Premium
Sensitivity of geomorphons to mapping specific landforms from a digital elevation model: A case study of drumlins
Author(s) -
Sărășan Adriana,
Józsa Edina,
Ardelean Adrian C.,
Drăguț Lucian
Publication year - 2019
Publication title -
area
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 82
eISSN - 1475-4762
pISSN - 0004-0894
DOI - 10.1111/area.12451
Subject(s) - drumlin , computer science , sensitivity (control systems) , digital elevation model , identification (biology) , landform , object (grammar) , segmentation , artificial intelligence , data mining , geology , pattern recognition (psychology) , remote sensing , geomorphology , engineering , sea ice , cryosphere , oceanography , botany , electronic engineering , ice stream , biology
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.