Ceborne Thermal Emission and Reflection Radiometer (ASTER), Quickbird, ERS-1 and -2, and ALOS-2 were also among the sensors which have been utilized in combination with other sensors. Nonetheless, Quickbird, ASTER, GeoEye, and ERS-1 and -2 were the least frequent sensors with five or much less uses.Remote Sens. 2021, 13,21 ofFigure 16. Frequency of unique sensors applied in RS-based wetland classification studies in Canada. Blue and red bards indicate if a single or multi-source data are utilised.4.4. Degree of Classification Accuracy For any complete investigation in the RS-based Canadian wetland studies, the reported overall accuracies had been assessed and compared with several parameters, including the year of publication, the extent on the study location, as well as the number of Vc-seco-DUBA Protocol classes deemed within the classification approach (see Figure 17). Figure 17a presents the histogram from the overall classification accuracies reported in 128 papers. Note that a wide selection of research (39 papers) didn’t report the general accuracy of their classification solutions (black column in Figure 17a). As outlined by Figure 17a, pretty much 80 (46 papers) of the studies have an general accuracy involving 84 and 93 ; though only 33 papers have an overall accuracy of much less than 84 (between 62 and 83 ). Primarily based on Figure 17b, there is not a clear partnership amongst the overall classification accuracy and also the year of publication. Two articles that were published in 1976995 have close all round accuracy to one another along with the medium general accuracy of 86 . Two articles that have been published in 1996000 have achieved various accuracies. The medium general accuracy of these articles is 71 . In one more time-interval, there is a higher quantity of publications which have a wide selection of all round accuracies among 63 and 96 . Based on Figure 17c, wetland classification procedures applied for the provincial scales possess the highest median all round accuracies, followed by incredibly modest and regional study areas. Alternatively, the papers on national scales possess the lowest median general accuracies. Based on Figure 17d, greater than 90 of the investigated articles employed a number of classes (in between two and six). In these papers, the general accuracies vary among 62 and 96 . Having said that, the median all round accuracies of those papers are 87 for 1 classes and 86 for four classes. Inside the case of 7 classes, the total variety of papers decreases to four papers. The median all round accuracy of these four papers is 89 . Moreover, those articles that deemed aRemote Sens. 2021, 13,22 ofgreater variety of classes have higher median overall accuracies. We also discovered two papers that regarded 108 classes for classifying wetlands and achieved the median overall accuracies of 94 . As noticed, a larger number of classes appear to be more precise for the wetland classification process. We count on larger accuracies for a reduced quantity of classes. Thus, due to the considerable discrepancy within the variety of papers, it is actually not possible to supply a solid conclusion regarding the partnership between the all round accuracy of classification system and also the variety of classes.Figure 17. All round accuracies reported in in RS-based wetland classification studies in Risperidone-d4 site Canada based on (a) the amount of papers, (b) the year of publications, (c) the extent of study location, and (d) the amount of classes deemed in the classification approach.5. Conclusions This critique paper demonstrated the trends of RS-based wetlands research in Canada by investigating 300 articles published fr.