Assembling wall-to-wall maps from distribution models of vegetation types
Peter Horvath, Rune Halvorsen, Trond Simensen, and Anders Bryn are the authors of a new paper in GIScience and Remote Sensing. They compare three methods of assembling wall-to-wall maps using modelled distributions of individual vegetation types.
Material (left), assembly method (centre), and output (right) for making maps from individual models of vegetation types
Distribution modeling methods are used to provide occurrence probability surfaces for modeled targets. However, surfaces provided by distribution modeling need to be transformed into classified wall-to-wall maps of vegetation types to be useful for practical purposes, such as nature management and environmental planning. In the newly published paper (https://doi.org/10.1080/15481603.2021.1996313) the authors evaluated the performance of three methods for assembling predictions from individual distribution models into nation-wide, vegetation-cover maps.
From individual predictions to wall-to-wall vegetation cover
The authors used grid-cell based probability surfaces from distribution models of 31 vegetation types to test the three assembly methods. The first, a probability-based method, selected for each grid cell the vegetation type with the highest predicted probability of occurrence in that cell. The second, a performance-based method, assigned the vegetation types, ordered from high to low model performance, to a fraction of the grid cells given by the vegetation type’s prevalence in the study area. The third, a prevalence-based method, differed from the performance-based method by assigning vegetation types in the order from low to high prevalence. All methods were evaluated by use of reference data collected in the field.
The probability-based method had the lowest total disagreement with, and proportional dissimilarity from, the reference datasets, but the differences between the three methods were small. The three assembly methods differed strongly with respect to the distribution of the total disagreement on its quantity and allocation components: the cell-by-cell assignment method strongly favored allocation disagreement and the type-by-type methods strongly favored quantity disagreement. The probability-based method best reproduced the general pattern of variation across the study area, but at the cost of many rare vegetation types, which were left out of the assembled map. By contrast, the prevalence-based and performance-based methods represented vegetation types in accordance with nationwide area statistics.
The results show that maps of vegetation types with wall-to-wall coverage can be assembled from individual distribution models with a quality acceptable for indicative purposes, but all the three tested methods currently also have shortcomings. The results also indicate specific points in the methodology for map assembly that may be improved.
The full article “A comparison of three ways to assemble wall-to-wall maps from distribution models of vegetation types” is published open-access here: https://www.tandfonline.com/doi/full/10.1080/15481603.2021.1996313