[HTML][HTML] Geomorphometry and terrain analysis: Data, methods, platforms and applications

L Xiong, S Li, G Tang, J Strobl - Earth-Science Reviews, 2022 - Elsevier
Terrain is considered one of the most essential natural geographic features and is a key
factor in physical processes. Geomorphometry and terrain analyses have provided a wealth …

Physical geomorphometry for elementary land surface segmentation and digital geomorphological mapping

J Minár, L Drăguţ, IS Evans, R Feciskanin, M Gallay… - Earth-Science …, 2023 - Elsevier
By interpretations related to energy, elementary land surface segmentation can be treated
as a physical problem. Many pieces of such a view found in the literature can be combined …

[HTML][HTML] Towards accurate mapping of loess waterworn gully by integrating google earth imagery and DEM using deep learning

R Chen, Y Zhou, Z Wang, Y Li, F Li, F Yang - International Soil and Water …, 2024 - Elsevier
Accurate mapping of loess waterworn gully (LWG) is essential to further study gully erosion
and geomorphological evolution for the Chinese Loess Plateau (CLP). Due to the vertical …

A reproducible and reusable pipeline for segmentation of geoscientific imagery

D Buscombe, EB Goldstein - Earth and Space Science, 2022 - Wiley Online Library
Segmentation of Earth science imagery is an increasingly common task. Among modern
techniques that use Deep Learning, the UNet architecture has been shown to be a reliable …

Enhancing reproducibility and replicability in remote sensing deep learning research and practice

AE Maxwell, MS Bester, CA Ramezan - Remote Sensing, 2022 - mdpi.com
Many issues can reduce the reproducibility and replicability of deep learning (DL) research
and application in remote sensing, including the complexity and customizability of …

Multiscale object-based classification and feature extraction along Arctic coasts

A Clark, B Moorman, D Whalen, G Vieira - Remote Sensing, 2022 - mdpi.com
Permafrost coasts are experiencing accelerated erosion in response to above average
warming in the Arctic resulting in local, regional, and global consequences. However, Arctic …

Multi-source deep-learning approach for automatic geomorphological mapping: the case of glacial moraines

I Rocamora, D Ienco, M Ferry - Geo-spatial Information Science, 2024 - Taylor & Francis
Landform mapping is the initial step of many geomorphological analyses (eg assessment of
natural hazards and natural resources) and requires vast resources to be applied to wide …

Exploring the Influence of Input Feature Space on CNN‐Based Geomorphic Feature Extraction From Digital Terrain Data

AE Maxwell, WE Odom, CM Shobe… - Earth and Space …, 2023 - Wiley Online Library
Many studies of Earth surface processes and landscape evolution rely on having accurate
and extensive data sets of surficial geologic units and landforms. Automated extraction of …

[HTML][HTML] Rapid estimation of minimum depth-to-bedrock from lidar leveraging deep-learning-derived surficial material maps

W Odom, D Doctor - Applied Computing and Geosciences, 2023 - Elsevier
Previously glaciated landscapes often share similar surficial characteristics, including large
areas of exposed bedrock, blankets of till deposits, and alluvium-floored valleys. These …

Explanation of the influence of geomorphometric variables on the landform classification based on selected areas in Poland

K Dyba - Scientific Reports, 2024 - nature.com
In recent years, automatic image classification methods have significantly progressed,
notably black box algorithms such as machine learning and deep learning. Unfortunately …