PolyMorph-2D: An open-source GIS plug-in for morphometric analysis of vector-based 2D polygon features

This paper introduces a free and open-source geographic information system (GIS) plug-in, named PolyMorph2D, for morphometric analysis of vector-based polygon features (PFs) in OpenJUMP. Written in JavaTM programming language, the plug-in allows researchers from various earth and spatial science-related disciplines to compute morphometric parameters of 2D input vector features forming a polygon (i.e., a closed curve) which may represent outer boundaries or contours of various natural and/or man-made entities that differ in size, shape, complexity and drawing scale (e.g., craters, sinkholes, cirques, drainage basins, land parcels, buildings, lakes, ponds, peaks, pits, playas, pockmarks, coral mounds, seamounts, landslides, drumlins, islands, atolls, granular materials, mineral crystals, fossils, etc.). Using this plug-in, a number of basic tasks (e.g., calculations related to location, length, width, perimeter, radius, area, and orientation) can be performed and derived parameters (i.e., shape and size measures) of PFs (e.g., axis ratios, ellipticity, circularity, compactness, dispersion, complexity, elongation, regularity, convexity, concavity, solidity, rectangularity, roundness, and sphericity) are computed and written to input polygon layer's attribute table, through a simple point-and-click interface. The derived parameters calculated by the plug-in are invariant to the PF's location, scale (size), and rotation. The plug-in is also capable of performing aforementioned morphometric calculations on overlapping PFs with or without holes, provided they are topologically correct. The extensive data matrix (consisting of 39 parameters) obtained from this route can be further subjected to a number of multivariate statistical analysis methods to decipher underlying processes and/or environmental factors responsible for formation of these shapes and to classify them into homogeneous subtypes or typologies featuring similar characteristics. (c) 2021 Elsevier B.V. All rights reserved.