Evaluation of the Geomorphon Approach for Extracting Troughs in Polygonal Patterned Ground Across Different Permafrost Environments

As the climate continues to warm, the thawing of ice-rich permafrost leads to changes in the polygonal patterned ground (PPG) landscape, exhibiting an array of spatial heterogeneity in trough patterns, governing permafrost stability and hydrological and ecosystem dynamics. Developing accurate methods for detecting trough areas will allow us to better understand where the degradation of PPG occurs. The Geomorphon approach is proven to be a computationally efficient method that utilizes digital elevation models (DEMs) for terrain classification across multiple scales. In this study, we firstly evaluate the appliance of the Geomorphon algorithm in trough mapping in Prudhoe Bay (PB) in Alaska and the Wudaoliang region (WDL) on the central Qinghai–Tibet Plateau. We used the optimized DEM resolution, flatness threshold (t), and search radius (L) as input parameters for Geomorphon. The accuracy of trough recognition was evaluated against that of hand-digitized troughs and field measurements, using the mean intersection over union (mIOU) and the F1 Score. By setting a classification threshold, the troughs were detected where the Geomorphon values were larger than 6. The results show that (i) the lowest t value (0°) captured the microtopograhy of the troughs, while the larger L values paired with a DEM resolution of 50 cm diminished the impact of minor noise, improving the accuracy of trough detection; (ii) the optimized Geomorphon model produced trough maps with a high accuracy, achieving mIOU and F1 Scores of 0.89 and 0.90 in PB and 0.84 and 0.87 in WDL, respectively; and (iii) compared with the polygonal boundaries, the trough maps can derive the heterogeneous features to quantify the degradation of PPG. By comparing with the traditional terrain indices for trough classification, Geomorphon provides a direct classification of troughs, thus advancing the scientific reproducibility of comparisons in PB and WDL. This work provides a valuable method that may propel future pan-Arctic studies of trough mapping.

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Publication Details

Journal
Remote Sensing
Published
2025-03-16
DOI
https://doi.org/10.3390/rs17061040
Primary Topic
Climate change and permafrost
Type
article
Field-Weighted Citation Impact
0.00

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article

Evaluation of the Geomorphon Approach for Extracting Troughs in Polygonal Patterned Ground Across Different Permafrost Environments

Tonghua Wu, Peiqing Lou, Xin Ma, Xiaofan Zhu et al.
Remote Sensing
Climate change and permafrost
article

Evaluation of the Geomorphon Approach for Extracting Troughs in Polygonal Patterned Ground Across Different Permafrost Environments

Tonghua Wu, Peiqing Lou, Xin Ma, Xiaofan Zhu, Dong Wang, Jie Chen, Xiaodong Wu, Jianzong Shi, Amin Wen
article en

Abstract

As the climate continues to warm, the thawing of ice-rich permafrost leads to changes in the polygonal patterned ground (PPG) landscape, exhibiting an array of spatial heterogeneity in trough patterns, governing permafrost stability and hydrological and ecosystem dynamics. Developing accurate methods for detecting trough areas will allow us to better understand where the degradation of PPG occurs. The Geomorphon approach is proven to be a computationally efficient method that utilizes digital elevation models (DEMs) for terrain classification across multiple scales. In this study, we firstly evaluate the appliance of the Geomorphon algorithm in trough mapping in Prudhoe Bay (PB) in Alaska and the Wudaoliang region (WDL) on the central Qinghai–Tibet Plateau. We used the optimized DEM resolution, flatness threshold (t), and search radius (L) as input parameters for Geomorphon. The accuracy of trough recognition was evaluated against that of hand-digitized troughs and field measurements, using the mean intersection over union (mIOU) and the F1 Score. By setting a classification threshold, the troughs were detected where the Geomorphon values were larger than 6. The results show that (i) the lowest t value (0°) captured the microtopograhy of the troughs, while the larger L values paired with a DEM resolution of 50 cm diminished the impact of minor noise, improving the accuracy of trough detection; (ii) the optimized Geomorphon model produced trough maps with a high accuracy, achieving mIOU and F1 Scores of 0.89 and 0.90 in PB and 0.84 and 0.87 in WDL, respectively; and (iii) compared with the polygonal boundaries, the trough maps can derive the heterogeneous features to quantify the degradation of PPG. By comparing with the traditional terrain indices for trough classification, Geomorphon provides a direct classification of troughs, thus advancing the scientific reproducibility of comparisons in PB and WDL. This work provides a valuable method that may propel future pan-Arctic studies of trough mapping.

Remote SensingVol. 17(6)
Chinese Academy of Sciences (CN), Northwest Institute of Eco-Environment and Resources (CN), University of Chinese Academy of Sciences (CN)
Science and Technology Program of Gansu Province
Openalex Percentile: Top 90%
Climate change and permafrost
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