Raining, validation, and testing datasets at a ratio of five:1:four. The distinct pixel quantity for each category is shown in Table 3.Remote Sens. 2021,Remote Sens. 2021, 13, x FOR PEER Assessment 13,12 ofFigure 10. Coaching, validation, and testing samples of each tree category with all the correct labels.Figure 10. Education, validation, and testing samples of every single tree category with all the true labels. Table 3. Pixels of coaching, validation, and testing for each tree category. Table 3. Pixels of coaching, validation, and testing for every tree category. Sample’s Pixel Quantity Categories Sample’s Pixel NumberTotal Education Validation Testing CategoriesEarly infected pinepine trees Late infected trees Late infected pine trees Broad-leaved trees Total Broad-leaved trees TotalEarly infected pine trees163,628 163,628 242,107 242,107 one hundred,163 505,898 100,Training32,726 48,421 20,033 101,505,Validation 130,902 32,726 193,685 48,421 80,130 20,033 404,717 101,Testing 327,256 130,902 484,213 193,685 200,326 1,011,795 80,130 404,Total 327,256 484,213 200,326 1,011,The classification Streptonigrin In Vivo accuracy was assessed by calculating the producer accuracy (PA), The general accuracy (OA), as well as the Kappa calculating the producer average accuracy (AA),classification accuracy was assessed by coefficient worth [46]. Theaccuracy average accuracy (AA), general accuracy (OA), and the Kappa coefficient value [46 formulas are as follows: formulas are as follows: PA = right classification pixel variety of each and every class/total pixel number of each class (2) PA = correct classification pixel number of every single class/total pixel variety of every single class Kappa = (OA – eAccuracy)/(1 – eAccuracy) (three) Kappa = (OA – eAccuracy)/(1 – eAccuracy) k eAccuracy = ( i=1kV p Vm)/S2 (4) eAccuracy = ( i=1 Vp Vm)/S2 exactly where OA is overall accuracy, k is the number of categories, Vp is the predicted value, Vm where OA is S would be the sample number. will be the measured value, and general accuracy, k will be the number of categories, Vp may be the predicted valu would be the measured value, and S will be the sample quantity. three. Results three. Benefits The reflectance curves of broad-leaved trees, early infected pine trees, and late infectedThe reflectance curves in Figure 11. Of trees, early infected and trees, pine trees within 400000 nm are depicted of broad-leaved the broad-leaved treespine two and la fected pine trees inside 400000 nm are depicted was most 11. Of the broad-leaved stages of infected pines, the distinction inside the spectral reflectance in Figure apparent in the and two stages of infected pines, the difference in the spectral reflectance was most green peak (52080 nm), red edge (66080 nm), and NIR (72000 nm). Moreover, the ous in incorrectly classified early infected pine trees into broad-leaved (72000 nm) models we employed nevertheless the green peak (52080 nm), red edge (66080 nm), and NIR trees thermore, early infected utilized nevertheless incorrectly classified early infected pine tree since the Combretastatin A-1 Protocol spectrum with the models wepine trees is related to that of broad-leaved trees (Figure 11). broad-leaved trees since the spectrum of early infected pine trees is comparable to t broad-leaved trees (Figure 11).Remote Sens. 2021, 13, x FOR PEER REVIEW14 ofRemote Sens. 2021, 13, x FOR PEER Overview Remote Sens. 2021, 13,14 of 23 13 ofFigure 11. The reflectance curve of broad-leaved trees, early infected pine trees, and late infected pine trees.Figure 11. The reflectance curve of broad-leaved trees, early infected pine trees, and late infected pine trees. Figure 11. The reflectan.