Remote Sensing to Detect Nests of the Leaf-Cutting Ant Atta sexdens (Hymenoptera: Formicidae) in Teak Plantations

Abstract

Leaf-cutting ants of the genus Atta are an important insect pest in forest plantations in many countries of South America. The objective of this work was to evaluate the potential for using Landsat-8 images, with medium spatial resolution and distributed free of charge, to detect leaf-cutting ant nests in Tectona grandis plantations in Brazil, using partial least squares discriminant analysis (PLS-DA). The regression model adjusted by PLS-DA selected three principal components with a cross-validation error of 0.275 to map and predict the presence of leaf-cutting ant nests in these plantations. The most important bands and vegetation indices were selected using the main variables in the projection (VIP) and predicted pixels with the presence or absence of leaf-cutting ant nests with an accuracy of 72.3% on an independent validation data set. The study indicates that Landsat-8 OLI images have the potential to detect and map leaf-cutting ant nests in T. grandis plantations.

Estimation of soil salt content by combining UAV-borne multispectral sensor and machine learning algorithms

“…Variable importance in projection (VIP) scores evaluates the importance of each variable in the projection used in a PLS model. Gray relational analysis (GRA) identify the primary and secondary relations among variables through the calculation and comparison of correlation sequence, and they both have been proved to be effective methods for variable selection (Santos et al, 2019;Wang et al, 2018a). Successive projections algorithm (SPA) is a variable selection method widely used in food and chemical engineering (Diniz et al, 2015;Ghasemi-Varnamkhasti et al, 2012;Wu et al, 2009).…”

Herbivory by Atta vollenweideri: Reviewing the significance of grass-cutting ants as a pest of livestock

“…These should include the concept that a species is a pest in a specific production system at a given population level, i.e., the critical economic injury level, as discussed in this study, for livestock production in rangelands. It is now time to apply the methods already developed for estimating the population density of Atta nests and using them as a decision criterion in rational pest management practices ( 1 , 34 , 35 ).…”

“…Only the quadrants falling entirely inside the areas were considered, making a total of 15,624 ha, in which nest density was estimated. Aerial localization of Atta nests has been used previously with both aerial photography ( 33 , 34 ) and satellite imagery ( 35 ); the first studies of this kind were, in fact, carried out with A. vollenweideri in Paraguay ( 7 , 36 ).…”