison between the models occurred in two sample áreas.
Some nonparametric statistical tests were used, such as: precision test, general error rate,
specificity, sensitivity, Spearman correlation and Cohen's Kappa. In the second chapter, to
measure the precision of CHIS+GPS/GLONASS model, the CHIS+RTK model was
generated as the observed variable. The comparison between the models took place in the two
sampled areas used in the first chapter, by which they were visually compared from graphs
and statistical tests. The statistical tests used were: Spearman correlation coefficients (SCC),
mean square root canopy height error (RMSEz), mean absolute canopy height error (MAEz)
and Wilcoxon test. The results of the first chapter demonstrate that CHIS+GPS/GLONASS
model has the best results in identifying invasive species when compared to the k-means and
NGRDI models. Precision tests for the CHIS+GPS/GLONASS model in sample area 1 and 2
were 0.973 and 0.9, respectively; k-means 0.209 and 0.6; NGRDI 0.795 and 0.518. The
results of the second chapter demonstrate that CHIS+GPS/GLONASS model presents faults
in the identification of invasive species when compared to the CHIS+RTK model, being less
accurate in the classification of invasive species selection heights. Spearman's correlation test
for sample area 1 was 0.56 and 0.55 for sample area 2. RMSEz for sample area 1 was 0.17 cm
and 0.12 cm for MAEz. A sample area 2 or RMSEz was 0.24 cm and 0.19 cm for the MAEz.
The Wilcoxon test was significant for areas such as sample areas. The CHIS model proved to
be a promising technique for identification of invasive species. It was exhibited with other
accessory models, and its accuracy was considered good, since the largest difference in height
errors was 0.24 cm and could be It is used in research that does not require great precision, as
examples of research that has as object research, arboreal vegetation, where small differences
in accuracy are not large.
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PESSI, Dhonatan Diego. Sensoriameno remoto com sensores de aeronaves remotamente pilotadas para aplicações de agricultura de precisão e gestão ambiental. 2019. 120 f. Dissertação (Mestrado em Gestão e Tecnologia Ambiental) - Universidade Federal de Mato Grosso, Instituto de Ciências Agrárias e Tecnológicas, Rondonópolis, 2019.