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Benthic species assemblages are groups of species that co-occur on the seafloor. Linking assemblages to physical environmental features allows for understanding and predicting their spatial distribution. Species identity and abundance are commonly quantified using a taxonomic approach to assess benthic diversity, yet functional traits that describe the behavior, life history, and morphology of a species may be equally or more important. Here, we investigate the biodiversity of five benthic species assemblages in relation to their habitat and environmental conditions in an Ecologically and Biologically Significant Area (EBSA) along Canada's east coast, using both a taxonomic approach and biological traits analysis. Random Forest regression was applied to map spatial patterns of functional and taxonomic diversity metrics, including richness, Shannon index, and Rao's quadratic entropy. We evaluate discrepancies between related taxonomic and trait measures, and the community-weighted mean of trait data was calculated to characterize each assemblage. Taxonomic and functional richness - representing the number of species and the species community volume in the trait space, respectively - showed similar spatial patterns. However, when considering diversity, which also accounts for the relative abundance and differences among species or traits, these patterns diverged. Taxonomically different assemblages exhibited similar trait compositions for two assemblages, indicating potential trait equivalencies, while one assemblage exhibited traits potentially indicating sensitivity to human activity. The taxonomic and functional metrics of richness and diversity were low close to the coast, which could be indicative of disturbance. Consideration of functional metrics can support spatial planning and prioritization for management and conservation efforts by assessing the sensitivity of traits to different stressors. [ABSTRACT FROM AUTHOR]

Introduction The amount of sediment production, the manner and time of sedimentation, the size and composition of sediment grains, and transport among the waterways network are important features of the sedimentation regime of Watersheds; Because changes in each of these factors cause changes in Watershed performance. Therefore, sediment production is a reflection of the importance and amount of erosion processes and sediment sources in the upstream parts of the Watershed and how sediment is transported and deposited from the moment of movement of erosion materials from the point of separation to the exit of it. Sediment connectivity indicators indicate the spatial changes of connectivity patterns in different parts of the Watershed and provide a suitable estimate of the contribution of sediment sources and sediment transport routes. For this purpose, investigating the spatial pattern of sediment flux at the Watershed scale is of particular importance in developing comprehensive management plans and measures to control erosion and sedimentation. Although various indicators and models have been developed in this field, their performance has not been evaluated based on observational data and statistical methods. This research aims to analyze the sediment flux pattern of the Neyriz Watershed located in the east of Fars Province, based on sediment connectivity and sediment transfer capacity indicators, and compare their performance based on field sediment evidence. Materials and Methods At first, a digital model of the ground elevation of the Neyriz Watershed with a spatial resolution of 12.5 m was prepared and its drainage network was extracted. Then, the sediment connectivity index was calculated by considering the upstream and downstream features of the Watershed and by considering the roughness factor as the sediment movement resistance factor, and the sediment connectivity map of the Watershed was made. Then, the sediment transport capacity index map was also prepared based on the concept of topography and using the digital model layer of land height. For this purpose, the sediment transport capacity index was calculated for each pixel of Neyriz Watershed in SAGA-GIS software, and a sediment transport map was prepared. Based on field visits to different parts of the Watershed, 30 positions that had evidence of sediment transfer were recorded as observation points of the sediment transfer event. Also, 30 other positions that did not have signs and evidence of sediment transfer were added to the validation database as observation points of no sediment transfer event. The corresponding values of each index were also extracted in the geographic information system and based on the available information, using evaluation methods based on the error matrix including true skill statistic (TSS), efficiency (E), and F score (F-score), the validation of the mentioned indicators was done quantitatively. Results and Discussion The value of the sediment connectivity index of the Neyriz Watershed in Fars Province varied from -7.24 to 2.43 and its median value was -4.36. The spatial pattern of the sediment connectivity index in this Watershed is such that the middle and western parts have a low amount and the northern, southern, and eastern parts have more amounts. In this research, the drainage network of the Watershed was introduced as the target of receiving the sediment; Parts of the slopes of the Watershed level, which had the conditions of sediment production and transfer were connected to the drainage network in terms of the transfer path, have shown a higher value of connectivity index. This index provides valuable information for land management by considering the upstream characteristics of each point as well as the characteristics of the transfer path to the sediment-receiving target. The value of the sediment transfer capacity index varied from 7.2 to 23.16 and the average value was 10.19. The value of this index is high in the marginal parts of the Watershed where there are sloping lands, and the middle parts of the Watershed have a small value. Based on the findings, the index of sediment connectivity with the true skill statistic (TSS) of 0.833, the efficiency value (E) of 0.916, and the F score of 0.915 is a better performance than the sediment transport capacity index (TSS= 0.633, E=0.816, F-score=0.825). In addition, based on the values of the false positive component in the error matrix, the sediment transport capacity index predicts high sediment flux potential in many situations; While in the field observations, it was not true. Conclusion Based on statistical evaluation criteria, the sediment connectivity index has been able to better describe the state of sediment flux and is more consistent with field realities. So that the sediment connectivity index, in addition to considering the characteristics of the upstream area of each point of the Watershed, is possible to consider the path of the sediment particle to the target location of the receiver (such as the nearest branch of the network drainage) has made it possible. Based on the findings obtained in this research, although the sediment transfer capacity index in some parts of the Neyriz Watershed of Fars Province was in line with the sediment connectivity index; However, due to the energy-based nature of the flow, this index only considers the local conditions of the points and ignores the features of the upstream area as well as the process of transporting sediment particles to the downstream. Therefore, it is suggested to use the sediment connectivity index in the erosion and sedimentation studies of Watersheds. Because when information about the amount of sediment production is not available; the Sediment connectivity index can provide useful information about the sediment transfer process in the Watershed. [ABSTRACT FROM AUTHOR]

At least 10 global digital elevation models (DEMs) at one-arc-second resolution now cover Earth. Comparing derived grids, like slope or curvature, preserves surface spatial relationships, and can be more important than just elevation values. Such comparisons provide more nuanced DEM rankings than just elevation root mean square error (RMSE) for a small number of points. We present three new comparison categories: fraction of unexplained variance (FUV) for grids with continuous floating point values; accuracy metrics for integer code raster classifications; and comparison of stream channel vector networks. We compare six global DEMs that are digital surface models (DSMs), and four edited versions that use machine learning/artificial intelligence techniques to create a bare-earth digital terrain model (DTM) for different elevation ranges: full Earth elevations, under 120 m, under 80 m, and under 10 m. We find edited DTMs improve on elevation values, but because they do not incorporate other metrics in their training they do not improve overall on the source Copernicus DSM. We also rank 17 common geomorphic-derived grids for sensitivity to DEM quality, and document how landscape characteristics, especially slope, affect the results. None of the DEMs perform well in areas with low average slope compared to reference DTMs aggregated from 1 m airborne lidar data. This indicates that accurate work in low-relief areas grappling with global climate change should use airborne lidar or very high resolution image-derived DTMs. [ABSTRACT FROM AUTHOR]

Numerically interpolated contour lines (NICL) developed from a high-resolution, accurate digital elevation model (DEM) can be considered the most accurate contour baseline available from surveyed data. Displays of this baseline, however, can exhibit an undesirable angularity and clutter that impedes human understanding of the data and defies the universal appeal of a smooth curve. To achieve smooth, readable lines, the prevailing wisdom today is to either 1) smooth the underlying surface model before creating the lines or 2) use mathematical methods adapted from computer-aided design (CAD) to smooth the lines in x and y. However, these smoothing methods can result in an inaccurate rendition of the original data that undermines their subsequent use in analysis and modeling applications. Upon close inspection, lines generated from such methods can depart from the baseline by more than a definable and acceptable distance in x and y, particularly noticeable in important areas of slope change. Here, we argue that generalized contours have a geometric accuracy requirement that must be observed. We present a novel alternative to the prevailing methods that 1) presents an incremental smoothing method that is a logical complement to Douglas-Poiker thinning; 2) introduces the use of slope as a means of controlling the degree of smoothing locally; 3) produces novel, operational definitions of tests for smoothness and accuracy as well as for line symmetry; and 4) introduces the notion of a topological TIN as a new type of terrain model and a medium for edits of contours. The method only manipulates the baseline contours in x and y. By using only simple proportions of sides and self-similar geometry to smooth the original lines, we at the same time impose computable, dynamic constraints on the smoothing. This combination ensures the accuracy and acceptability of the final contours at scales appropriate for working GIS displays. The result is a Locally Adjusted Curve Approximation (LACA) technique for contour line smoothing.

Local morphometric variables (LMVs) are frequently found as weaker predictors than other environmental covariates in digital soil mapping. This study tested and evaluated the performance of a hybrid approach combining gradient boosted regression trees (GBRT) and regularized regression (RR) algorithms in predicting soil textural fractions using a set of LMVs in Khuzestan province, Iran. Here five LMVs (slope gradient, slope aspect, horizontal curvature, vertical curvature, and contour geodesic torsion) were derived from a spheroidal equal-angular DEM as original predictors. The results demonstrated that the hybrid approach improved prediction accuracy for sand, clay, and silt contents by an average of 56% compared to the GBRT models. The importance analysis revealed the significant contribution of tree-based variables obtained from decomposing GBRT models in predicting soil textural fractions. This approach could be recommended for digital soil mapping, particularly in situations of limited environmental covariates or geomorphometric techniques that cannot be easily applied. [ABSTRACT FROM AUTHOR]

Benthic species assemblages are groups of species that co-occur on the seafloor. Linking assemblages to physical environmental features allows for understanding and predicting their spatial distribution. Species identity and abundance are commonly quantified using a taxonomic approach to assess benthic diversity, yet functional traits that describe the behavior, life history, and morphology of a species may be equally or more important. Here, we investigate the biodiversity of five benthic species assemblages in relation to their habitat and environmental conditions in an Ecologically and Biologically Significant Area (EBSA) along Canada’s east coast, using both a taxonomic approach and biological traits analysis. Random Forest regression was applied to map spatial patterns of functional and taxonomic diversity metrics, including richness, Shannon index, and Rao’s quadratic entropy. We evaluate discrepancies between related taxonomic and trait measures, and the community-weighted mean of trait data was calculated to characterize each assemblage. Taxonomic and functional richness – representing the number of species and the species community volume in the trait space, respectively – showed similar spatial patterns. However, when considering diversity, which also accounts for the relative abundance and differences among species or traits, these patterns diverged. Taxonomically different assemblages exhibited similar trait compositions for two assemblages, indicating potential trait equivalencies, while one assemblage exhibited traits potentially indicating sensitivity to human activity. The taxonomic and functional metrics of richness and diversity were low close to the coast, which could be indicative of disturbance. Consideration of functional metrics can support spatial planning and prioritization for management and conservation efforts by assessing the sensitivity of traits to different stressors.

In recent years, some topographic metrics (Gilbert metrics) have been proposed to investigate the degree of mobility and stability of drainage divides, through erosion rates between basins that share the same divide. Here, we investigated the mobility dynamics in the main divide of the Ibicuí and Jacuí river basins in southern Brazil, considering several indicators of erosive processes in this region. The mobility and stability of the Ibicuí-Jacuí interfluve were assessed based on the χ and Gilbert (elevation, gradient, and relative relief) metrics extracted from the Copernicus DEM (COP-30) and field data, including aerial images. Our results showed that mobility occurs throughout the studied interfluve. In particular, the central region showed a high level of drainage divide mobility, likely due to its geographical location in the Central Depression geomorphological unit, which is dominated by low-resistant sedimentary rocks and relatively low elevations. The results also indicated that the main direction of the interfluve’s mobility is from east to west, highlighting that sub-basins from the Jacuí basin are potentially more erosive and, thus, are migrating toward the Ibicuí basin. Once connected, these sub-basins may alter the regional fluvial dynamics of this important region in southern Brazil.

ABSTRACTSoil erosion, a major factor contributing to land degradation, poses significant environmental challenges across sub-Saharan Africa, including Ethiopia. This study identifies erosion-prone sub-watersheds in southern Ethiopia's middle Omo-Gibe River basin using digital elevation model data, analyzed using a geomorphometric and statistically weighted sum priority approach in a Geographic Information System environment. Additionally, hypsometric analysis, lithology, land use/cover analysis, and field observations were integrated to enhance methodological reliability in assessing soil erosion patterns and subsequent land degradation in the basin. Results highlight sub-watersheds with varying degrees of erosion sensitivity, emphasizing morphometric parameters and landscape characteristics. Furthermore, hypsometric analysis confirms a moderate to high susceptibility of sub-watersheds to soil erosion. Moreover, half of the river basin consists of shrubland, encompassing scrubs, range lands, and small wooded areas. These are less efficient in mitigating erosion compared to forests, especially in the face of significant summer rainfall and ensuing runoff. Statistical prioritization identified 19 sub-watersheds, covering 43% of the basin's total area, as highly prone to soil erosion and land degradation. The study's findings are valuable for Ethiopian watershed management decision-makers, enabling informed resource allocation and targeted interventions to control soil erosion and protect water resources by utilizing the outputs of this study.

Broad‐scale mapping of stream channel and floodplain geomorphic metrics is critical to improve the understanding of geomorphic change, biogeochemical processes, riverine habitat quality, and opportunities for management intervention. The Floodplain and Channel Evaluation Tool (FACET) was developed to provide an open‐source tool for automated processing of digital elevation models (DEMs) to generate regional‐scale estimates of bank height, channel width, floodplain width, and a suite of other fluvial geomorphic dimensions that can be summarized at the stream reach‐ or catchment‐scale. FACET was tested on 3‐m DEMs covering the Delaware River watershed and 85% of the Chesapeake Bay watershed in the United States (U.S.) and on 1‐m DEMs for a subset of the study area. Accuracy was assessed from data collected at 67 field sites in the study area. FACET successfully measured geomorphometry for over 270,000 stream reaches (88% of streams attempted) in the study area. Factors that reduced the ability of FACET to accurately estimate geomorphic metrics included errors in DEM hydro‐conditioning, gradually sloping banks, incised stream channels, and the use of fixed input parameters to define buffer lengths. Even with these limitations, FACET was able to map regional patterns in stream and floodplain geomorphometry providing a robust dataset that can enhance modeling and management efforts throughout the mid‐Atlantic region, U.S. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel method for determining the depth of lineaments using satellite gravity data, which we test in the Sahel of Sfax area (eastern Tunisia). This region has a relatively flat topography with few significant discontinuities at the surface. As a first step, we used morphometric indices such as slope, aspect, and hydrographic network, calculated from SRTM DEM, to generate separate lineament maps. We then combined these lineaments into a synthetic lineament map, one that showed to be highly consistent with the Bouguer anomaly map deduced from satellite gravity data and the results of similar studies with gravity and seismic geophysical data. The lineament map was then refined and confirmed thanks to field data. These lineaments were later combined with the 3D Euler solution map, and their depth classification was deduced. These results demonstrate both the accuracy of the proposed method as a way to assess lineament depth and its ability to provide valuable information about an area's subsurface geology. This method can be useful for mineral exploration, hydrocarbon exploration, and geohazard assessments. [ABSTRACT FROM AUTHOR]

This study focuses on the multiscale calculation of different plan curvature forms to enhance the modeling of soil penetration resistance and gravimetric soil water content utilizing the classification and regression trees algorithm in a low-relief watershed. To that end, three forms of plan curvature were derived using the Wood method from a two-meter digital elevation model on six neighborhood sizes. The results showed that the neighborhood size influenced the plan curvature values and there was little difference between the utilization of three forms of plan curvature in the landform determination. The modeling results indicated that the three forms of plan curvature on most neighborhood scales have different contributions to each other in modeling the spatial variability of each soil property. The neighborhood scale was a critical factor in soil modeling because it controls the smoothing rate of plan curvature. The overall results suggest that soil models with poor performance could be constructed if the plan curvature forms and the neighborhood size are not considered in the geomorphometric analysis. Therefore, it is recommended to use the procedure implemented in this study for digital soil mapping in various regions. [ABSTRACT FROM AUTHOR]

BACKGROUND AND OBJECTIVES: Micro-hydropower plants are significant contributors of electricity and clean source of renewable energy. A nationwide or large watershed inventory of potential micro hydropower dam sites is lacking, hindering micro-hydropower development. Traditional ground survey approaches for locating micro-hydropower dam sites are expensive, time-consuming, laborious, and vulnerable to inconsistency. Geographic information system frameworks are commonly used, and they provide significant value to hydropower evaluation. A suitability approach for dam site identification is important in supporting the optimization of hydropower utilization in the context of watershed management and in eliminating the inconsistency of conventional approaches. The objective of this study was to identify potential sites for micro-hydropower dams on the basis of various parameters by using a suitability modeling approach based on geographic information system. METHODS: The Saddang Watershed was chosen as the study area, it is located in the South Sulawesi and West Sulawesi Provinces of Indonesia, and it is an example of a large watershed. The analytical hierarchy process was used for criterion weighting and to create a dam suitability index map based on the following criteria: geomorphometry, geology, rainfall, soil texture, and land use land cover. The developed dam suitability index map was validated by comparing it with existing dams by using the receiver operating characteristic curve. The identification of potential micro-hydropower dam sites involved overlay and query methods. It considers dam suitability index, proximity from road and settlement, existence of conservation forest, and the potential hydraulic head. FINDINGS: The dam suitability index map with five suitability classes was obtained, with the high and very high suitability indexes extending to 8.7 percent of the study area. These classes were typified by high drainage density, topographic wetness index, stream power index, low vegetation cover, moderate slope, situated on second or higher stream orders, normal temporal distribution of rainfall, and sandy clay loam soil texture with igneous and sedimentary complex rocks. The developed suitability model was sufficiently effective in determining dam suitability index, as indicated by a value greater than 0.9 of the area under the curve. A total of 635 potential dam locations were identified with high and very high suitability indexes, located on first or second stream orders, within a 4,000 m radius of roads and settlements, outside conservation forest areas, and with a potential hydraulic head greater than 20 meter. CONCLUSION: Integrating a dam suitability index map and restriction factors into a geographic information system framework, enabled a robust analysis for identifying potential sites of microhydropower dams. The proposed approach is expected to contribute to the advancement of renewable energy initiatives and water resource management within large watersheds. It is also expected to serve as a valuable resource for policymakers involved in the implementation of microhydropower projects and watershed management to support the achievement of renewable energy development targets. [ABSTRACT FROM AUTHOR]

We discuss a technique for investigating changes in complex topography and shape of structures using geomorphometric methods to study surfaces of wafers and membranes formed by the Bosch process. The wafers were analyzed before and after the deposition of the SiO2 layer. The membranes were analyzed during the bulge testing. The study was carried out using maps of the catchment area and principal curvatures taking into account artifacts of the approximation of experimental data. We found a correspondence between the distribution of lines connecting the highest surface areas before and after the deposition of the SiO2 layer on the wafers. For membranes with structure: Al(0.8 μm)/SiO2(0.6 μm)/Al(1.1 μm), pSi*(0.8 μm)/SiNx (0.13 μm)/SiO2, Al(0.6 μm) we also found that features of membrane boundaries are mainly caused by their initial shape rather than change under the action of an applied pressure. The advantages of geomorphometric methods for studying changes in the shape of wafers and thin-film membranes in technological processes for the manufacturing of microelectronic devices are shown in comparison with traditional methods for analyzing surface topography maps. [ABSTRACT FROM AUTHOR]

Climate change research identifies risks to agriculture that will impact agricultural land suitability. To mitigate these impacts, agricultural growing regions will need to adapt, diversify, or shift in location. Various machine learning algorithms have successfully modelled agricultural land suitability globally, predominantly using climate and soil features. Topography controls many of the environmental processes that impact agriculture, including soils, hydrology, and nutrient availability. This research evaluated the relationship between specialty crops and topography using land-surface parameters extracted from a 30 m DEM, soil features, and specialty crop presence/absence data derived from eight years of previous land classifications in southern Ontario, Canada. Using random forest, a model was developed for each specialty crop where feature permutation importance, Matthew's correlation coefficient, and the area under the precision-recall curve was calculated. Elevation relative to watershed minimum and maximum, direct radiation on Day 172, and spherical standard deviation of normals were identified as the mean most important topographic features across all models and beet crops were found to have the highest association with topographic features. These results identify locations of agricultural expansion opportunities if climate becomes more favourable. The importance of topography in addition to climate and soils when identifying suitable areas for specialty crops is also highlighted. [ABSTRACT FROM AUTHOR]

The Granites-Tanami Orogen (GTO) is a significant auriferous province located in the poorly exposed southwestern part of the North Australian Craton. This paper looks at the data sources that are suited to studying regolith-landform in areas such as the Tanami Region. One of the most useful datasets for regional regolith-landform mapping is a digital elevation model (DEM). The DEM data that were reviewed demonstrated the utility of TanDEM over other sources, and quantitative results focused on these data for identifying regolith-landform patterns that would aid in geochemical sampling and other land use studies. This paper will demonstrate that neither the classical approach of mapping boundaries based on visual estimates of breaks in slope, nor the alternative approach of producing maps and models derived from algorithms, can be used in isolation. Visual estimates of many boundaries are complex, unreliable and time consuming, and algorithmic mapping is driven by parameters than can produce an infinite set of models. This paper shows that simple landform visualisation is often the most powerful tool for map and model creation, supported by geomorphometric analysis and remotely sensed spectral imagery. The use of TanDEM data is shown to produce the best regolith-landform maps and models of the Tanami Region, which can then improve mineral exploration success.

BACKGROUND AND OBJECTIVES: Micro-hydropower plants are significant contributors of electricity and clean source of renewable energy. A nationwide or large watershed inventory of potential micro hydropower dam sites is lacking, hindering micro-hydropower development. Traditional ground survey approaches for locating micro-hydropower dam sites are expensive, time-consuming, laborious, and vulnerable to inconsistency. Geographic information system frameworks are commonly used, and they provide significant value to hydropower evaluation. A suitability approach for dam site identification is important in supporting the optimization of hydropower utilization in the context of watershed management and in eliminating the inconsistency of conventional approaches. The objective of this study was to identify potential sites for micro-hydropower dams on the basis of various parameters by using a suitability modeling approach based on geographic information system.METHODS: The Saddang Watershed was chosen as the study area, it is located in the South Sulawesi and West Sulawesi Provinces of Indonesia, and it is an example of a large watershed. The analytical hierarchy process was used for criterion weighting and to create a dam suitability index map based on the following criteria: geomorphometry, geology, rainfall, soil texture, and land use land cover. The developed dam suitability index map was validated by comparing it with existing dams by using the receiver operating characteristic curve. The identification of potential micro-hydropower dam sites involved overlay and query methods. It considers dam suitability index, proximity from road and settlement, existence of conservation forest, and the potential hydraulic head.FINDINGS: The dam suitability index map with five suitability classes was obtained, with the high and very high suitability indexes extending to 8.7 percent of the study area. These classes were typified by high drainage density, topographic wetness index, stream power index, low vegetation cover, moderate slope, situated on second or higher stream orders, normal temporal distribution of rainfall, and sandy clay loam soil texture with igneous and sedimentary complex rocks. The developed suitability model was sufficiently effective in determining dam suitability index, as indicated by a value greater than 0.9 of the area under the curve. A total of 635 potential dam locations were identified with high and very high suitability indexes, located on first or second stream orders, within a 4,000 m radius of roads and settlements, outside conservation forest areas, and with a potential hydraulic head greater than 20 meter.CONCLUSION: Integrating a dam suitability index map and restriction factors into a geographic information system framework, enabled a robust analysis for identifying potential sites of micro-hydropower dams. The proposed approach is expected to contribute to the advancement of renewable energy initiatives and water resource management within large watersheds. It is also expected to serve as a valuable resource for policymakers involved in the implementation of micro-hydropower projects and watershed management to support the achievement of renewable energy development targets.

At least 10 global digital elevation models (DEMs) at one-arc-second resolution now cover Earth. Comparing derived grids, like slope or curvature, preserves surface spatial relationships, and can be more important than just elevation values. Such comparisons provide more nuanced DEM rankings than just elevation root mean square error (RMSE) for a small number of points. We present three new comparison categories: fraction of unexplained variance (FUV) for grids with continuous floating point values; accuracy metrics for integer code raster classifications; and comparison of stream channel vector networks. We compare six global DEMs that are digital surface models (DSMs), and four edited versions that use machine learning/artificial intelligence techniques to create a bare-earth digital terrain model (DTM) for different elevation ranges: full Earth elevations, under 120 m, under 80 m, and under 10 m. We find edited DTMs improve on elevation values, but because they do not incorporate other metrics in their training they do not improve overall on the source Copernicus DSM. We also rank 17 common geomorphic-derived grids for sensitivity to DEM quality, and document how landscape characteristics, especially slope, affect the results. None of the DEMs perform well in areas with low average slope compared to reference DTMs aggregated from 1 m airborne lidar data. This indicates that accurate work in low-relief areas grappling with global climate change should use airborne lidar or very high resolution image-derived DTMs.

Geomorphometric analysis provides crucial insights into the hydrological characteristics by delineating the land-surface features of a drainage basin. The study focused on analyzing the geomorphometric parameters of the Montenegrin segment of the Ibar River drainage basin using the ALOS Global Digital Surface Model 30 m (AW3D30). Geomorphometric parameters, covering linear and areal parameters, were computed using standard mathematical formulas in LibreOffice Calc software and hydrology tools in commercial GIS software ArcGIS, as well as open-source software QGIS with SAGA GIS modules. Results reveal a dendritic pattern in the stream network, with an inverse relationship between stream length and order, and an elevated bifurcation ratio indicating heightened vulnerability to flooding, influenced by geological, geomorphological, and climatic factors. Furthermore, examination of diverse areal morphometric parameters, such as drainage density, stream frequency, form factor, circularity ratio, and elongation ratio, unveils the hydrological dynamics of the Ibar basin. This characterization illustrates the region as possessing high permeability and dense vegetation cover, suggesting vulnerability to erosion and consequent effects on water and sediment discharge. Additionally, this study underscores the significance of user-defined parameters in geomorphometric modeling, particularly in selecting algorithms within analysis software, which significantly impact drainage basin parameters. [ABSTRACT FROM AUTHOR]

Soil erosion, a major factor contributing to land degradation, poses significant environmental challenges across sub-Saharan Africa, including Ethiopia. This study identifies erosion-prone sub-watersheds in southern Ethiopia's middle Omo-Gibe River basin using digital elevation model data, analyzed using a geomorphometric and statistically weighted sum priority approach in a Geographic Information System environment. Additionally, hypsometric analysis, lithology, land use/cover analysis, and field observations were integrated to enhance methodological reliability in assessing soil erosion patterns and subsequent land degradation in the basin. Results highlight sub-watersheds with varying degrees of erosion sensitivity, emphasizing morphometric parameters and landscape characteristics. Furthermore, hypsometric analysis confirms a moderate to high susceptibility of sub-watersheds to soil erosion. Moreover, half of the river basin consists of shrubland, encompassing scrubs, range lands, and small wooded areas. These are less efficient in mitigating erosion compared to forests, especially in the face of significant summer rainfall and ensuing runoff. Statistical prioritization identified 19 sub-watersheds, covering 43% of the basin's total area, as highly prone to soil erosion and land degradation. The study's findings are valuable for Ethiopian watershed management decision-makers, enabling informed resource allocation and targeted interventions to control soil erosion and protect water resources by utilizing the outputs of this study. [ABSTRACT FROM AUTHOR]

The Suwałki Glacial Megaflood Landsystem documented in NE Poland led to further morphological analysis of bedforms that originated from glacial lake-outburst floods (GLOFs) in the central and eastern parts of the Augustów Plain. This article focuses on (1) the recognition of largescale subaqueous dunes in the vicinity of Serwy Lake, (2) the creation of a database consisting of relevant morphometric parameters (lengths, heights and gradients of stoss and lee slopes) and indexes (steepness and asymmetry ratios) and (3) comparison with other landforms that undoubtably indicate glacial floods (e.g., Missoula, Altai, British Columbia, Wigry Lake). The remote identification and measurement of the megadunes' morphometry based on LiDAR data and digital elevation model with resolution 1×1 m (using hillshade and geomorphons) yielded data characterising 254 bedforms. These represent two-dimensional large-scale subaqueous dunes, which have lengths varying between 23.6 and 241.8 m and average heights of 0.6-5.4 m. Moreover, their morphometric variation creates a continuum typical of subaqueous dunes and has similarities to prominent examples linked to GLOFs. The study is especially crucial due to the lack of a wide range of information about megadune development under unconfined settings during the Weichselian glaciation. [ABSTRACT FROM AUTHOR]

Bankfull channel extents are of fundamental importance in fluvial geomorphology, to describe the geomorphic character of a river, and to provide a boundary for further processing of morphologic and hydraulic attributes. With ever‐increasing availability of high‐resolution spatial data (e.g., lidar, aerial photography), manual delineation of channel extents is a bottleneck which limits the geomorphic insights that can be gained from that data. To address this limitation, we developed and tested two automated channel delineation methods that define bankfull according to different conceptualisations of bankfull extent: (a) a cross‐sectional method called HydXS that identifies the elevation which maximizes hydraulic depth (cross‐section area/wetted width); and (b) a neural network image segmentation model based on a pretrained model (ResNet‐18), retrained with images derived from a digital elevation model. The cross‐sectional method outperformed the neural network method overall. Its prediction accuracy varied according to channel size and type, with overall precision of 0.87 and recall of 0.80. The neural network method was strongest in larger streams, and outperformed the cross‐sectional method in channel sections with inset benches. A tool to delineate morphological bankfull conditions can allow us to more efficiently implement high‐resolution and large‐scale analyses of channel morphology (e.g., regional hydraulic geometry, channel evolution, physical complexity/habitat surveys), and improve management of fluvial geomorphology and stressors. Plain Language Summary: Identifying the extents of rivers in the landscape is a necessary first step to better understand and manage them. Historically, delineating these extents has been an intensive manual task. We developed and tested two methods of automatically identifying river extents from high resolution elevation data. The first method used cross‐section data, and identified the elevation in each cross‐section where flow first starts to spread across the floodplain. The second method worked directly on gridded elevation data, identifying in‐river and out‐of‐river pixels using a neural network (a type of artificial intelligence model) trained on other image segmentation problems then retrained on our river elevation data. Both methods showed promise. The cross‐sectional method was most accurate overall, performing well on channels 7.5–26 m in width. The neural network method was more accurate for larger than smaller stream channels. It outperformed the cross‐sectional method in channels which had inset low flow channels within a larger high‐flow channel. The methods developed will allow us to map channel extents in a standardized and efficient way, opening the door to much larger‐scale analyses of river dimensions and processes. Key Points: Two automated bankfull identification methods based on lidar‐derived data were shown to perform well on alluvial stream channelsThe HydXS objective‐function cross‐sectional method performed best overall, with precision of 0.87 and recall of 0.80The neural network image segmentation method performed better in larger channels and outperformed HydXS in channels with inset benches [ABSTRACT FROM AUTHOR]

Numerically interpolated contour lines (NICL) developed from a high-resolution, accurate digital elevation model (DEM) can be considered the most accurate contour baseline available from surveyed data. Displays of this baseline, however, can exhibit an undesirable angularity and clutter that impedes human understanding of the data and defies the universal appeal of a smooth curve. To achieve smooth, readable lines, the prevailing wisdom today is to either 1) smooth the underlying surface model before creating the lines or 2) use mathematical methods adapted from computer-aided design (CAD) to smooth the lines in x and y. However, these smoothing methods can result in an inaccurate rendition of the original data that undermines their subsequent use in analysis and modeling applications. Upon close inspection, lines generated from such methods can depart from the baseline by more than a definable and acceptable distance in x and y, particularly noticeable in important areas of slope change. Here, we argue that generalized contours have a geometric accuracy requirement that must be observed. We present a novel alternative to the prevailing methods that 1) presents an incremental smoothing method that is a logical complement to Douglas-Poiker thinning; 2) introduces the use of slope as a means of controlling the degree of smoothing locally; 3) produces novel, operational definitions of tests for smoothness and accuracy as well as for line symmetry; and 4) introduces the notion of a topological TIN as a new type of terrain model and a medium for edits of contours. The method only manipulates the baseline contours in x and y. By using only simple proportions of sides and self-similar geometry to smooth the original lines, we at the same time impose computable, dynamic constraints on the smoothing. This combination ensures the accuracy and acceptability of the final contours at scales appropriate for working GIS displays. The result is a Locally Adjusted Curve Approximation (LACA) technique for contour line smoothing. [ABSTRACT FROM AUTHOR]

We describe the use of geomorphometric methods for studying thin-film structures in microelectronics. In particular, we developed a method for processing data from measuring equipment (optical profilometer and spectral ellipsometer) to calculate maps of mechanical stress distribution considering a complex (i.e., nonspherical) shape of structures (that is, nonuniform deformation) and nonuniform film thickness. The results of calculations for SiO2/Si and GaN/Al2O3 structures are presented. The calculated value of mechanical stresses for SiO2: σ ≤ 300 MPa. A relationship was obtained between the highest values of mechanical stress and volumetric defects for GaN. Geomorphometric methods are effective for (1) preparation of initial experimental data for the purpose of subsequent calculation of second partial derivatives (which are necessary for computation of mechanical stresses from the topographic data of structures); (2) direct calculation of curvature maps for subsequent determination of mechanical stresses; and (3) qualitative assessment of local topographic features poorly manifested on the initial topographic maps, which are directly related to the areas of the highest mechanical stresses. [ABSTRACT FROM AUTHOR]

Landslides represent one of the main geological hazards, especially in Chile. The main purpose of this study is to evaluate the application of machine learning algorithms (SVM, RF, XGBoost and logistic regression) and compare the results for the modeling of landslide susceptibility in the province of Chañaral, III region, Chile. A total of 86 sites are identified using various sources, in addition to 86 non-landslide sites. This spatial data management and analysis are conducted using QGIS software. The sites are randomly divided, and then a cross-validation process is applied to calculate the accuracy of the models. After that, from 22 conditioning factors, 12 are chosen based on the information gain ratio (IGR). Subsequently, five factors are excluded by the correlation criterion. After this analysis, two indices not previously utilized in the literature, the NDGI (normalized difference glacier index) and EVI (enhanced vegetation index), are employed for the final model. The performance of the models is evaluated through the area under the ROC (receiver operating characteristic) curve (AUC). To study the statistical behavior of the model, the Friedman nonparametric test is performed to compare the performance with the other algorithms and the Nemenyi test for pairwise comparison. Of the algorithms used, RF (AUC = 0.957) and XGBoost (AUC = 0.955) have the highest accuracy values measured in AUC compared to the other models and can be used for the same purpose in other geographic areas with similar characteristics. The findings of this investigation have the potential to assist in land use planning, landslide risk reduction, and informed decision making in the surrounding zones. [ABSTRACT FROM AUTHOR]

Copyright of Revista de la Asociación Geológica Argentina is the property of Asociacion Geologica Argentina and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: Mountain rivers differ from alluvial rivers due to their morphology and hydraulic characteristics. Within various types of mountain rivers, the canyon rivers are those under the direct or indirect influence of canyon landscapes. Studies involving canyons are extensive in the literature. However, there is a lack of knowledge to establish a relationship between morphology, topography, local sediments, and river channel characteristics. This study aims to understand the relationship between morphology, topography, and local sediments in a canyon river in Southern Brazil. Methods: Topobathymetric data were obtained during a field survey using a total station and an RTK-GPS device for three reaches (canyon landscape (CL), transition landscape (TL), and floodplain landscape (PL)) in the canyon river. Features such as bankfull width, depth, channel slope, and floodplain width were obtained. Geomorphic patterns of the reaches were evaluated in terms of their classification and similarity level through cluster analysis. Sediment size was surveyed using the zig-zag pebble-count procedure. Results: Results suggest that sediment supply is an essential characteristic of the canyon's influence on river morphology. This condition improves the heterogeneity observed in the Geomorphic Unit Tool and topographical results. The thalweg lines are more complex in CL than the TL and PL reaches. Three grain-size-distribution curves presented similar sediment size and mean diameters. Sediments larger than d80 remain immobile or, at least, need fractioning for transporting or depositing somewhere. Alternatively, these sediments may be transported during debris flow events or discharges with a high return period. Conclusion: The influence of the canyon on river characteristics weaken from upstream, close to the gorge, to downstream toward the floodplain. The valley shape can affect sediment transport since the entrenchment caused by the canyon walls influences the water level and the hydraulic conditions for incipient motion conditions. [ABSTRACT FROM AUTHOR]

The geomorphology of the Zanjanroud basin is affected by the active tectonic zones resulting from the interaction of the Soltanieh, Zanjan, Tarem, and Manjil faults and the faults that have been investigated more closely in this research. The interaction of these faults has made this basin in the form of a small high plateau, heterogeneous compared to the surrounding areas and a suitable place for the establishment of human settlements. In this research, remote sensing and geomorphometric techniques have been used to identify the lineaments and tectonic evidence in order to discover the tectonic effect on the geomorphology of the basin. The contour lines have been converted into a map after checking with the help of telemetry, geomorphometry and field techniques. Then, by analyzing and interpreting the evidence, the relationship between the dynamic pattern of the faults and its effects on the morphology of different landforms is presented with an emphasis on the interactive reconstruction of drainage networks and faults. The results show that the active tectonics of the faults are concentrated towards the centre of the basin and Zanjanroud area. On the other hand, the compliance of the morphology and topographical trends of the basin, as well as the Zanjan River canal and many drainages with the extraction lines with the help of geomorphometric techniques, clearly shows the effectiveness of geomorphometry to evaluate and prove the impact of terraforming on the geomorphology of the basins. Although no destructive earthquake has been reported in the region, But the presence of morphological evidence and the interruption of Quaternary to Holocene deposits indicate the active deformation of the region. Therefore, it seems that the fault systems of the basin have the potential to create earthquakes with a much higher magnitude than what has happened so far, which indicates the necessity of planning based on a detailed study of the faults in the region. [ABSTRACT FROM AUTHOR]

Landform diversity influences and interacts with both biodiversity and geodiversity and thus, they are key factors in the assessment of landscape resilience. However, research on the spatial relationships between landscape geodiversity and biodiversity is challenging because we are still lacking methods to link abiotic with biotic factors. The goal of this study is to explore and quantitatively assess the spatial relationship between geomorphometric factors and the relative distribution of rare earth elements (REEs) in soils and organism. Therefore, we selected a representative Mediterranean landscape characterized by ancient olive grove cultivations. The results show for different landforms and lithotypes a positive linear correlation in the lanthanum/samarium vs. lanthanum/ytterbium (La/Sm vs. La/Yb) signature between the bioavailable fraction of topsoil and olive drupe. Results of La/Yb vs. La/Sm reported as power function for olive drupes and topsoil follow comparable scaling ranges showing a power law of 0.83 and 0.71 respectively with an R2 0.96 vs. 0.71. A different scaling range behavior from topsoil to the related olive drupe was found for each parent rock material. Results of the Machine Learning (ML) modelling framework showed that the LaN/SmN in topsoil, were substantiality correlated to channel network base level, topographic wetness index, NDWI and valley depth. Under the physiographic environmental variables of the study area, the spatial distribution of LaN/YbN was mainly related to the lithological characteristics. Furthermore, NDVI was the most important variable to predict the fractionation ratio of LaN/YbN in olive drupe and the topographic channel network distance for LaN/SmN in olive drupe. Our findings provide new insights in the spatial distribution of REEs allowing an assessment of bio- and geodiversity of olive groves taking into account biophysical factors. Our research represents a starting point for future applications and modelling techniques to analyze at the catchment-scale the REEs biophysical fluxes and food traceability.

The increasing availability and quality of high-resolution bathymetry data has led to a growing need for automated classification approaches to extract seabed features and better understand our ever-changing and complex seascapes. Here we present a new set of GIS tools designed to classify seabed landforms on continental and island shelf settings. The classification approach utilises bathymetry data and its derivatives of slope, ruggedness and bathymetric position index to delineate key components of the seabed surface. The user is guided through a series of steps to break down the seabed surface into components termed ‘surface elements’ (e.g. smooth, rugose, slope areas), which are subsequently grouped into prominent seabed features termed ‘seabed landforms’ (e.g. reefs, channels, scarps). Manual review and editing are incorporated into the workflow, striking a balance between automation and expert manual interpretation. We present the toolset using examples from the statewide marine lidar dataset from New South Wales, Australia, and explore tool settings using bathymetric data representing different data sources (multibeam and marine lidar), environmental seascapes, data resolutions (2, 5, 10 and 20 m cell size) and data preparation treatments (with and without data smoothing). The GIS toolset presented offers an effective and flexible method to extract key features from high-resolution shelf bathymetry data. Such mapping provides fundamental baseline data for vast applications within marine planning, research and management.

Copyright of Revista de la Asociación Geológica Argentina is the property of Asociacion Geologica Argentina and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The geomorphology of the Zanjanroud basin is affected by the active tectonic zones resulting from the interaction of the Soltanieh, Zanjan, Tarem, and Manjil faults and the faults that have been investigated more closely in this research. The interaction of these faults has made this basin in the form of a small high plateau, heterogeneous compared to the surrounding areas and a suitable place for the establishment of human settlements. In this research, remote sensing and geomorphometric techniques have been used to identify the lineaments and tectonic evidence in order to discover the tectonic effect on the geomorphology of the basin. The contour lines have been converted into a map after checking with the help of telemetry, geomorphometry and field techniques. Then, by analyzing and interpreting the evidence, the relationship between the dynamic pattern of the faults and its effects on the morphology of different landforms is presented with an emphasis on the interactive reconstruction of drainage networks and faults. The results show that the active tectonics of the faults are concentrated towards the centre of the basin and Zanjanroud area. On the other hand, the compliance of the morphology and topographical trends of the basin, as well as the Zanjan River canal and many drainages with the extraction lines with the help of geomorphometric techniques, clearly shows the effectiveness of geomorphometry to evaluate and prove the impact of terraforming on the geomorphology of the basins. Although no destructive earthquake has been reported in the region, But the presence of morphological evidence and the interruption of Quaternary to Holocene deposits indicate the active deformation of the region. Therefore, it seems that the fault systems of the basin have the potential to create earthquakes with a much higher magnitude than what has happened so far, which indicates the necessity of planning based on a detailed study of the faults in the region. [ABSTRACT FROM AUTHOR]

Traditional methods of qualitative description of relief used in the process of landscape analysis, zoning, forecasting of exogenous processes, assessment of agricultural land do not allow to distinguish objectively forms of relief, to reveal statistically reliable relations between relief indicators and components of geosystems. For agro-ecological evaluation and land grouping with the help of modern methods of data classification, a geodatabase with quantitative indicators of relief is needed. Space images of high and medium spatial resolution are necessary for formation of geodata base of geomorphometric indicators during regional researches. Background. Quantitative (geomorphometric) indicators of relief are of great practical importance when identifying and describing landforms and relief elements. One or two indicators are often used for agricultural land assessment. In foreign literature various combined topographic indices are widely used for land classification. The scientific significance of the research is associated with modern methods of geomorphometric analysis of the relief based on remote sensing data and their application for automated mapping of relief types. Purpose. Creation of a geodatabase (GDB) of geomorphometric parameters of the Novosibirsk region on the basis of satellite data. Materials and methods. Digital modeling and geomorphometry methods were used in the work. Results. The database of geomorphometric parameters of the relief with the use of middle and high spatial resolution space images ALOP PALSAR (12.5 m/pixel) and ALOS DSM (30 m/pixel), topographic maps of M 1:25000 were developed. A geodatabase of geomorphometric parameters of the relief by the example of the Novosibirsk Region was developed including GIS information layers with geomorphometric parameters of the relief and attribute tables. The LGB has been used to map the types of relief in the Novosibirsk Region agrolandscapes. Automatic classification of relief types using multispectral images of K-Nearest Neighbor (KNN or k-NN, nearest neighbor) teacherless algorithms and the iterative self-organizing algorithm ISODATA (Self-Organizing Data Analysis) were performed. The input raster data for the terrain type classification were terrain parameters and vegetation indices NDVI, EVI, OSAVI, TSAVI, determined on the basis of multispectral satellite images Sentinel-2 A. By the example of Priobskiy central forest-steppe agrolandscape mapping of relief types was carried out: watershed drained undrained flat-leveled, watershed drained weakly drained, interfluvial undrained flatwaterlogged. The main relief-forming processes in the Priobskoye central forest-steppe agro-landscape are planar washout and waterlogging. Conclusion. Modern methods of geomorphometry and geoinformatics allow you to create a spatial database of geomorphometric parameters for a comprehensive assessment of the land on the basis of remote information. The use of a geomorphometric database of geomorphometric parameters of relief and vegetation indices made it possible to carry out mapping of relief types for the Novosibirsk region agrolandscapes.

Climate change research identifies risks to agriculture that will impact agricultural land suitability. To mitigate these impacts, agricultural growing regions will need to adapt, diversify, or shift in location. Various machine learning algorithms have successfully modelled agricultural land suitability globally, predominantly using climate and soil features. Topography controls many of the environmental processes that impact agriculture, including soils, hydrology, and nutrient availability. This research evaluated the relationship between specialty crops and topography using land-surface parameters extracted from a 30 m DEM, soil features, and specialty crop presence/absence data derived from eight years of previous land classifications in southern Ontario, Canada. Using random forest, a model was developed for each specialty crop where feature permutation importance, Matthew’s correlation coefficient, and the area under the precision-recall curve was calculated. Elevation relative to watershed minimum and maximum, direct radiation on Day 172, and spherical standard deviation of normals were identified as the mean most important topographic features across all models and beet crops were found to have the highest association with topographic features. These results identify locations of agricultural expansion opportunities if climate becomes more favourable. The importance of topography in addition to climate and soils when identifying suitable areas for specialty crops is also highlighted.

Digital elevation models (DEMs) are crucial in natural hazard assessments, as they often present the only comprehensive information. While satellites deliver remote sensing information of the land surface of up to 2m resolution, only 25% of the seafloor is mapped with a minimum resolution of 400m. The acquisition of high-resolution bathymetry requires hydroacoustic surveys by research vessels or autonomous vehicles, which is time-consuming and expensive. Predicted bathymetry from satellite altimetry, on the other hand, is widely available but has a significantly lower spatial resolution and high uncertainties in elevation, especially in shallow waters. The research on volcanic islands as a source of both volcanic as well as marine hazards such as tsunamis, is greatly limited by the lack of high-resolution bathymetry. Here we compare 24 geomorphometric parameters of 47 volcanic islands derived from a) the comprehensive bathymetric data of the General Bathymetric Chart of the Ocean (GEBCO) and b) high-resolution (< 250m), ship-based bathymetry. Out of 24 parameters tested, 20 show < ± 2.5% median deviation, and quartiles < ± 10%. Parameters describing the size of a volcanic island are the most robust and slope parameters show the greatest deviations. With this benchmark, we will be able to increase geomorphometric investigations to volcanic islands where little or no high-resolution bathymetry data is available.

Extreme precipitation events can cause geomorphic adjustments in the riverscapes. As a result of the increase in severity and frequency of these events in climate change scenarios, riverscapes may become more sensitive to the geoforms sculpting processes. Consequently, communities in the river valleys may be adversely affected, worsening socio-environmental problems arising from these places’ occupation. This work investigates the relationship between events classified as heavy rainfall and persistent rainfall and geomorphic adjustments in the riverscape. A section of the Itapocu River in southern Brazil between latitudes 26°25’S and 26°32’S was used as a case study. Extreme events recorded in pluviometers’ historical series located around the study area were selected and characterized. These events occurred between 01/30/2019 and 04/15/2019; 11/15/2020 and 12/30/2020; 02/23/2021 and 03/10/2021. The geomorphic adjustments were identified by selecting Sentinel-2 orbital imagery. The satellite images were applied in the river valley geoforms vectorization and correlation among transverse and longitudinal sections to the river valley. The analysis of fluvial sensitivity went through the adjustments’ significance evaluation by the Wilcoxon Signed Rank Test. The results indicated that the river presented adjustments related to extreme precipitation events. These adjustments were identified as channel migration, channel expansion, channel narrowing, river bar expansion, and river bar narrowing. However, only channel migration, channel expansion, and channel narrowing were significant. In 2019, 82.03% of the river was significantly affected by the events, while in 2020 and 2021, events impacted 57.67% and 64.72% of the river, respectively.

The mechanisms of sediment removal associated with the nivation process suite are underinvestigated, a situation that hinders development of a unified, coherent theory of cryoplanation terrace formation. This study links sorted stripes—a type of periglacial patterned ground frequently encountered on cryoplanation terrace treads—to active hydrologic networks capable of transporting large quantities of fine sediments on periglacial hillslopes. Traditional interpretations hold that the presence of sorted patterned ground indicates geomorphic quiescence, a view that has contributed to the dismissal of these features as a factor in the formation of erosional periglacial topography. We address the geomorphic role of sorted stripes as fluvial features by investigating their hydrologic potential for transporting weathered material across and off developing cryoplanation terraces. Flow modeling and watershed geomorphometric analyses were conducted using a high‐resolution digital elevation model of a large cryoplanation terrace in a geomorphically active periglacial upland near Atlin, British Columbia, Canada. Results demonstrate the landscape‐scale spatial organization and geomorphic effectiveness of sorted‐stripe networks—"little tools"—for transporting water and suspended sediment across large cryoplanated surfaces. We present a qualitative model of sediment production and transportation, "the periglacial conveyor system," that outlines erosional processes responsible for cryoplanation terrace formation and defines the distinctive hydrologic–geomorphic imprint imparted by sorted stripes on periglacial hillslopes. [ABSTRACT FROM AUTHOR]

Topography is a key factor that affects edaphic, climatic, and biotic factors directly or indirectly. Relationships between Compound Topographic Index (CTI) model and soil properties were investigated in order to determine the ecological potential of the area in order to plan the sustainability of the fertile lands and the rehabilitation of the degraded areas in the study area. Totally 84 soil samples (0–20 cm) collected from different land use types (forest, cropland, rangeland) in Karst Mountain, Andırın-Kahramanmaras, Turkey. The CTI distributions are generated from digital elevation data of 12 m resolution obtained from AlosPalsar Satellite images. Although CTI values changed to Forest> Cropland> Rangeland, the highest correlation was found between CTI and soil moisture content in rangeland (R2 = 0.81). Lower correlations were found with other land uses (R2 = 0.63 in Cropland and R2 = 0.31 in Forest). CEC and Clay content were found to have a significant (p < 0.01) positive correlation with Curvature. Despite a distinctive topographic structure of karst ecosystems, these correlations verified the influence of topography on soil properties. CTI, which has strong correlations with soil moisture content can be used in planning reclamation processes of degraded karst ecosystems. [ABSTRACT FROM AUTHOR]

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In the context of digital terrain analysis applied to morphocronological interpretation, this paper presents a proposed method for identifying and mapping paleosurfaces based exclusively by Digital Terrain Model (DTM) and geomorphometric parameters. It was considered that the highest residual elevations in a neighborhood predefined by the temporal-spatial relationship indicate the levels of paleosurfaces and that when tangential to the current surface in flat portions they characterize remnants or levels of old terraces. The study area included the state of Paraná, whose evaluation of the results considered previous papers of geochronological dating, evolutionary interpretations and measurements of long-term denudation rates. The results showed average rates of denudation and estimation of the age of erosion tops and remnants for each geomorphological context of the study area. [ABSTRACT FROM AUTHOR]

Historic agricultural practices have played a dominant role in shaping landscapes, creating a heritage which must be understood and conserved from the perspective of sustainable development. Agroforestry (i.e., the practice of combining trees with agriculture or livestock) has existed since ancient times in European countries, and it has been recognised as one of the most resilient and multifunctional cultural landscapes, providing a wide range of economic, sociocultural, and environmental benefits. This research explores aspects of the history, physical characteristics, decline, and current state of conservation of historic agroforestry systems on the Northern Apennines in Italy, using an interdisciplinary approach combining archival sources, landscape archaeology, dendrochronology, and GIS analysis. Furthermore, through computer-based modelling, this research aims to evaluate how the abandonment of this historic rural land-use strategy impacted slope geomorphic processes over the long term. The importance of environmental values attached to traditional rural landscapes has received much attention even beyond the heritage sector, justifying the definition of transdisciplinary approaches necessary to ensure the holistic management of landscapes. Through the integration of the Unit Stream Power-Based Erosion Deposition (USPED) equation with landscape archaeological data, the paper shows how restoring the historic agroforestry landscape could significantly mitigate soil mass movements in the area. Thus, the interdisciplinary workflow proposed in this study enables a deep understanding of both the historical evolution of agroforestry systems and its resulting effects for cumulative soil erosion and deposition in the face of climate change. [ABSTRACT FROM AUTHOR]

Landform classification is crucial for a host of applications that include geomorphological, soil mapping, radiative and gravity-controlled processes. Due to the complexity and rapid developments in the field of landform delineation, this study provides a scoping review to identify trends in the field. The review is premised on the PRISMA standard and is aimed to respond to the research questions pertaining to the global distribution of landform studies, methods used, datasets, analysis units and validation techniques. The articles were screened based on relevance and subject matter of which a total of 59 articles were selected for a full review. The parameters relating to where studies were conducted, datasets, methods of analysis, units of analysis, scale and validation approaches were collated and summarized. The study found that studies were predominantly conducted in Europe, South and East Asia and North America. Not many studies were found that were conducted in South America and the African region. The review revealed that locally sourced, very high-resolution digital elevation model ( DEM) products were becoming more readily available and employed for landform classification research. Of the globally available DEM sources, the SRTM still remains the most commonly used dataset in the field. Most landform delineation studies are based on expert knowledge. While object-based analysis is gaining momentum recently, pixel-based analysis is common and is also growing. Whereas validation techniques appeared to be mainly based on expert knowledge, most studies did not report on validation techniques. These results suggest that a systematic review of landform delineation may be necessary. Other aspects that may require investigation include a comparison of different DEMs for landform delineation, exploring more object-based studies, probing the value of quantitative validation approaches and data-driven analysis methods.

Libraries with pre-written codes optimize the workflow in cartography and reduce labour intensive data processing by iteratively applying scripts to implementing mapping tasks. Most existing Geographic Information System (GIS) approaches are based on traditional software with a graphical user's interface which significantly limits their performance. Although plugins are proposed to improve the functionality of many GIS programs, they are usually ad hoc in finding specific mapping solutions, e.g., cartographic projections and data conversion. We address this limitation by applying the principled approach of Geospatial Data Abstraction Library (GDAL), library for conversions between cartographic projections (PROJ) and Geographic Resources Analysis Support System (GRASS) GIS for geospatial data processing and morphometric analysis. This research presents topographic analysis of the dataset using scripting methods which include several tools: (1) GDAL, a translator library for raster and vector geospatial data formats used for converting Earth Global Relief Model (ETOPO1) GeoTIFF in XY Cartesian coordinates into World Geodetic System 1984 (WGS84) by the 'gdalwarp' utility; (2) PROJ projection transformation library used for converting ETOPO1 WGS84 grid to cartographic projections (Cassini–Soldner equirectangular, Equal Area Cylindrical, Two-Point Equidistant Azimuthal, and Oblique Mercator); and (3) GRASS GIS by sequential use of the following modules: r.info, d.mon, d.rast, r.colors, d.rast.leg, d.legend, d.northarrow, d.grid, d.text, g.region, and r.contour. The depth frequency was analysed by the module 'd.histogram'. The proposed approach provided a systematic way for morphometric measuring of topographic data and combine the advantages of the GDAL, PROJ, and GRASS GIS tools that include the informativeness, effectiveness, and representativeness in spatial data processing. The morphometric analysis included the computed slope, aspect, profile, and tangential curvature of the study area. The data analysis revealed the distribution pattern in topographic data: 24% of data with elevations below 400 m, 13% of data with depths −5000 to −6000 m, 4% of depths have values −3000 to −4000 m, the least frequent data (−6000 to 7000 m) <1%, 2% of depths have values −2000 to 3000 m in the basin, while other values are distributed proportionally. Further, by incorporating the generic coordinate transformation software library PROJ, the raster grid was transformed into various cartographic projections to demonstrate distortions in shape and area. Scripting techniques of GRASS GIS are demonstrated for applications in topographic modelling and raster data processing. The GRASS GIS shows the effectiveness for mapping and visualization, compatibility with libraries (GDAL, PROJ), technical flexibility in combining Graphical User Interface (GUI), and command-line data processing. The research contributes to the technical cartographic development. [ABSTRACT FROM AUTHOR]

In the well-known conceptual model SCORPAN, a given soil property is considered as dependent on the following environmental factors: soil, climate, organisms, topography, time, and space. Predictive mapping of soils in digital soil mapping is based on similar ideas, but environmental factors may include not only factors of soil formation, but also, for example, remote sensing data. At present, predictive mapping has found wide application not only in soil science but also in ecology, agriculture, and geomorphology. This paper provides a review of environmental factors that are used in predictive mapping with a special attention to situations, when wide sets of environmental factors may be used and a part of them are not quantitative, such as vegetation types. The systems of quantitative variables for topography and climate description are most developed, so special attention is paid to them. Land surface description is performed using both local and non-local variables that need integration. In climate description, variables, which give estimates of dry or wet terrain features, such as moisture ratio or water deficit, are essential. They need evaluation of potential evapotranspiration that is not measured by weather stations, but can be calculated. The possibilities of accounting for these and other environmental factors, including non-quantitative ones, in quantitative statistical models of predictive mapping are described together with principles of their construction, verification, comparison, and choice of appropriate models. Examples of predictive soil mapping applications are given for various scales, and their specificity for different scales is outlined. Some aspects of remote sensing data usage are discussed. [ABSTRACT FROM AUTHOR]

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Landform classification is crucial for a host of applications that include geomorphological, soil mapping, radiative and gravity-controlled processes. Due to the complexity and rapid developments in the field of landform delineation, this study provides a scoping review to identify trends in the field. The review is premised on the PRISMA standard and is aimed to respond to the research questions pertaining to the global distribution of landform studies, methods used, datasets, analysis units and validation techniques. The articles were screened based on relevance and subject matter of which a total of 59 articles were selected for a full review. The parameters relating to where studies were conducted, datasets, methods of analysis, units of analysis, scale and validation approaches were collated and summarized. The study found that studies were predominantly conducted in Europe, South and East Asia and North America. Not many studies were found that were conducted in South America and the African region. The review revealed that locally sourced, very high-resolution digital elevation model (DEM) products were becoming more readily available and employed for landform classification research. Of the globally available DEM sources, the SRTM still remains the most commonly used dataset in the field. Most landform delineation studies are based on expert knowledge. While object-based analysis is gaining momentum recently, pixel-based analysis is common and is also growing. Whereas validation techniques appeared to be mainly based on expert knowledge, most studies did not report on validation techniques. These results suggest that a systematic review of landform delineation may be necessary. Other aspects that may require investigation include a comparison of different DEMs for landform delineation, exploring more object-based studies, probing the value of quantitative validation approaches and data-driven analysis methods. [ABSTRACT FROM AUTHOR]

Complex mountain geodynamics are difficult to decouple due to forcing factors, feedback mechanisms, and system couplings that arise from interacting atmospheric, surface, and tectonic processes. The operational-scale dependencies and process–form relationships that govern the spatio-temporal extent of process regimes, which in turn govern relief production, have yet to be adequately characterized and mapped. This research establishes a topographic morphological structural framework for representing and querying the spatial organizational structure of the topography that governs, and is governed by mountain geodynamics. The spatial scale-dependent structure of the topography is accounted for using land-surface parameters and land-surface partitioning into distinct terrain units that represent important aspects of the geomorphological system. The properties and spatial topology of terrain units provide constraints for modeling process–form relationships, which are represented as process–form indices and synthesized using logistic regression to empirically detect glacial and bedrock river incision process regimes at the basin-scale for 31 basins in the Central Karakoram at about 80% accuracy. The topographic morphological structural framework approach provides a mechanism for tractable representation of scale-dependent topographic structure for automated characterization of the land surface, providing insight into polygenetic geomorphological systems and systems coupling through defined process–form relationships. [ABSTRACT FROM AUTHOR]

Eastern oysters (Crassostrea virginica) generate structurally complex reef systems that offer diverse ecosystem services. However, there is limited understanding of how reef structure translates into reef condition. This knowledge gap might be better addressed if oyster reef structure could be more rapidly assessed. Conventional in situ monitoring techniques are often time-intensive, invasive, and do not provide spatially continuous information on the reef structure. Unoccupied Aircraft Systems (UAS), commonly referred to as drones, equipped with optical sensors can rapidly and non-invasively map intertidal oyster reef surfaces. We demonstrate how a digital surface model from UAS-based light detection and ranging (lidar) can enable very high-resolution characterization and monitoring of intertidal oyster reef surface morphology. Generalized linear models (GLMs) identified relationships between in situ live oyster counts and surface complexity metrics derived from digital surface models produced from lidar point clouds. Statistically significant relationships between surface complexity metrics (e.g., gray level co-occurrence features, volume to area ratio, skewness of elevation) and live oyster counts suggest that surface complexity provides useful proxies for reef condition. Advancing the application of remote sensing to intertidal oyster reefs can help identify reefs that are prone to degradation and inform conservation and restoration strategies.