Four methods were used to quantify short-term (1–2 years) reach-wide streambank erosion rates along three low-order streams in western Virginia: (1) bank height and cross-section (XS) surveys, (2) bank height and top of bank (TOB) surveys, (3) bank height survey and aerial imagery analysis and (4) DEM of Difference (DoD) using UAS LiDAR with channel Geomorphic Change Detection (GCD) software. Results show physical surveys are best for quantifying short-term erosion rates for small, low-order streams in this region.

The paper describes how existing wetland data can be used to train a random forest ML model in Google Earth Engine and generate an accurate map of wetlands for the U.S. State of Arizona. Methods can be easily applied to other parts of the U.S.

In this study, we verified that the longitudinal profile–based cirque classification method is applicable to classify the relatively large cirque and non-cirque dataset in southeastern Tibetan Plateau, including dataset 1 (256 typical cirques and 101 non-cirques) and dataset 2 (883 all-type cirques and 101 non-cirques).

Our study combines geophysical surveys (ground-penetrating radar and electrical resistivity tomography) with surface movement parameters derived from satellite-based differential SAR interferometry. We show that this combination improves the understanding of current geomorphological surface dynamics, as seasonal acceleration and movement angle are sensitive to changes in sub-surface properties.

A method for identifying rangeland soil and water conservation structures, such as earthen berms, within high-resolution lidar data is described and evaluated.

The Martian bedform migration is analysed using satellite and rover observations at Gale, Jezero and Pasteur craters. The results concerning physical and chemical properties indicate short and long-term variability determined by localized aeolian processes. It is essential for understanding the geological history and recent surface dynamics.

To use open-access DEMs for hydrological applications in large-scale plains, it is mandatory to evaluate them using dense and reliable GCP data, apply appropriate statistical methods, and conduct fit-for-use analyses based on well-documented issues.

We study the bank erosion and migration in Brahmaputra river (in Assam). The findings are (1) Barpeta district is severely affected, while Tinsukia is the least affected by bank erosion of Brahmaputra river. (2) Brahmaputra experienced both erosion and deposition along its reach. (3) Maximum erosion and migration rate occurred during the period of 2018–2020. (4) During the study period (2016–2022), the left bank of Zone 1 (8440 ha; −28.76 m/year) and right bank of Zone 3 (7640 ha; −24.38 m/year) undergo higher erosion and migration rate, respectively.

We developed a semi-empirical model correlating coastal geomorphological change to wave energy and water-level variations. The calibrated model estimates topographical change produced by discrete conditions at Holgate, NJ, demonstrating the potential of our approach for the study of coastal processes and the metrics it can provide to inform coastal management.

Rock glaciers can serve as a valuable proxy for mapping debris-covered glaciers, as they are interconnected in a continuum, with debris-covered glaciers potentially transforming into rock glaciers over time. Six machine learning models, combined with multispectral satellite and topographical data, are employed to estimate debris-covered glacier extent in Kinnaur district. Random forest performed best among the models, followed by K-nearest neighbours and Naïve Bayes. The combination of machine learning models and rock glacier inventory data proved to be an alternative approach for remote sensing-based accurate mapping of debris-covered glaciers, with potential applications in broader environmental studies and other regions.

This research revealed interannual area, volume and topography changes of sandbars in different sub-reaches in the lower Mekong River from 2018 to 2022 based on Sentinel-2 imageries. The operation of the Xayaburi Dam and deficient rainfall between 2019 and 2020 have significantly changed erosion and deposition patterns in the lower Mekong River, which were significant global factors contributing to the shrinkage of the sandbars in 2019–2022.

• We develop a hierarchical method to map geomorphic units across valley bottoms.
• The method accommodates user decisions regarding effort invested versus quality and accuracy.
• The method produces 12 preliminary, 20 refined, and four sub-types of geomorphic units.
• The method can be applied to all river types.

A new method for detecting and extracting tidal channels using full-polarised SAR, multispectral imagery and machine learning is proposed. This method can extract the tidal channels at the Yellow River Estuary with a resolution of 3 m and an overall accuracy of 99.6%. The method demonstrates the potential to extract high-resolution tidal channels that can be used to advance the monitoring of changes in estuarine geomorphic processes.

The dominant longitudinal waterflow between terrace steps and converging lateral waterflow along terrace surface control the degradation patterns in the abandoned terraces on the Loess Plateau, and the hydro-geomorphological response is constrained by original slope topography and terrace morphology.

Classification indicators, data resolution, and classification methods (in increasing order of impact) affect the uncertainty of geomorphological classification. We present a guide to choosing the most appropriate method for evaluating the uncertainty of geomorphological classification.

Approximately 50.9% of the Yangtze River source region exhibits evident thermokarst features. Surficial geological factors, specifically geomorphology and slope, are primary factors in shaping thermokarst distribution. In landscapes with thermokarst ponds, both seasonal deformation and long-term subsidence rates intensify, but the amplification diminishes once pond coverage exceeds 5%.

The capture of the proto-Sutlej by the headward eroding Upper Indus River as a consequence of a >1500 m base level change in the Zhada basin exerted an impact on regional growth and tectonics. The gradual expansion of the Leo-Pargil Horst and the ensuing transient uplift-incision regime resulted in the capture of the Zhada paleo-lake ~<5.6 Ma ago. This led to the development of the present Sutlej drainage network with a local base level at the Sutlej and Spiti River confluence.

The accuracy of the DJI Zenmuse L1 solid-state UAV LiDAR system is comparable with other aerial-based methods and statistically indistinguishable from detailed ground-based TLS surveys. However, the sensor is unable to penetrate dense ground-hugging vegetation, resulting in elevation bias in these areas. Ten best practice recommendations are provided to assist users of UAV solid-state LiDAR to produce bare earth DEMs in fluvial environments.

Karst landforms are one of the typical geographical units with a specific physical process on the earth's surface. In this study, we proposed a method considering surface flow for karst landform classification. The proposed approach is validated and applied in two sample karst areas, Fenglin and Fengcong, located in Guilin, China. The results demonstrated that the karst landform units of Fenglin and Fengcong can be effectively classified. The proposed method can be extended to other landform types with complex landforms.

Two machine learning methods, K-Nearest Neighbours (KNN) and Random Forest (RF), were employed to compare the disparities among commonly used open-source digital elevation models (DEMs) in landslide susceptibility mapping. The study revealed significant differences among the DEMs, with the Copernicus DEM 30 m (referred to as COP) emerging as the most recommended option due to its superior rendering performance and stability.