This dataset includes a series of R scripts required to carry out some of the practical exercises in the book “Land Use Cover Datasets and Validation Tools”, available in open access.
The scripts have been designed within the context of the R Processing Provider, a plugin that integrates the R processing environment into QGIS. For all the information about how to use these scripts in QGIS, please refer to Chapter 1 of the book referred to above.
The dataset includes 15 different scripts, which can implement the calculation of different metrics in QGIS:
- Change statistics such as absolute change, relative change and annual rate of change (Change_Statistics.rsx)
- Areal and spatial agreement metrics, either overall (Overall Areal Inconsistency.rsx, Overall Spatial Agreement.rsx, Overall Spatial Inconsistency.rsx) or per category (Individual Areal Inconsistency.rsx, Individual Spatial Agreement.rsx)
- The four components of change (gross gains, gross losses, net change and swap) proposed by Pontius Jr. (2004) (LUCCBudget.rsx)
- The intensity analysis proposed by Aldwaik and Pontius (2012) (Intensity_analysis.rsx)
- The Flow matrix proposed by Runfola and Pontius (2013) (Stable_change_flow_matrix.rsx, Flow_matrix_graf.rsx)
- Pearson and Spearman correlations (Correlation.rsx)
- The Receiver Operating Characteristic (ROC) (ROCAnalysis.rsx)
- The Goodness of Fit (GOF) calculated using the MapCurves method proposed by Hargrove et al. (2006) (MapCurves_raster.rsx, MapCurves_vector.rsx)
- The spatial distribution of overall, user and producer’s accuracies, obtained through Geographical Weighted Regression methods (Local accuracy assessment statistics.rsx).
Descriptions of all these methods can be found in different chapters of the aforementioned book.
The dataset also includes a readme file listing all the scripts provided, detailing their authors and the references on which their methods are based.