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Paper considers ecological geomorphometry as the scientific area aimed at the study of place and functions of terrain and modern morphogenetic processes in the functioning of other components of natural environment, ecosystems, and in shaping of the conditions for human activities, applying the methods of quantitative spatial analysis. Some terminological issues are considered, as well as a short history of geomorphometry, its main tasks and research methods. In particular, the methods of quantitative analysis of the structure of terrain surface are considered, namely –the detection of the spatial trends, of periodicity, and of the spatial autocorrelation. The capabilities of the method of autocovariogram building and analysis are shown for the purpose of the studies of terrain elements, forms and types, their automatic delineation and classification. The basics of ecologically grounded classification of morphometric variables are considered, as well as the principles of the delineation of complex morphometric variables (topographic ecological indices), which reflect the impact of terrain morphology on ecological processes and ecological factors distributions. The main principles of ecological classification of terrain elements are also considered, together with the automatic delineation of terrain forms and types on the basis of their geometric signatures, that are defined through the distribution of the set of morphometric variables and the parameters of their spatial variability. Paper also reviews former studies by the author in the areas of morphometric analysis of the terrain surfaces of several study areas in Ukrainian Carpathians; the automatic terrain classification and segmentation; the analysis of the relationships between morphometric variables and ecological factors, the character of ground cover and the vegetation. Key words: ecological geomorphometry; topographic surface; morphometric variables; morphotop, autocovariogram; geometric signature.

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 investiga...

The Indian plate’s western boundary is extremely tilted towards the direction of convergence between Asia and India signifying an exceptional example of massive scale oblique continent-continent collision. This transform boundary motion is sinistral in nature and Digital Elevation Model (DEM) based geomorphometry permits the investigation of 3-D characteristics of the regional topography. This technique is specifically useful along inter-plate transform margins where the visual interpretation and topographic assessment is unable to observe the trends of the landforms evolution. In this context, the geomorphometry of the regional surface might be influenced largely by climate change and lower rate of active deformation. The geomorphic indices; Isobase Levels (IBLs), Topographic Asymmetry factor (T-factor) and Hack Gradient Index (HGI) have been executed to analyze fluvial drainage networks in connection to neotectonic movements. The sinistral movement along the Chaman Fault system and relatively less deformed Katawaz Block are the major surface dynamics to compute the style of deformation in the Sulaiman Range and Lobe Region (SRLR). Within the SRLR, the Sulaiman Fold and Thrust Belt (SFTB) is thrusting with a rate of 4–15 mm/yr in a North-South (NS) trend between IndoPak-Eurasian and a shortening of 4–6 mm/yr in East-West (EW) context. Seismicity is typically towards NorthWest-SouthEast (NW-SE) accommodating the moment release in the current century between the IndoPak-Eurasian transform plate boundary in the western most of the western Himalayan Syntaxis. The results obtained from the applied geomorphic indices indicate significant uplift in terms of higher IBL and HGI values all along the SRLR (Harnai, Katwaz, Qilla Saifullah, Zhob, Loralai, Jissa Shareef, Sakhi Sarwar and Fort Munro). The T-factor results also display tilt block neotectonics that are in agreement with the results of IBL and HGI.

Multiscalar topography influence on soil distribution has a complex pattern that is related to overlay of pedological processes which occurred at different times, and these driving forces are correlated with many geomorphologic scales. In this sense, the present study tested the hypothesis whether multiscale geomorphometric generalized covariables can improve pedometric modeling. To achieve this goal, this case study applied the Random Forest algorithm to a multiscale geomorphometric database to predict soil surface attributes. The study area is in phanerozoic sedimentary basins, in the Alter do Chao geological formation, Eastern Amazon, Brazil. The multiscale geomorphometric generalization was applied at general and specific geomorphometric covariables, producing groups for each scale combination. The modeling was run using Random Forest for A-horizon thickness, pH, silt and sand content. For model evaluation, visual analysis of digital maps, metrics of forest structures and effect of variables on prediction were used. For evaluation of soil textural classifications, the confusion matrix with a Kappa index, and the user’s and producer’s accuracies were employed. The geomorphometry generalization tends to smooth curvatures and produces identifiable geomorphic representations at sub-watershed and watershed levels. The forest structures and effect of variables on prediction are in agreement with pedological knowledge. The multiscale geomorphometric generalized covariables improved accuracy metrics of soil surface texture classification, with the Kappa Index going from 43% to 62%. Therefore, it can be argued that topography influences soil distribution at combined coarser spatial scales and is able to predict soil particle size contents in the studied watershed. Future development of the multiscale geomorphometric generalization framework could include generalization methods concerning preservation of features, landform classification adaptable at multiple scales.

Glaciated areas are important targets for interdisciplinary research. In the last quarter of the 20th century, there has been a significant shift in glacier observation approaches from direct fieldwork to remote sensing. Over the past 15 years, unmanned aerial systems have been increasingly used for this purpose. In this article, we briefly describe a newly launched Russian–Chinese project aimed at developing a theory and methodology for digital modeling and analysis of the glacier microtopography using very high resolution data from unmanned aerial surveys. We argue the relevance of the study and review key publications on the application of digital terrain modeling and geomorphometry in glaciology. Next, we discuss the aim of the project and tasks performed by the Russian side, as well as materials and methods used in the study. As initial data, we use multi-temporal, digital aerial images of very high resolution (5 cm) collected by the unmanned aerial survey of the ice sheet and glaciers near the Larsemann Hills, East Antarctic. Finally, we present some examples for geomorphometric analysis of glacier microtopography including snow/ice features of eolian origin.

Neste trabalho foram investigadas variações de área nas geleiras no Monte Melimoyu (44ºS, 72ºO) no período de 1970-2017, e as possíveis relações com a variabilidade climática entre 1950 e 2017. Dados ópticos do Sentinel-2A, de elevação do Modelo Digital de Elevação (MDE) ASTER-GDEM v.2, e de área das geleiras do inventário GLIMS foram utilizados na análise em SIG. As séries temporais de precipitação do Explorador Climático - Chile, e dados de reanálise de temperatura da universidade de Delaware foram utilizados para a análise climática. A área das geleiras diminuiu de 80,97 km² em 1970 para 52,14 km² em 2017, representando 35,6% de área, com destaques para a retração de geleiras no Oeste, Sudoeste, Norte e Nordeste, com perdas entre 65% e 44% de área total, e variações de elevação da linha de frente entre 74 m e 570 m. A precipitação anual média aproximada foi de 2.359 mm no período de 1950 a 2017 e mostra tendência de diminuição de aproximadamente -18 mm/ano, enquanto que os dados de temperatura mostram média anual de 9,87°C e uma tendência contínua de aumento na região, de 0,04ºC entre 1948 e 2017. Os contrastes entre as geleiras em perda de área e variação de elevação da linha de frente estão relacionados às diferenças de área e geomorfometria de cada geleira. Essas geleiras são semelhantes em tamanho, altitude e declividade do setor frontal, e as variações identificadas podem estar relacionadas às tendências mais quentes e secas para o período analisado.

Relief classification methodologies seek to define the parameters that determine those parts of the terrestrial surface that present homogeneous forms and elements. The rapid development of geotechnology has increasingly provided tools and methodologies that assist in studies related to relief. The present work proposes a methodology to classify the relief in three taxonomic levels, using automated processing in a GIS environment. This procedure was applied in a case study of the Santa Maria River basin, in the west of Rio Grande do Sul State, Brazil. The digital data processing employed was the Geographic Information System ArcGIS® and the data from the SRTM 3 arc-second radar (90 meters) was the basis for the Digital Elevation Model. The processing for the first taxon used the amplitude and slope data to define four forms of relief: flat areas, slightly undulating hills, undulating hills, and hills with buttes and larger hills. In the second taxonomic level, ten relief elements were identified: flat, peak, ridge, shoulder, spur, slope, hollow, footslope, valley, and pit. In the third taxonomic level, the slope forms were characterized into eight units using the slope, profile, and curvature plane parameters. It was possible to detect the three proposed levels, the relief forms, relief elements, and slope forms. GIS processing offers a fast and precise definition of the relief forms and elements, and the slope forms, as well as the relationship between the three taxonomic levels.

The scientific community has widely discussed the role of abiotic and biotic forces in reshaping the Earth’s surface. Currently, the literature is debating whether humans are leaving a topographic signature on the landscape. Apart from the influence of humans on processes, does the resulting landscape bear an unmistakable signature of anthropogenic activities? This research analyses from a statistical point of view the morphological signature of anthropogenic and natural land covers in different topographic context, as a fundamental challenge in the emerging debate of human-environment relationships and the modelling of global environmental change. It aims to explore how intrinsically small-scale processes, related to land use, can influence the form of entire landscapes and to determine whether these processes create a distinctive topography. The work focusses on four study areas in floodplains, plain to hilly, hills and mountains, for which LiDAR-derived Digital Terrain Models (DTMs) are available. Surface morphology is described with different geomorphometric parameters (slope, mean curvature and surface peak curvature) and their frequency distribution. The results show that the distribution of geomorphometric indices can reveal anthropogenic land covers and landscapes. In most cases, different land covers show statistically significant differences (p < 0.05) in their morphology. Finally, this study demonstrates the possibility to use a geomorphic analysis to quantify anthropogenic impact based on land covers in different landscape contexts. This provides useful insight into understanding the impact of human activities on the present morphology and offers a comprehensive understanding of coupling human-land interaction from a geomorphological point of view.

Despite the rapid development of computational technologies and methods and the increasing number of publications related to the geomorphometric analysis of terrain, no summaries in this branch of geomorphology were created in the last decade. In the “Russian-language” articles and books in geomorphometry this problem is especially relevant. Sometimes, geomorphometry has become regarded as a semi-marginal discipline which has no real importance for studying of landforms. The list of the main drags for thegeomorphometric analysis development is given in the article: geomorphological convergence and homology, not-interpretability of complex statistical models, slight representativeness of common metrics for automatictracing of geomorphological boundaries, and so on. The possible solutions of these problems on the way to the morpho-chrono-genetic mapping of landforms are scheduled. A short review is provided of clustering, classification, computer vision and pattern recognition, development and using of unusual geomorphometric variables. The article encourages geomorphologists to intensify their efforts (and to lead the researches if possible) in these four thematic directions to prevent the proceeding separation of traditional geomorphology and geomorphometry.

The aim of this study is geomorphometric relief classification of a temperate latitude upland area in Central Europe. The Silesian Upland represents diversified structural relief which contains a fan-shaped configuration of long thresholds and wide erosion depressions. A 20 m × 20 m digital elevation model (DEM) provided input data for the analysis. The k-median method was applied to examine morphometric variables of the relief. The aim of these activities was to identify clusters with objects of similar mathematical characteristics. These clusters were the basis of landform classification. Smaller numbers of clusters 4 transparently show hypsometric relationships. Key elements of the morphology of the area were clearly visible. The division into 6 clusters gives the best results—a detailed but clear image of the morphological diversity by distinguishing characteristic landform elements. The results for 8 clusters show significant background noise and are ambiguous, which makes them difficult to identify. Our research has confirmed that the k-median method is a useful tool for landform classifications. We determined optimal parameters of this method (filtering window size, DEM resolution, number of clusters, aspect influence).

A surface network is a topological data structure formed by a set of thalwegs and ridges on a digital terrain model. Its computation relies on the detection of saddles on the terrain. Hence, computation methods must guarantee enough saddles are detected but also that no improper conflicts between ridges and thalwegs are created, leading to an inconsistent network. This paper presents a new approach that maximizes the number of saddles and ensures this topological consistency for high-resolution terrain models represented by a raster grid. The grid is triangulated in order to preserve saddles and to facilitate thalweg and ridge computation. It does not require any user parameter and lines remain aligned with triangulation edges, avoiding numerical errors. The method also includes a coherent partitioning of the terrain into hills and dales. A case study shows that the surface network computation can be achieved in reasonable time and hence can be applied to the analysis of large terrain models.

Finely resolved geodetic data provide an opportunity to assess the extent and morphology of crevasses and their change over time. Crevasses have the potential to bias geodetic measurements of elevation and mass change unless they are properly accounted for. We developed a framework that automatically maps and extracts crevasse geometry and masks them where they interfere with surface mass-balance assessment. Our study examines airborne light detection and ranging digital elevation models (LiDAR DEMs) from Haig Glacier, which is experiencing a transient response in its crevassed upper regions as the glacier thins, using a self-organizing map algorithm. This method successfully extracts and characterizes ~1000 crevasses, with an overall accuracy of 94%. The resulting map provides insight into stress and flow conditions. The crevasse mask also enables refined geodetic estimates of summer mass balance. From differencing of September and April LiDAR DEMs, the raw LiDAR DEM gives a 9% overestimate in the magnitude of glacier thinning over the summer: −5.48 m compared with a mean elevation change of −5.02 m when crevasses are masked out. Without identification and removal of crevasses, the LiDAR-derived summer mass balance therefore has a negative bias relative to the glaciological surface mass balance.

We explore the assumption that uplift drives erosion and hence, more dissected (eroded) terrains may indicate areas subject to more intense uplift than others, especially if other factors such as elevation and geology can be demonstrated as inconsistent with the spatial pattern of dissection. Geomorphometry and statistics are employed to recognize the enhanced erosional signal within a medium-altitude mountain terrain of the Sudetes in Central Europe, considered as a representative for moderately uplifted areas of complex bedrock diversity. This signal is understood as a meso-scale reflection of relief properties, whereas the recognition of homogeneous terrain units, different in terms of strength of erosional signal, is carried out by means of multi-criteria terrain classification, involving Principal Component Analysis and k-means grouping. Four groups covering 45% of the area have been identified. They were quantitatively compared with independent variables of altitude, lithology, structural units and rock strength, and also assessed in relation to rainfall pattern. It is concluded that their dependence on altitude and geology is only partial. Then, three types of dissected terrain are distinguished and interpreted in terms of uplift intensity, rock strength as a factor modulating erosional response to uplift and timescale. The spatial distribution of these types of terrain indicates several isolated ‘hot spots’ of erosional dissection on predominantly strong rocks, linked by less elevated areas, underlain by rocks of variable strength. The former are considered as having longer history of uplift and dissection, dated back to the late Palaeogene, whereas the latter record more recent history of endo-exogenic interactions, possibly since the late Miocene. The presence of canyon-like valleys incised into planar or gently sloping relief may indicate the most recent pulse of relief rejuvenation. The procedure proposed in the paper is suitable to be used in various settings, given that good quality topographic data are available.

Identification geogorphometric of the "Topographic Wetness Index and Terrain Ruggedness Index" has been carried out in the Riam Kanan sub-watershed to determine the type and distribution and its relationship with landforms and land use. The material used in this study is imagery SRTM 30 m, Google Earth imagery. The research process begins with secondary data collection, the next process is the interpretation of image SRTM 30 m imagery in order to obtain landform maps, interpretations of Google Earth imagery in order to obtain land use maps, correlate 30 m SRTM images through digital processes to classify the Terrain Ruggedness Index (TRI) and Topographic Wetness Index (TWI). The final process is data analysis by overlaying landform maps, land use and TRI and TWI. The results of the research data have obtained an area of 116,650.03 ha out of 13 types of distribution of landforms dominated by structural mountains which are quite extensive with 38,200.08 ha while land use consists of 8 types of distribution dominated by forest areas with an area of 88,070.15 ha. The results of the TWI analysis were dominated by class 1 (dry) with an area of 80,193.87 ha while TRI was dominated by class 3 (medium) with an area of 66,400.64 ha. Both TWI and TRI contained in landforms and land use are dominated by structural mountainous landforms which are quite insignificant and use of forest land. Keywords: Geomorphometry, LandForm, LandUse, Overlay.

The need for reducing erosion and sediment transport, and protecting human settlements has urged the construction of channel control works in mountain streams. Such works include different structures, the check dams being probably the most widespread and archetypical. The performance of channel control works in mountain streams has usually been evaluated based on their effectiveness in stabilizing the channels and the adjacent hillslopes, and in retaining sediment. The widespread presence of channel control works in mountain streams of various regions, however, has also a significant impact on hillslope-channel coupling and on sediment transfer across the channel system. Taking into account the impact of channel control works on sediment connectivity at the catchment scale has remarkable importance for planning new control structures and managing the existing ones and, more in general, for sediment management in mountain catchments. In this paper, we consider the channel control works within the conceptual framework of sediment connectivity and related terminology, and we analyze the spatial and temporal scales of the interactions between channel control works and sediment coupling-decoupling. Some examples from the Italian Alps outline the impact of check dams and other hydraulic structures on sediment connectivity and show the potential of geomorphometry in assessing such impacts. The overall effect of control works on sediment connectivity consists of an alteration of the sediment cascade with a decrease in the efficiency of sediment transfer. Sediment is partly retained behind grade-control dams within the catchment or in sediment traps equipped with retention check dams near the alluvial fan apex. These works contribute to decouple the alluvial fans from the upslope catchment. On the contrary, channel bed lining on alluvial fans favors sediment transfer to the receiving river, but this effect usually involves small amounts of sediment not retained by the check dams built upstream.

This work analyzed the application of Sentinel-2 multispectral imagery and GLIMS data for mapping glacier retreat and to estimate glacier area changes of Mount Melimoyu, located in northern Patagon...

This study demonstrated the potential of methods derived from geomorphometry and regression models to evaluate landslide susceptibility in a study area located in southern Colombia. From a morphometric stance, the first step was to evaluate the quality of DEM sources by comparison to control points obtained by static-mode GPS. The PALSAR_RTC_hi data was selected for having the best accuracy of heights and was used to derivate terrain parameters at SAGA software. Then, the Principal Component Analysis selected variables with low collinearity, and we classified twelve landforms using fuzzy k-means algorithm, which was compared to a geomorphological map by using the multinomial logistic regression method in R software. We got a Kappa coincidence index of about 30%. The resulting landslide susceptibility mapping took dependent (a mask with unstable-stable cells from an existing landslide inventory) and independent variables (selected morphometric ones). The binary logistic regression showed the propensity of the area to be adversely affected by landslides. This model’s performance was tested with a ROC curve over a sample, with 20% of landslide database resulting in an Area Under the Curve of 0,55. This result was contrasted with a spatial prediction model of debris flow, explaining the high frequency of avalanches.

Fine-resolution LiDAR DEMs can represent surface features such as road and railway embankments with high fidelity. However, transportation embankments are problematic for several environmental modelling applications, and particularly hydrological modelling. Currently, there are no automated techniques for the identification and removal of embankments from LiDAR DEMs. This paper presents a novel algorithm for identifying embankments in LiDAR DEMs. The algorithm utilizes repositioned transportation network cells as seed points in a region-growing operation. The embankment region grows based on derived morphometric parameters, including road surface width, embankment width, embankment height, and absolute slope. The technique was tested on eight LiDAR DEMs representing subsections of four watersheds in southwestern Ontario, Canada, ranging in size from 16 million cells to 134 million cells. The algorithm achieved a recall greater than or equal to 90% for seven of the eight DEMs, while achieving a Pearson’s phi correlation coefficient greater than 80% for five of the eight DEMs. Therefore, the method has moderate to high accuracy for identifying embankments. The processing times associated with applying the technique to the eight study site DEMs ranged from 1.4 s to 20.3 s, which demonstrates the practicality of using the embankment mapping tool in applications with data set sizes commonly encountered in practice.

A Deep-Seated Gravitational Slope Deformation (DSGSD) affects the SE slope of the Siah-kuh anticline in its SE periclinal tip in the Ilam region (Zagros Mts., Iran), almost 30 km south of the Seymareh Landslide, which represents the largest landslide on Earth surface. The DSGDS is driven by a Mass Rock Creep (MRC) process and involves an area of about 8 km2. The evolution of such a gravity-induced process is strictly related to the evolution of the of Dowairij River drainage system. River incision originated a stress release at the bottom of the slope which likely caused the initiation of the deformational process. The present study is part of a broader International Programme on Landslide project (Project IPL-237) focused on the role of time-dependent rock mass deformations and landscape evolution rates as predisposing factors for massive rock slope failures. In this regard, the preliminary results of an ongoing research are here presented focusing on the assessment of the present-day landscaping processes. Specifically, a geomorphological survey was carried out in this area firstly through the analysis and interpretation of remote data (Google Earth satellite optical images), which led to the first detection of possible gravity-induced landforms, such as evidence of bulging and lateral release within the deforming slope of the Siah-kuh fold-related ridge. To confirm and quantify the existence of ground displacement due to a MRC process, InSAR techniques were performed for the Siah-kuh slope and surrounding areas by processing 279 satellite Sentinel-1 (A and B) radar images of the ascending and descending orbit spanning from 06 October 2014 to 31 March 2019. Moreover, a quantitative morphometric evaluation was also performed through a morphometric index suitable for predicting the catchment-scale suspended sediment yield on the deformation area produced by the Dowairij River system. We derived the erosion rate of the drainage network responsible for the valley engraving which allows to estimate a starting time for MRC in the order of 101 ka. The comparison between the valley erosion rate and the slope strain rate reveals a difference of almost one order of magnitude allowing to assume that the gravity induced process, identified from remote and field geomorphological survey, evolves faster and originates landforms which can be preserved by the drainage system of the Dowairij River.

For developing countries, detailed soil resource data and maps are essential in land-use planning. Unfortunately, obtaining detailed soil data for mapping is expensive. Detailed soil studies and mapping in developing countries often use the grid method. In addition to being time-consuming, the grid method needs a lot of sample points and surveyors. Geomorphometry can be a less expensive alternative for detailed soil mapping. Geomorphometry uses computationally measured terrain characteristics to describe other hard-to-measure terrain and soil properties. In our study, landform arrangements and slopes were analyzed together to create a map of soil pH. Bompon watershed, Indonesia, was used as a case study. Soil mapping units with potentially similar soil pH were created based on a classification system of the two geomorphometric parameters. Soil samples were taken from each of the units. The samples' soil pH was measured and compared to the geomorphometric predicted result. Regression tests were performed to see the significance of geomorphometric parameters on soil pH conditions. Regression tests show that the results of p value of the four soil layers are 0.046, 0.019, 0.037, and 0.047, respectively, on a 5% confidence level. According to the test result, landform arrangements and slopes can indicate soil pH conditions in Bompon. Our estimate suggests that our geomorphometric method is cheaper than the grid method by a factor of seven. The ability to use geomorphometric parameters to describe other soil properties could enable a cheap and fast production of detailed soil maps for developing countries.

Despite of the geomorphological diversity of Central America and Costa Rica, there are few detailed geomorphological studies in the region. A 1:25,000 geomorphological analyses of the Upper General River Basin (UGRB) located in the southeast in Costa Rica is presented, based on the interpretation of aerial photographs and field geomorphological mapping. First, a morphometric analysis was performed to calculate and analyze seven variables that were merged in order to produce the flood and landslides susceptibility maps. Second, a total of 43 types of landforms divided genetically into endogenic (tectonic), and exogenic (fluvial, gravitational, and glacial) features are mapped for an area of 1560 km2. Finally, a geomorphological hazard map with the zonation of the different susceptibility levels of landslides and floods were performed. This cartography is important in terms of geomorphological evolution, disaster risk reduction as well as for land use planning for approximately 40,000 inhabitants. The presented methodology can also be applied in other developing countries for different purposes such as landscape evolution, morphogenetic detailed maps, disaster risk reduction, and land use planning.

Made available in DSpace on 2021-06-25T10:20:57Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-01-01 The Tapajós river is among the largest rivers in the world and has been credited as the main affluent of the lower Amazon River. Geomorphological studies in the Tapajós commonly deal with evolutionary, hydrological, and sedimentological issues. Recently, important advances have been made in understanding the morphology and dynamics in the Tapajós, especially in the confluence zone near Santarém, eastern Amazonian Brazil. However, the lack of an independent channel classification system makes it difficult to integrate data obtained from different sources. This work presents a classification system for the lower Tapajós based on morphometric variables extracted from transversal profiles coupled with radar and optical remote sensing data. We used discriminant analysis of principal components for the first time in fluvial geomorphology to provide a clustering-based geomorphological classification, which is statistically supported. We propose a segmentation of the channel into three distinct sections referred to as narrower channel reach, higher ria reach, and lower ria reach. The results showed that the channel has a distinct morphological pattern in each of these reaches, which can also be observed by the variation along the longitudinal profile. Our findings showed that the most variable hydrological and sedimentological patterns are found in the lower ria reach, while the higher ria reach comprises a canyon-shaped, more stable part of the channel. We discuss the implications of this pattern on the ria’s evolution. The method developed here could be applied to other areas of the Amazon basin, where the lack of data and logistical difficulties carrying out fieldwork are common obstacles to large-scale investigations. The identified reaches are indended to be considered in the sample design of future works and in the formulation of water resources management strategies. Universidade Federal do Oeste do Pará – UFOPA Universidade Federal de São Paulo – UNIFESP Universidade Estadual Paulista – UNESP Universidade Estadual Paulista – UNESP

Mountain regions are characterized by a spatial geomorphic heterogeneity that confers on the environment a significant geomorphodiversity. A methodology based on a different scale/spatial/resolution approach is proposed to evaluate the relationship existing among geomorphodiversity, geomorphological processes. and sediment connectivity. Starting from the geomorphological mapping of the Veglia Devero Natural Park (Lepontine Alps), indexes of fragmentation (IFrm) and geomorphodiversity (IGmf) were computed. The results were used to select a meaningful sub-area (Buscagna stream catchment) for calculating the index of connectivity (IC). The relationships among these three indexes are discussed, using a semi-quantitative approach including descriptive statistics (i.e., box plot) and analysis of the different geomorphoconnectivity sectors, testifying to the role of geomorphic processes in regulating sediment fluxes and, consequently, controlling landscape units. IGmf turned out to be more conservative than IFrm and more management-oriented for protected areas, while IC was confirmed to be particularly suitable to characterize connectivity in small mountain catchments featuring different geomorphic processes and a complex topography. This study suggests that coupling the sediment connectivity with the geomorphology and geomorphodiversity of a given area represents a quite novel approach that could be usefully applied in the framework of protected areas to investigate also biodiversity patterns and consequently environmental evolution in space and time.

Mud volcanism is observed in many tectonically active regions worldwide. One of the typical areas of mud volcanic activity is the Taman Peninsula, Russia. In this article, we examine the possibilities of multiscale analysis of remote sensing and morphometric data of different origins, years, scales, and resolutions for studying mud volcanic landscapes. The research is exemplified by the central-northern margin of the Taman Peninsula, where mud volcanism has only been little studied. The data set included one arc-second gridded Advanced Land Observing Satellite World three-dimensional (3D) digital surface model (AW3D30 DSM); a Corona historical declassified satellite photography; high-resolution imagery from an unmanned aerial survey (UAS) conducted with a multi-copter drone DJI Phantom 4 Pro, as well as a series of 1-m gridded morphometric models, including 12 curvatures (minimal, maximal, mean, Gaussian, unsphericity, horizontal, vertical, difference, vertical excess, horizontal excess, accumulation, and ring one) derived from UAS-based images. The data analysis allowed us to clarify the conditions of neotectonic development in the central-northern margin of the Taman Peninsula, as well as to specify manifestations of the mud volcanism in this region. In particular, we were able to detect minor and weakly topographically expressed mud volcanic features (probably, inactive gryphons, and salses), which are hidden by long-term farming practice (e.g., ploughed and covered by soil).

Terrain derivatives exhibit surface morphology in various aspects. However, existing spatial change calculation methods for terrain derivatives are based on a mathematical scalar operating system, which may disregard the directional property of the original data to a certain extent. This situation is particularly true in second-order terrain derivatives, in which original data can be terrain derivatives with clear directional properties, such as slope or aspect. Thus, this study proposes a mathematical vector operation method for the calculation of second-order terrain derivatives. Given the examples of the first-order terrain derivatives of slope and aspect, their second-order terrain derivatives are calculated using the proposed vector method. Directional properties are considered and vectorized using the following steps: rotation-type judgment, standardization of initial direction, and vector representation. The proposed vector method is applied to one mathematical Gaussian surface and three different ground landform areas using digital elevation models (DEMs) with 5 and 1 m resolutions. Comparison analysis results between the vector and scalar methods show that the former achieves more reasonable and accurate second-order terrain derivatives than the latter. Moreover, the vector method avoids overexpression or even exaggeration errors. This vector operation concept and its expanded methods can be applied in calculating other terrain derivatives in geomorphometry.

In the Mediterranean Sea, crustose coralline algae form endemic algal reefs known as Coralligenous (C) build-ups. The high degree of complexity that C can reach through time creates notable environmental heterogeneity making C a major hotspot of biodiversity for the Mediterranean basin. C build-up can variably modify the submarine environment by affecting the evolution of submerged landforms, although its role is still far from being systematically defined. Our work proposes a new, ad-hoc semi-automated, GIS-based methodology to map the distribution of C build-ups in shallow coastal waters using high-resolution bathymetric data, collected on a sector of the southern Apulian continental shelf (Southern Adriatic Sea, Italy). Our results quantitatively define the 3D distribution of C in terms of area and volume, estimating more than 103,000 build-ups, covering an area of roughly 305,200 m2, for a total volume of 315,700 m3. Our work firstly combines acoustic survey techniques and geomorphometric analysis to develop innovative approaches for eco-geomorphological studies. The obtained results can contribute to a better definition of the ocean carbon budget, and to the monitoring of local anthropogenic impacts (e.g., bottom trawling damage) and global changes, like ocean warming and acidification. These can affect the structural complexity and total volume of carbonate deposits characterizing the Mediterranean benthic environment.

The stream length-gradient (SL) index is widely used in geomorphological studies aimed at detecting knickzones, which are extensive along-stream deviations from the typical concave-up shape assumed for stream longitudinal profiles at steady-state conditions. In particular, SL was practical for identifying anomalous gradients along bedrock stream channels in mountainous catchments. This work presents the GIS toolbox SLiX designed to extract values of the SL index, starting from Digital Elevation Models (DEMs). SLiX is also suitable for the spatial analysis of the SL values, allowing for the identification of landscape portions where anomalous high values of SL occur and, consequently, those catchment sectors where stream channels show peaks in the erosional dynamic. The SLiX main outputs are (i) point shapefiles containing, among stream channels attributes, the extracted values of SL along the stream network analyzed, and (ii) SL anomaly maps in GeoTIFF format, computed through the Hotspot and Cluster Analysis (HCA), that permit the detection of the catchment sectors where the major SL anomalies occur and consequently the principal knickzones. The application of the proposed tool within an experimental catchment located in the Northern Apennines of Italy demonstrated the proper functionality and the potential of its use for different geomorphological and environmental studies. The accurate and cost-effective detection of anomalous changes in stream gradient ensured by SLiX is of great interest and can be useful for studies aimed at unravelling the Earth processes responsible of their formation (e.g., active hillslope processes, such as landslides directly interacting with the streambed, presence of geological structures, and meander cut-off). The applications of SLiX have clear implications for preliminary analyses, at a regional scale in different morpho-climatic contexts, for the hydrological management of river basins and/or to prevent geological hazards related to the fluvial erosional dynamics.

In this work, we tested the reliability of two different methods of automated landform classification (ACL) in three geological domains of the southern Italian chain with contrasting morphological features. ACL maps deriving from the TPI-based (topographic position index) algorithm are strictly dependent to the search input parameters and they are not able to fully capture landforms of different size. Geomorphons-based classification has shown a higher potential and can represent a powerful method of ACL, although it should be improved with the introduction of additional DEM-based parameters for the extraction of landform classes.

Context Recent research suggests that novel geodiversity data on landforms, hydrology and surface materials can improve biodiversity models at the landscape scale by quantifying abiotic variability more effectively than commonly used measures of spatial heterogeneity. However, few studies consider whether these variables can account for, and improve our understanding of, species’ distributions. Objectives Assess the role of geodiversity components as macro-scale controls of plant species’ distributions in a montane landscape. Methods We used an innovative approach to quantifying a landscape, creating an ecologically meaningful geodiversity dataset that accounted for hydrology, morphometry (landforms derived from geomorphometric techniques), and soil parent material (data from expert sources). We compared models with geodiversity to those just using topographic metrics (e.g. slope and elevation) and climate data. Species distribution models (SDMs) were produced for ‘rare’ (N = 76) and ‘common’ (N = 505) plant species at 1 km2 resolution for the Cairngorms National Park, Scotland. Results The addition of automatically produced landform geodiversity data and hydrological features to a basic SDM (climate, elevation, and slope) resulted in a significant improvement in model fit across all common species’ distribution models. Adding further geodiversity data on surface materials resulted in a less consistent statistical improvement, but added considerable conceptual value to many individual rare and common SDMs. Conclusions The geodiversity data used here helped us capture the abiotic environment’s heterogeneity and allowed for explicit links between the geophysical landscape and species’ ecology. It is encouraging that relatively simple and easily produced geodiversity data have the potential to improve SDMs. Our findings have important implications for applied conservation and support the need to consider geodiversity in management. Electronic supplementary material The online version of this article (10.1007/s10980-018-0723-z) contains supplementary material, which is available to authorized users.

Many retreating Alpine valley glaciers leave large lateral moraines behind. Reworking of these landforms by geomorphic processes is one of the most important paraglacial processes in many Alpine environments. Although several studies investigated moraine reworking by gullying processes, it is not well known what happens when gullying ceases and why and when lateral moraine slopes become stable. This study improves the understanding of the paraglacial transition from active to stable Alpine lateral moraine slopes by assessing potential influencing factors, indicators for completed paraglacial adjustment, and its spatiotemporal patterns using a combination of geomorphic and ecologic data. A geomorphic and ecologic permanent plot survey and geomorphic mapping were carried out on three lateral moraine complexes in the Turtmann glacier foreland (Switzerland). Subsequently, permanent plot data were analysed using multivariate statistics. Our study suggests that ecosystem engineering by colonizing plant species, slope geomorphometry, and material properties are important factors influencing the paraglacial transition from active to stable slopes. Geomorphic processes are often absent once vertical vegetation layers and soil horizons develop, showing that mature vegetation and advanced soil development are valuable indicators for slope stability and completed paraglacial adjustment. In a conceptual model, we describe the paraglacial transition of Alpine lateral moraine slopes as a temporal sequence in which gullying (Stage I), solifluction (Stage II), and finally stabilization (Stage III) follow one after another. In space, paraglacial adjustment is heterogeneous, and resulting patterns can be explained by the identified influencing factors.

Topographic measures are frequently used in a variety of landscape ecology applications, in their simplest form as elevation, slope, and aspect, but increasingly more complex measures are being employed. We explore terrain metric similarity with changes in scale, both grain and extent, and examine how selecting the best measures is sensitive to changes in application. There are three types of topographic measures: 1) those that relate to orientation for approximating solar input, 2) those that capture variability in terrain configuration, and 3) those that provide metrics about landform features. Many biodiversity hotspots and predators have been found to coincide with areas of complexity, yet most complexity measures cannot differentiate between terrain steepness and uneven and broken terrain. Currently characterizing terrain in landscape-level analyses can be challenging, especially at coarser spatial resolutions but developing methods that improve landscape-level assessments include multivariate approaches and the use of neighborhood statistics. Some measures are sensitive to the spatial grain of calculation, the physiography of the landscape, and the scale of application. We show which measures have the potential to be multi-collinear, and illustrate with a case study how the selection of the best measures can change depending on the question at hand using mountain lion (Puma concolor) occurrence data. The case study showed a combination of infrequently employed metrics, such as view-shed analysis and focal statistics, outperform more commonly employed singular metrics. The use of focal statistics as a measure of topographic complexity shows promise for improving how mountain lions use terrain features.

The goal of this study was to experiment artificial neural network (ANN) classifier on various available physical factors in the study area to produce a reliable landslide susceptibility map. The mapping of landsides is classically established through the identification and analysis of hillslope instability factors. Even if a variety of approaches use these analyses with geographic information system (GIS) performances to carry out a good result, there is no satisfaction because of the complexity of the landslides encountered in the field. In the present study, landslide susceptibility models were produced by using multilayer perceptron (MLP) ANN in the Mediterranean Rif coastal zone of Morocco. This was established in the following steps: (i) production of landslide inventory map; (ii) production of the hillslope factors, twenty factors composed of geology, geomorphometry, proximity, and thematic data derived from satellite imageries; (iii) extraction of vector model to be used to train ANN, construction of ANN models; (iv) validation and evaluation of results. The results of the prediction models were evaluated by the receiver operating characteristic (ROC) curves. The obtained area under the curve (AUC) values are greater than 0.90, indicating that the models are quite accurate. The visual comparisons between landslide susceptibility maps and the input factor maps show that roads and geology are the most important factors influencing five types of mass movements (complex, slide, flow, and rockfall). The success of this work will be helpful to expand this method to the whole Rif mountains in Morocco.

This study evaluates the relationships between dimensionless basin geomorphometry and discharge in the Ikpa River. The basin was stratified into seven sub-units using [1] scheme. Geospatial tools were used in generating data for the digital elevation model, while dimensionless geomorphometric parameters were generated from topographic maps (sheet 322 NE; sheet 322 SE; sheet 323 SW; and sheet 331 NW) of the basin area drawn on a scale of 1.50,000. The sampled sub-basins were gauged and discharge measured by a surface float. Graphical analysis of discharge revealed wide variations between months and in seasons across sub-basins with the rainy season attracting highest volume of discharge and the corresponding fluvial processes. The regression analysis yields a coefficient of multiple determination (R) of 0.937, signifying a very high effect expressed by 87.8 of the proportion of variance in dimensionless geomorphometric parameters on discharge in Ikpa River Basin. Also, the computed F value yields 1.439, while the Table value tested at (0.05)5/2 confident level offers 19.30. The result led to the conclusion that variations in relief ratio, average bifurcation ratio, circularity ratio, elongation ratio and form factor have a significant effect on discharge in Ikpa River Basin. This paper recommends for prompt installations of state of the art river gauging and monitoring facilities to provide the needed information to the government, researchers, and individuals for the sustainable land and watershed development options (dam and irrigation) in the coastal plain of Ikpa River basin.

Polygon-based terrain classification data were created globally using 280 m digital elevation models (DEMs) interpolated from the multi-error-removed improved-terrain DEM (MERIT DEM). First, area segmentation was performed globally with the logarithmic value of slope gradient and the local convexity calculated from the DEM. Next, by adding surface texture, k-means clustering was performed globally and the polygons were grouped into 40 clusters. Then, we tried to reclassify these 40 clusters into geomorphologic terrain groups. In this study, we attempted reclassification and grouping using local information from Japan as a test case. The 40 clusters were compared with Japanese geological and geomorphological data and were then reclassified into 12 groups that had different geomorphological and geological characteristics. In addition, large shape landforms, mountains, and hills were subdivided by using the combined texture. Finally, 15 groups were created as terrain groups. Cross tabulations were performed with geological or lithological maps of California and Australia in order to investigate if the Japanese grouping of the clusters was also meaningful for other regions. The classification is improved from previous studies that used 1-km DEMs, especially for the representation of terrace shapes and landform elements smaller than 1 km. The results were generally suitable for distinguishing bedrock mountains, hills, large highland slopes, intermediate landforms (plateaus, terraces, large lowland slopes), and plains. On the other hand, the cross tabulations indicate that in the case of gentler landforms under different geologic provinces/climates, similar topographies may not always indicate similar formative mechanisms and lithology. This may be solved by locally replacing the legend; however, care is necessary for mixed areas where both depositional and erosional gentle plains exist. Moreover, the limit of the description of geometric signatures still appears in failure to detect narrow valley bottom plains, metropolitan areas, and slight rises in gentle plains. Therefore, both global and local perspectives regarding geologic province and climate are necessary for better grouping of the clusters, and additional parameters or higher resolution DEMs are necessary. Successful classification of terrain types of geomorphology may lead to a better understanding of terrain susceptibility to natural hazards and land development.

A pesquisa tem como objetivo estabelecer a relacao entre o padrao de formas do terreno, representado pelos parâmetros geomorfometricos e as diferentes classes de cobertura e uso da terra. A area de estudo corresponde a Bacia Hidrografica do Arroio Carijinho, que esta localizada na porcao central do Estado do Rio Grande do Sul, abrange area referente a 162,71 km². A pesquisa se justifica pela nao existencia de materiais e trabalhos academicos que auxiliam na elaboracao de politicas publicas para os municipios. Alem disso, o canal principal do Arroio Carijinho, possui barragem da Companhia Riograndense de Saneamento (CORSAN) que auxilia no abastecimento de agua potavel. Os dados topograficos de altitude, declividade e plano de curvatura foram obtidos a partir do SRTM (90m) e trabalhados em uma arvore de decisao. O uso e a cobertura da terra na bacia hidrografica utilizou-se uma imagem do satelite Sentinel – 2B de 02/07/2017 com resolucao espacial de 10 metros. A analise dos parâmetros topograficos definidos, gerou oito unidades geomorfometricas distintas. O cruzamento entre a geomorfometria e as classes de cobertura e uso da terra demonstram a atuacao do homem, associado as relacoes sociais envolvidas sobre as formas de relevo. Evidencia-se a importância do estudo do relevo no planejamento ambiental aliado ao ordenamento territorial, tendo como base a definicao de locais apropriados para os diferentes usos. A B S T R A C T The research aims to establish the relationship between the pattern of the landforms, represented by geomorphometric parameters, and the different classes of coverage and use of the land. The study area corresponds Hydrographic Basin to the Arroio Carijinho, which is located in the central portion of the Rio Grande do Sul, with area of 162.71 km². The research is justified by the lack of materials and academic works that help in the elaboration of public policies for the municipalities. In addition, the main channel of Arroio Carijinho, has a dam of Companhia Riograndense de Saneamento (CORSAN) that assists in the supply of drinking water. The topographic data of altitude, slope and curvature plane were obtained from the SRTM (90m) and worked on a decision tree. The use and cover of the land in the hydrographic basin was used an image of the satellite Sentinel - 2B of 02/07/2017 with spatial resolution of 10 meters. The analysis of the defined topographic parameters generated eight different geomorphometric units. The cross between the geomorphometry and the classes of cover and use of the land demonstrate the performance of the man, associated with the social relations involved on the landforms. It is evident the importance of the study of the relief in the environmental planning allied to the territorial planning, based on the definition of appropriate places for the different uses. Keywords: Geomorphometry; Hidrographic basin; Planning

Gully erosion is a widespread and significant process involved in soil and land degradation. Mapping gullies helps to quantify past, and anticipate future, soil losses. Digital terrain models offer promising data for automatically detecting and mapping gullies especially in vegetated areas, although methods vary widely measures of local terrain roughness are the most varied and debated among these methods. Rarely do studies test the performance of roughness metrics for mapping gullies, limiting their applicability to small training areas. To this end, we systematically explored how local terrain roughness derived from high-resolution Light Detection And Ranging (LiDAR) data can aid in the unsupervised detection of gullies over a large area. We also tested expanding this method for other landforms diagnostic of similarly abrupt land-surface changes, including lava fields, dunes, and landslides, as well as investigating the influence of different roughness thresholds, resolutions of kernels, and input data resolution, and comparing our method with previously published roughness algorithms. Our results show that total curvature is a suitable metric for recognising analysed gullies and lava fields from LiDAR data, with comparable success to that of more sophisticated roughness metrics. Tested dunes or landslides remain difficult to distinguish from the surrounding landscape, partly because they are not easily defined in terms of their topographic signature.

Benthic habitat mapping is a rapidly growing field of underwater remote sensing studies. This study provides the first insight for high-resolution hydroacoustic surveys in the Slupsk Bank Natura 2000 site, one of the most valuable sites in the Polish Exclusive Zone of the Southern Baltic. This study developed a quick and transparent, automatic classification workflow based on multibeam echosounder and side-scan sonar surveys to classify benthic habitats in eight study sites within the Slupsk Bank. Different predictor variables, four supervised classifiers, and the generalisation approach, improving the accuracy of the developed model were evaluated. The results suggested a very high significance for the classification performance of specific geomorphometric features that were not used in benthic habitat mapping before. These include, e.g., Fuzzy Landform Element Classification, Multiresolution Index of the Valley Bottom Flatness, and Multiresolution Index of the Ridge Top Flatness. Comparison of classification results with manual maps demonstrated that Random Forest had the highest performance of four tested supervised classifiers. Because the current needs include benthic habitat mapping for the whole area of the Polish Exclusive Economic Zone, the key findings of this study may be further applied to extensive areas in the Polish waters and other vast areas worldwide.

Data-driven GIScience shows a growing interest in making spatial information from large text data. In this paper, we quantify and thus evaluate the relation between text frequency and properties of the outer-text, geographic setting by comparing text frequencies of mountain names to the respective geomorphometric characteristics. We focus on some 2000 unique mountain names that appear some 50,000 times in a large compilation of texts on Swiss alpine history. The results on the full data set suggest only a weak relation: only 5–10% of the variation in the text frequency being explained by the respective geomorphometric characteristics. However, an analysis of multiple scales allows us to identify a Simpson’s Paradox. What appears to be ‘noise’ in the analysis of all mountains in the whole of Switzerland shows significant local signals. Small spatial extents, found all over Switzerland, can show considerably strong correlations between text frequency and spatial prominence, with up to 90% of the tot...

Barrier islands exhibit a range of landforms that reflect the complex and varied combination of coastal and aeolian processes realized over the evolution of the island. A detailed analysis of the topography can be used to describe the evolution of a barrier island and provide insight on how it may be affected by a change in sea level, storm activity and wind exposure patterns. Topographic anisotropy, or the directional dependence of relief of landforms, can be used to determine the relative importance of different processes to island evolution at a range of scales. This short communication describes the use of scale-dependent topographic anisotropy to characterize the structure of Santa Rosa Island in northwest Florida. Scale-dependent topographic relief and asymmetry were assessed from a LiDAR-derived DEM from May 2004, a few months before the island experienced widespread erosion and overwash during Hurricane Ivan. This application demonstrates how anisotropy can be used to identify unique scale-dependent structures that can be used to interpret the evolution of this barrier island. Results of this preliminary study further highlight the potential of using topographic anisotropy to controls on barrier island response and recovery to storms as well as island resiliency with sea level rise and storm activity.

Geomorphometry, the science of digital terrain analysis (DTA), is an important focus of research in both geomorphology and geographical information science (GIS). Given that 70% of China is mountainous, geomorphological research is popular among Chinese scholars, and the development of GIS over the last 30 years has led to significant advances in geomorphometric research. In this paper, we review Chinese progress in geomorphometry based on the published literature. There are three major areas of progress: digital terrain modelling methods, DTA methods, and applications of digital terrain models (DTMs). First, traditional vector- and raster-based terrain modelling methods, including the assessment of uncertainty, have received widespread attention. New terrain modelling methods such as unified raster and vector, high-fidelity, and real-time dynamic geographical scene modelling have also attracted research attention and are now a major focus of digital terrain modelling research. Second, in addition to the popular DTA methods based on topographical derivatives, geomorphological features, and hydrological factors extracted from DTMs, DTA methods have been extended to include analyses of the structure of underlying strata, ocean surface features and even socioeconomic spatial structures. Third, DTMs have been applied to fields including global climate change, analysis of various typical regions, lunar surface and other related fields. Clearly, Chinese scholars have made significant progress in geomorphometry. Chinese scholars have had the greatest international impact in areas including high-fidelity digital terrain modelling and DTM-based regional geomorphological analysis, particularly in the Loess Plateau and the Tibetan Plateau regions.

The aim of this study was to introduce a new morphometric index named Relief Index (RI). RI is the ratio of the total length of the contour lines and the surface area at which they occur. This easily calculated index provides an objective quantitative measure of relief variability as an important feature in geomorphological studies. To achieve this goal, a highly detailed morphometric analysis was carried out using a high-resolution (1m×1m) DEM. Twenty one sample areas in southern Poland were examined. These analyses showed RI, as a good tool for rapidly evaluating topography heterogeneity in division into relief classes. I distinguished 4 classes of the Relief Index that classify earth surface considering the variability of the relief. Results of the calculations demonstrated that there is a significant correlation between RI and the local relief and slopes, but there is no correlation between RI and planar curvatures and TWI. The relief of the sample areas were analysed using geomorphometric parameters (slopes, local relief, planar curvatures). Moreover the influence of the DEM resolution on Relief Index values was examined.

The geomorphometric classifications of three groups of volcanoes situated in the Andes Cordillera, Central America, and Mexico are performed and compared. Input data are eight local topographic gradients (i.e. elevation differences) obtained by processing each volcano raster ASTER-GDEM data. The pixels of each volcano DEM have been classified into 17 classes through a K-means clustering procedure following principal component analysis of the gradients. The spatial distribution of the classes, representing homogeneous terrain units, is shown on thematic colour maps, where colours are assigned according to mean slope and aspect class values. The interpretation of the geomorphometric classification of the volcanoes is based on the statistics of both gradients and morphometric parameters (slope, aspect and elevation). The latter were used for a comparison of the volcanoes, performed through classes' slope/aspect scatterplots and multidimensional methods. In this paper, we apply the mentioned methodology on 21 volcanoes, randomly chosen from Mexico to Patagonia, to show how it may contribute to detect geomorphological similarities and differences among them. As such, both its descriptive and graphical abilities may be a useful complement to future volcanological studies.

Alluvial fan and bajada mapping is important for practical and economic importance to society. In this study, advanced geomorphometric, image processing and knowledge representation methods were investigated, enhanced and developed, towards the simultaneous identification of alluvial fans and bajadas. The developed method was based on the landform-pattern element approach. Data used included the 10 m spatial resolution National Elevation Dataset, provided by USGS and a pan-sharpened 15 m Landsat OLi imagery. The study area was located in the Death Valley, Nevada, USA. Digital Terrain Model (DTM) processing included noise-removal filtering and depression treatment. A two-phase GEographic Object-Based Image Analysis approach involving multi-scale segmentation and fuzzy ontology-based reasoning was designed. On the first phase, topographic forms were identified, by examining their morphometry and spatial relationships. On the second phase, the alluvial fans and bajadas were identified based on draina...