Sensitivity of geomorphons to mapping specific landforms from a digital elevation model: A case study of drumlins

Abstract

The current paper explores the suitability of geomorphons for the automatic extraction of drumlins. To calibrate the geomorphons to the size of drumlins, it is necessary to optimally define the maximum scale of mapping, i.e., the lookup distance parameter (L). Therefore, based on the concept of topographic grain, we introduce a new automated approach for identifying the specific threshold of L (13 cells) and assessing its potential to generate consistent and accurate results in drumlin extraction. Following an object-based image analysis (OBIA) routine, a new method for mapping and detecting drumlins is proposed. The aggregated geomorphons map was employed both as a thematic layer for image segmentation and as a first criterion for the identification of drumlin candidates. The classification results were quantitatively compared with the reference data in order to evaluate the performance of the drumlin classification, by using five additional L values (3, 50, 100, 200, 400 cells). The evaluation revealed that the highest drumlin detection rate of 91.7% was reached at an L value of 13 cells (65 m), while the lowest value of 84.3% was reached at the default value (L-3 cells). We conclude that the use of the automated procedure for the detection of the L value is useful in achieving a rapid computation of geomorphons, which leads to consistent and accurate results in drumlin extraction. A comparison with previous OBIA methods suggests that the proposed approach produced the most accurate extraction of drumlins. K E Y W O R D S digital elevation model, Eberfinger drumlin field, landform mapping, object-based image analysis, sensitivity analysis, topographic grain

Comparison of digital elevation models through the analysis of geomorphic surface remnants in the Desatoya Mountains, Nevada

“…Histograms and dot plot diagrams were also generated using RStudio v1.2.5033. For another quantitative assessment of the feature extraction performance, the confusion matrix (Sărășan et al., 2018; Stehman, 1997; Torres et al., 2020) approach was used, where all 244 digitized peaks served as reference.…”

“…Researchers have numerous opportunities to evaluate and measure the accuracy of digital elevation models (DEMs), knowing that there is a broad spectrum of information and methodology to dissect the issue. DEMs are frequently used in disciplines like geology (Van Dijk, Bello, Toscano, Bersani, & Nardon, 2000), geomorphology (Amatulli, McInerney, Sethi, Strobl, & Domisch, 2020; Etzelmuller, 2000; Mahalingam & Olsen, 2016; Sărășan, Józsa, Ardelean, & Drǎguţ, 2018), hydrology (Boulton & Stokes, 2018), ecology (Kellndorfer et al., 2004), agriculture (Pilesjö, Persson, & Harrie, 2006), and so on. Employing space and airborne remote sensing images are still a widespread and cost‐efficient technique to collect elevation information.…”

Evaluating an Automated Object-Oriented Method to Delineate Drumlins From Both Terrestrial and Submarine Digital Elevation Models

“…(2016) used automated method to extract drumlins from high-resolution Light Detection and Ranging (LiDAR) data. Sărășan et al (2019) used geomorphons threshold in their automated technique. Yu et al (2015) used Curvature Based Relief Separation (CBRS) technique for automated drumlin shape and volume estimation using high resolution LiDAR imagery.…”

O Uso De Métodos De Mapeamento Automático De Relevo Para Análise De Formas Glaciais

“…Libohova et al (2016) utilizaram a classifi cação relevo por geomorphons para interpretação e classifi cação do solo para paisagens a jusante de morainas terminais no Norte de Indiana (EUA). Sarasan et al (2018) O objetivo deste artigo é avaliar a potencialidade da metodologia de geomorphons (JASIEWICZ e STĘPIŃSKI, 2013) para a identifi cação de tipos de formas de relevo em ambientes glaciais de montanha. A análise foi aplicada em uma área da Cordilheira Branca, Peru.…”