AERONAVE REMOTAMENTE PILOTADA DE BAIXO CUSTO NO ESTUDO DE PLANTAS INVASORAS EM ÁREAS DE CERRADO
DOI:
10.31413/nativa.v8i1.8433Resumo
O objetivo dessa pesquisa é analisar se o método CHIS (Canopy Height Invasive Species) representa uma rotina de classificação assertiva na identificação de espécies invasoras a partir de imagens RGB em área de Cerrado com evidência de perturbação. A metodologia empregada foi a produção dos modelos de elevação MDS (Modelo Digital de Superfície) e MDT (Modelo Digital do Terreno) a partir das imagens coletadas em campo com drone e posteriormente processadas no software PhotoScan. A produção do CHIS foi a partir da subtração dos modelos MDS e MDT. Para aferir a precisão do modelo CHIS foram gerados dois modelos convencionais para comparação: classificação não supervisionada K-means e índice de vegetação NGRDI (Normalized Red-Green Difference Index). A comparação entre os modelos se deu em duas áreas amostrais escolhidas de forma não aleatória. Ao final foi aplicado teste de acurácia, correlação e Cohen’s Kappa. Os resultados demonstram que o modelo CHIS obteve os melhores resultados na identificação de espécies invasoras quando comparado com os modelos K-means e NGRDI. Os testes de acurácia para o modelo CHIS na área amostral 1 e 2 foi de 0,973 e 0,9 respectivamente; K-means 0,209 e 0,6; NGRDI 0,795 e 0,518. O modelo CHIS demonstrou ser promissor na identificação de espécies invasoras em áreas perturbadas quando comparado com modelos convencionalmente usados.
Palavras-chave: ARP; gestão ambiental; sensoriamento remoto; CHIS.
REMOTELY PILOTED AIRCRAFT (DRONE) OF LOW COST IN THE INVASIVE SPECIES STUDY IN CERRADO AREAS
ABSTRACT:
The objective of this research is to analyze if the CHIS (Canopy Height Invasive Species) method represents an assertive classification routine in the identification of invasive species from RGB images in Cerrado area with evidence of disturbance. The methodology used was the production of the DSM (Digital Surface Model) and DTM (Digital Terrain Model) elevation models from the images collected in the drone field and later processed in the PhotoScan software. The production of the CHIS was based on the subtraction of the DSM and DTM models. To verify the accuracy of the CHIS model two conventional models were generated for comparison: unsupervised K-means classification and NGRDI (Normalized Red-Green Difference Index) vegetation index. The comparison between the models occurred in two sample areas chosen in a non-random manner. At the end, it was applied test of accuracy, correlation and Cohen's Kappa. The results demonstrate that the CHIS model obtained the best results in the identification of invasive species when compared with the K-means and NGRDI models. The accuracy tests for the CHIS 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 CHIS model has been shown to be promising in the identification of invasive species in disturbed areas when compared to conventionally used models.
Keywords: RPA; environmental management; remote sensing; CHIS.
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