Accurate reference data to validate burned area (BA) products are crucial obtaining reliable accuracy metrics for such products. However, the of can be affected by numerous factors; hence, we expect some degree deviation with respect real ground conditions. Since usually produced semi-automatic methods, where human-based image interpretation is an important part process, in this study, analyze ...

The area under the ROC curve (AUC) has been widely used to measure ranking performance for binary classification tasks. AUC only employs the classifier’s scores to rank the test instances; thus, it ignores other valuable information conveyed by the scores, such as sensitivity to small differences in the score values. However, as such differences are inevitable across samples, ignoring them may ...

The first large scale laser scanning project in Sweden for the purpose of forest inventory was started by a regional forestry board in central Sweden. The objective was to compare laser scanning with traditional operational methods for large area forest variable estimations. Laser data were acquired for a 50 km forest area in central Sweden with approximately 1.2 laser measurements per square m...

This paper describes solution for Time Series Land Cover Classification Challenge (TiSeLaC). Using features extracted from satellite images time series (SITS) each pixel corresponding to 30m⇥30m area can be classified to one of general class (urban area, forest, water, etc.). The following approaches implemented and evaluated: classical data mining multiclass prediction, local context embedding...