Landform Classification Research Articles

Classification of snow valanche landform

Classification of snow valanche landform

Water erosion susceptibility mapping by applying Stochastic Gradient Treeboost to the Imera Meridionale River Basin (Sicily, Italy)

Soil erosion by water constitutes a serious problem affecting various countries. In the last few years, a number of studies have adopted statistical approaches for erosion susceptibility zonation. In this study, the Stochastic Gradient Treeboost (SGT) was tested as a multivariate statistical tool for exploring, analyzing and predicting the spatial occurrence of rill–interrill erosion and gully erosion. This technique implements the stochastic gradient boosting algorithm with a tree-based method. The study area is a 9.5km2 river catchment located in central-northern Sicily (Italy), where water erosion processes are prevalent, and affect the agricultural productivity of local communities. In order to model soil erosion by water, the spatial distribution of landforms due to rill–interrill and gully erosion was mapped and 12 environmental variables were selected as predictors. Four calibration and four validation subsets were obtained by randomly extracting sets of negative cases, both for rill–interrill erosion and gully erosion models. The results of validation, based on receiving operating characteristic (ROC) curves, showed excellent to outstanding accuracies of the models, and thus a high prediction skill. Moreover, SGT allowed us to explore the relationships between erosion landforms and predictors. A different suite of predictor variables was found to be important for the two models. Elevation, aspect, landform classification and land-use are the main controlling factors for rill–interrill erosion, whilst the stream power index, plan curvature and the topographic wetness index were the most important independent variables for gullies. Finally, an ROC plot analysis made it possible to define a threshold value to classify cells according to the presence/absence of the two erosion processes. Hence, by heuristically combining the resulting rill–interrill erosion and gully erosion susceptibility maps, an integrated water erosion susceptibility map was created. The adopted method offers the advantages of an objective and repeatable procedure, whose result is useful for local administrators to identify the areas that are most susceptible to water erosion and best allocate resources for soil conservation strategies.

Relationship between landform and soil salinity in the surface and subsurface soils (case study: Southeast of Fars Province, Iran)

Forty surface and subsurface soil samples were collected from agricultural field of Darab, southern Iran. Some physicochemical properties and also EC were determined. Geostatistical analysis was done by using the Kriging method (including ordinary, simple, universal, indicator, probability and disjunctive models) in ArcGIS 10.2 software. The results of stepwise multiple regressions indicate that in the surface and subsurface soils, sand and silt contents respectively are the most influential soil characteristics that predict EC. The root mean square error (RMSE) analysis of the different models indicated that indicator model with RMSE value of 0.518 and probability model with RMSE 0.509 are the best models for the description of the spatial distribution of EC in the surface and subsurface soils, respectively. Finally, for determination of accuracy of the best models (indicator and probability models) in surface and subsurface soils, 10 sample points were used. The RMSE values for EC in the surface and subsurface soils were calculated 0.476 and 0.349, respectively. It is recommended that other interpolation methods such as co-Kriging and soil properties such as CEC and SAR are used in order to prepare precision maps in the future. Finally the relationship between landform classes and EC values were determined by using topography position index. The results show that the high EC value was shown in plain small for subsurface soil and surface soil in the study area. While the low EC value was seen in mountain top and stream for subsurface soil and surface soil that was indicative leaching of the soil.

Semi-automatic classification of glaciovolcanic landforms: An object-based mapping approach based on geomorphometry

A new object-oriented approach is developed to classify glaciovolcanic landforms (Procedure A) and their landform elements boundaries (Procedure B). It utilizes the principle that glaciovolcanic edifices are geomorphometrically distinct from lava shields and plains (Pedersen and Grosse, 2014), and the approach is tested on data from Reykjanes Peninsula, Iceland. The outlined procedures utilize slope and profile curvature attribute maps (20m/pixel) and the classified results are evaluated quantitatively through error matrix maps (Procedure A) and visual inspection (Procedure B). In procedure A, the highest obtained accuracy is 94.1%, but even simple mapping procedures provide good results (>90% accuracy). Successful classification of glaciovolcanic landform element boundaries (Procedure B) is also achieved and this technique has the potential to delineate the transition from intraglacial to subaerial volcanic activity in orthographic view.This object-oriented approach based on geomorphometry overcomes issues with vegetation cover, which has been typically problematic for classification schemes utilizing spectral data. Furthermore, it handles complex edifice outlines well and is easily incorporated into a GIS environment, where results can be edited or fused with other mapping results. The approach outlined here is designed to map glaciovolcanic edifices within the Icelandic neovolcanic zone but may also be applied to similar subaerial or submarine volcanic settings, where steep volcanic edifices are surrounded by flat plains.

Relationship between landform classification and vegetation (case study: southwest of Fars province, Iran)

AbstractThis study is aimed at investigating the relationship between landform classification and vegetation in the southwest of Fars province, Iran. First, topographic position index (TPI) is used to perform landform classification using a Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) with resolution of 30 m. The classification has ten classes; high ridges, midslope ridges, upland drainage, upper slopes, open slopes, plains, valleys, local ridges, midslope drainage and streams. Visual interpretation indicates that for the local, midslope and high ridge landforms, normalized difference vegetation index (NDVI) values and tree heights are higher as compared to the other landforms. In addition, it is found that there are positive and significant correlations betweenNDVI and tree height (

Development and validation of MK-PRISM-Wind for wind speed interpolation

MK-PRISM developed for wind interpolation was applied to case studies and was verified in previous studies. Thus, some tests were necessary before the model used in order to produce wind speed maps for the whole area of South Korea. In this study, the MK-PRISM was applied to producing wind speed maps of South Korea. The result showed that sharp changes occur in wind speed distribution, despite the continuous similar topographic. The primary reason for the phenomenon was that a linear regression slope between elevation and wind speed used in interpolation process was changed rapidly in some areas. This study used the landform classification data to address this problem. The improved model controlled similarly the slope of the linear regression equation in the continuous valley, slope, and ridge. Therefore, the slope of the linear regression equation does not change dramatically in the improved model. The improved model was named MK-PRISM-Wind in this study. The wind speed was similar on the ridge continuously in the wind speed distribution produced by MK-PRISM-Wind. In addition, the wind speed was more gradually changed compared to the previous model on the plains and foothills. The results mean that MK-PRISM-Wind can produce wind speed maps more reasonable than the previous model, and it can be applied to the wind speed interpolation of South Korea. High-resolution gridded wind speed map produced by MK-PRISM-Wind is expected to be utilized for various studies.

Ecologically-Relevant Maps of Landforms and Physiographic Diversity for Climate Adaptation Planning.

Key to understanding the implications of climate and land use change on biodiversity and natural resources is to incorporate the physiographic platform on which changes in ecological systems unfold. Here, we advance a detailed classification and high-resolution map of physiography, built by combining landforms and lithology (soil parent material) at multiple spatial scales. We used only relatively static abiotic variables (i.e., excluded climatic and biotic factors) to prevent confounding current ecological patterns and processes with enduring landscape features, and to make the physiographic classification more interpretable for climate adaptation planning. We generated novel spatial databases for 15 landform and 269 physiographic types across the conterminous United States of America. We examined their potential use by natural resource managers by placing them within a contemporary climate change adaptation framework, and found our physiographic databases could play key roles in four of seven general adaptation strategies. We also calculated correlations with common empirical measures of biodiversity to examine the degree to which the physiographic setting explains various aspects of current biodiversity patterns. Additionally, we evaluated the relationship between landform diversity and measures of climate change to explore how changes may unfold across a geophysical template. We found landform types are particularly sensitive to spatial scale, and so we recommend using high-resolution datasets when possible, as well as generating metrics using multiple neighborhood sizes to both minimize and characterize potential unknown biases. We illustrate how our work can inform current strategies for climate change adaptation. The analytical framework and classification of landforms and parent material are easily extendable to other geographies and may be used to promote climate change adaptation in other settings.

Landform classification using topography position index (case study: salt dome of Korsia-Darab plain, Iran)

In the research aim is to evaluate the Jennes algorithm for landform classification in salt dome of Korsia of Darab plain, Iran. The Jennes’s approach uses a multi-scale approach by fitting a quadratic polynomial to a given window size using least squares. In the study used window size of 3*3 and 10*10. Input data for landform classification is digital elevation model (DEM) with resolution of 30 m. After prepared landform classification map for the study area, used geology map. The results show that the evaluated method can be helpful in the predictive mapping of geology. The algorithm of landforms classification proposed by Jennes seem to be the most applicable method.

LiDAR DEM detection and classification of postglacial faults and seismically-induced landforms in Finland: a paleoseismic database

During the last decades, postglacial faults (PGFs) have been found in northern Fennoscandia, the first fault scarps being discovered in western Finnish Lapland in the 1960s. With LiDAR-based digital elevation models (DEMs), a new and accurate remote sensing mapping methodology has been acquired. It allows the relatively rapid and low-cost detection and mapping of late- or PGFs and, for instance, mapping of landslides from areas where they have not previously been recognized. We describe the approach of the Geological Survey of Finland to the systematic search for (screening) and mapping of PGFs, paleolandslides, and other morphological features of Quaternary deposits related to post- and late-glacial seismic activity in Finland. The observations have been collected and classified into a file geodatabase with ArcGis (© ESRI) using a procedure that includes several steps. We also provide examples from western and northern Finland of how sites of late- and postglacial fault scarps and landslides have been detected and described from LiDAR DEM data.

Pathways of geomorphic evolution of sandstone escarpments in the Góry Stołowe tableland (SW Poland) — Insights from LiDAR-based high-resolution DEM

The tableland of the Stołowe Mountains (SW Poland), with its prominent mesas and sandstone-capped escarpments, belongs to the most spectacular geomorphic landscapes of Central Europe. While the gross morphological features of the area have long been recognized, the evolutionary pathways of densely forested and poorly accessible escarpment slopes remained poorly understood. In this paper we use LiDAR data to shed a new light on landform inventories within the escarpments, their spatial patterns and, using process–from–form reasoning, on the longer-term evolution of the escarpments. Four sites, two on each major escarpment, have been subject to detailed analysis which involved examination of shaded relief, slope, plan and profile curvature and topographic wetness index. In each case, the 1×1m model was used, while for the most complex site at Mt. Szczeliniec Wielki the results were compared with the 5×5m model to check the impact of model resolution on geomorphic interpretation. Despite some loss of information involved in model re-interpolation to the coarser scale, the main features of escarpment morphology could still be recognized. On the other hand, automatic landform classification based on the calculation of Topographic Position Index from the 10×10m model and performed for the entire tableland failed to reveal differences between various sections of the escarpments, detectable on finer models. The analysis of spatial patterns of minor landforms within the escarpments, identified on LiDAR-derived models shows that no single pathway of escarpment evolution exists. Both the upper slopes (in sandstone caprock) and the mid-slopes (in weaker rocks) show signs of instability and these are not necessarily coupled. Large-scale caprock failures do occur but seem rare and localized. Sandstone free faces are rather subject to continuous slow retreat by detachment of individual joint-bound blocks. Another zone of instability occurs well below the caprock and the dominant processes are shallow landslips initiated within weak, deformable rocks.

CHARACTERISTICS OF BEDROCK LANDFORMS IN THE MOUNTAIN AND SEMI-MOUNTAIN VALLEYS

A particular class of channel landforms is described. It is represented by sculptured-erosion forms, created by channel flow cutting into bedrock of mountain and semi-mountain rivers. The main types of this landform class, their changes along the valley, and their dependence on channel type and lithology are considered.

Geomorphic mapping and taxonomy of fluvial landforms

Fluvial geomorphologists use close to a 100 different terms to describe the landforms that make up riverscapes. We identified 68 of these existing terms that describe truly distinctive landforms, in which form is maintained under characteristic conditions and fluvial processes. Clear topographic definitions for these landforms to consistently identify and map them are lacking. With the explosion of continuous, high-resolution topography and digital elevation models, we have plenty of new basemaps in which these landforms are clearly visible, but very few examples of manual or automated classification of fluvial landforms. Fluvial landforms are the building blocks of a river and are variously referred to as geomorphic units, morphological units, habitat units, and channel units. We present a tiered framework for describing geomorphic units, with tier 1 differentiating units on the basis of their stage, tier 2 separating shape (e.g., concave, convex, or planar), tier 3 using particular key attributes to narrow in on the likely specific geomorphic unit type, and tier 4 differentiating those types on the basis of vegetative or roughness modifiers. Information on the assemblage and configuration of geomorphic units can be used to inform process-based interpretations of the range of river behavior. The accuracy and transferability of such analyses is fundamentally tied to the taxonomy we assign to these discrete building blocks. In this paper we clarify the terminology and definitions relating to the identification and delineation of geomorphic units, margins, and structural elements. We establish a set of procedures that can be used to manually map and identify these features. The proposed framework provides a rigorous and repeatable approach to identification of topographically defined features of riverscapes. We demonstrate the application of these systematic yet flexible procedures with a series of maps from rivers in differing valley settings.

Reconciling Precariously Balanced Rocks (PBRs) with Large Earthquakes on the San Andreas Fault System

Research Article| August 05, 2015 Reconciling Precariously Balanced Rocks (PBRs) with Large Earthquakes on the San Andreas Fault System Lisa Grant Ludwig; Lisa Grant Ludwig aProgram in Public Health, University of California Irvine, 2085 AIRB, 653 East Peltason Drive, Irvine, California 92697‐3957 U.S.A.lgrant@uci.edu Search for other works by this author on: GSW Google Scholar James N. Brune; James N. Brune bSeismological Laboratory, University of Nevada Reno, Reno, Nevada 89557 U.S.A. Search for other works by this author on: GSW Google Scholar Abdolrasool Anooshehpoor; Abdolrasool Anooshehpoor cU.S. Nuclear Regulatory Commission, MS C5A24M, Washington, D.C. 20555‐0001 U.S.A. Search for other works by this author on: GSW Google Scholar Matthew D. Purvance; Matthew D. Purvance dItasca Consulting Group, 111 Third Avenue South, Suite 450, Minneapolis, Minnesota 55401 U.S.A. Search for other works by this author on: GSW Google Scholar Richard J. Brune; Richard J. Brune e3107 Murray Lane, Costa Mesa, California 92626‐2735 U.S.A. Search for other works by this author on: GSW Google Scholar Julian C. Lozos Julian C. Lozos fDepartment of Geophysics, Stanford University, 397 Panama Mall, Stanford, California 94305 U.S.A. Search for other works by this author on: GSW Google Scholar Author and Article Information Lisa Grant Ludwig aProgram in Public Health, University of California Irvine, 2085 AIRB, 653 East Peltason Drive, Irvine, California 92697‐3957 U.S.A.lgrant@uci.edu James N. Brune bSeismological Laboratory, University of Nevada Reno, Reno, Nevada 89557 U.S.A. Abdolrasool Anooshehpoor cU.S. Nuclear Regulatory Commission, MS C5A24M, Washington, D.C. 20555‐0001 U.S.A. Matthew D. Purvance dItasca Consulting Group, 111 Third Avenue South, Suite 450, Minneapolis, Minnesota 55401 U.S.A. Richard J. Brune e3107 Murray Lane, Costa Mesa, California 92626‐2735 U.S.A. Julian C. Lozos fDepartment of Geophysics, Stanford University, 397 Panama Mall, Stanford, California 94305 U.S.A. Publisher: Seismological Society of America First Online: 14 Jul 2017 Online ISSN: 1938-2057 Print ISSN: 0895-0695 © 2015 by the Seismological Society of America Seismological Research Letters (2015) 86 (5): 1345–1353. https://doi.org/10.1785/0220140239 Article history First Online: 14 Jul 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Lisa Grant Ludwig, James N. Brune, Abdolrasool Anooshehpoor, Matthew D. Purvance, Richard J. Brune, Julian C. Lozos; Reconciling Precariously Balanced Rocks (PBRs) with Large Earthquakes on the San Andreas Fault System. Seismological Research Letters 2015;; 86 (5): 1345–1353. doi: https://doi.org/10.1785/0220140239 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietySeismological Research Letters Search Advanced Search A major goal of seismology is to predict earthquake shaking (Frankel, 1999). Earthquakes are generated by rupture of faults, but it is difficult to predict the endpoints of fault rupture (Wesnousky, 2006) and the ground motions that will likely be produced. Precariously balanced rocks (PBRs) are a class of fragile landforms that are susceptible to toppling by earthquakes (Brune, 1996). PBRs have been reported to exist in many areas, including seismically active regions of the United States and New Zealand (Stirling and Anooshehpoor, 2006; Anderson et al., 2011). The population... You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

English

In this research, landform classification was performed based on the simple method developed by Weise, who used topographic position index (TPI) to classify the landform. TPI compares the elevation of each cell in a digital elevation model (DEM) to the mean elevation of a specified neighborhood around that cell. It can be calculated by a simple formula in different scales. After preparing landform map of the study area, soil sampling and physicochemical analysis were done in landforms which had the most repeatability in the region (plain and open slope). Results showed that transferring of parent material from the upper geomorphic surfaces and accumulating during the time are the main agents to form the plain and in case of open slope, moderately high slope changes with erodible parent materials that have varied over time, are the main parameters in landform formation.   Key words: Digital elevation model, geomorphic surfaces, geomorphology, landscape, topography.

Landform classification for community siting: A case study in Quxian county, China

This study is to explore a suitable method to classify landform, in order to support the decision making for community siting in mountainous areas. It first proposes the landform classification for community siting (LCCS) method with detailed discussions on its rationality and the chosen parameters. This method is then tested and verified in Quxian county. The LCCS method entails two-grade parameters, which uses relative relief as the first grading parameter, slope as the second, followed by a synthesis process to form a suitable landform classification system. By applying the LCCS method in Quxian county, the result shows that its use of watershed to identify geomorphometric units, and its use of the altitude datum concept, can effectively classify landform according to the local cultural traditions, and the economic and environmental conditions. The verification result shows that comparing to the conventional methods, the LCCS method respects to people’s daily experience due to its bottom-up approach. It not only help to minimize the disturbance to the nature when choosing locations for community development, but also helps to prepare more precise land management policies, which maximizes agricultural production and minimizes terrain transformation.

Terrestrial laser scanning to deliver high-resolution topography of the upper Tarfala valley, arctic Sweden

Alpine valleys are experiencing rapidly changing physical, biological and geochemical processes as glacier masses diminish, snowfall patterns change and consequently as hillslopes and valley-floor landforms and sediments adjust. Measurement and understanding of these processes on a valley, landform and surface scale requires topographic data with sufficient spatial coverage and spatial resolution to resolve sources, fluxes and storages of sediment. Most ideally such topographic data will be of a resolution sufficient to resolve important spatial heterogeneity in land cover, topography and surface texture, for example. This study presents the first high-resolution (1 m grid cell size) and freely available topography for the upper part of the Tarfala valley, arctic Sweden. The topography was obtained using terrestrial laser scanning and a bespoke workflow is presented to most efficiently cover a 9.3 km2 area. The unprecedented spatial resolution of this topography, which is 15 times greater than that previously available, reveals a suite of alpine landforms. These landforms span multiple glacier forefields, a variety of bedrock surfaces, various hillslopes and types of mass movement, and valley floor glacial, fluvial and periglacial sediments, for example. Primary and second-order derivatives of this elevation data, and vertical transects are given and will assist future classification of landforms and thus assist future targeted field campaigns. Overall, this study presents (1) baseline data from which future re-surveys will enable quantitative analysis of a dynamic landscape, and (2) an efficient workflow that is readily transferable to any scientific study at any other site. Both of these project outputs will find widespread usage in future alpine studies.

Seabed morphology and sedimentary processes on high-gradient trough mouth fans offshore Troms, northern Norway

Trough mouth fans (TMF) situated at the mouths of formerly glaciated cross-shelf troughs are important paleoclimatic archives. Whereas the sedimentary processes of large, low-gradient TMFs have received considerable interest, little attention has been paid to the other end member of this landform class, i.e. TMFs with higher slope gradients. Detailed swath-bathymetric data and seismic profiles from the continental margin offshore Troms, northern Norway cover three high-gradient TMFs (the Andfjorden, Malangsdjupet and Rebbenesdjupet TMFs; slope gradients generally between 1° and 15°), as well as inter-fan areas, which include two submarine canyons (the Andøya and Senja Canyon) and the Malangsgrunnen inter-fan slope. The present-day morphologies of the Andfjorden and Malangsdjupet TMFs have evolved from sediment transport and distribution through gully-channel complexes. The Andfjorden TMF has later been affected by a large submarine landslide that remobilized much of these complexes. The Rebbenesdjupet TMF is dominated by a number of small and relatively shallow slide scars, which are inferred to be related to small-scale sediment failure of glaciomarine and/or contouritic sediments. The canyons cut into the adjacent TMFs, and turbidity currents originating on the fans widened and deepened the canyons during downslope flow. The Malangsgrunnen shelf break and inter-fan slope acted as a funnel for turbidity currents originating on the upper slope, forming a dendritic pattern of gullies. A conceptual model for the high-gradient TMFs on the Troms margin has been compiled. The main sediment input onto the TMFs has occurred during peak glacials when the Fennoscandian Ice Sheet reached the shelf edge. The overall convex fan form and progradational seismic facies show that these glacigenic deposits were repeatedly distributed onto the fan. On the Andfjorden and Malangsdjupet TMFs, gully-channel complexes occur within such deposits. It is thus inferred that the steep slope of these TMFs promoted rapid transformation from small-scale slumps and debris flows on the upper slope, into partly erosive turbidity currents. These flows continued into the deep sea, thus promoting efficient sediment by-pass across the TMFs. This model can be applied to other TMFs situated at the mouths of other glaciated cross-shelf troughs. In contrast, low-gradient TMFs are found to be dominated by glacigenic debris flow deposits. Furthermore, gully-channel complexes demonstrating the presence of erosive turbidity currents on high-gradient TMFs are rare on low-gradient TMFs. Large submarine landslides occur at both high- and low-gradient TMFs.

An integral image approach to performing multi-scale topographic position analysis

Digital elevation model (DEM) derived measures of terrain ruggedness and relative topographic position are useful parameters for automated landform classification and are widely applied in soils, vegetation, and habitat mapping. These elevation residual attributes are inherently scale dependent because they are defined in the context of a local neighborhood. Several previous studies have focused on assessing the multi-scale properties of elevation residuals based on varying roving window sizes, DEM grid resolution resampling, and hierarchical object-based methods. The computationally intensive nature of large-window DEM filtering has previously prevented the application of the varying roving window size approach from being applied to study the scaling properties of the terrain ruggedness and topographic position at broader regional scales.This paper explores the use of an integral image based approach to measuring the common relative topographic position metric deviation from mean elevation (DEV). The approach was applied to a large DEM of an extensive and heterogeneous region in eastern North America. Compared with traditional image filtering techniques, the integral image approach was extremely efficient for calculating DEV, enabling a fine-resolution multi-scale analysis of elevation residuals. A method is described to allow for the measurement of DEV at optimal scales for each grid cell within wide spatial scale ranges. A novel technique is also developed for visualizing the scaling characteristics of topographic position using color composite imagery.

Landslide detection and susceptibility mapping using LiDAR and an artificial neural network approach: a case study in the Cuyahoga Valley National Park, Ohio

The purpose of this study was to detect shallow landslides using hillshade maps derived from light detection and ranging (LiDAR)-based digital elevation model (DEM) derivatives. The landslide susceptibility mapping used an artificial neural network (ANN) approach and backpropagation method that was tested in the northern portion of the Cuyahoga Valley National Park (CVNP) located in northeast Ohio. The relationship between landslides and predictor attributes, which describe landform classes using slope, profile and plan curvatures, upslope drainage area, annual solar radiation, and wetness index, was extracted from LiDAR-based DEM using geographic information system (GIS). The approach presented in this paper required a training study area for the development of the susceptibility model and a validation study area to test the model. The results from the validation showed that within the very high susceptibility class, a total of 42.6 % of known landslides that were associated with 1.56 % of total area were correctly predicted. In contrast, the very low susceptibility class that represented 82.68 % of the total area was associated with 1.20 % of known landslides. The results suggest that the majority of the known landslides occur within a small portion of the study area, consistent with field investigation and other studies. Sample probabilistic maps of landslide susceptibility potential and other products from this approach are summarized and presented for visualization to help park officials in effective management and planning.

Classification of landforms in Southern Portugal (Ria Formosa Basin)

A Geographic Information Systems-based tool is used for macro-landform classification following the Hammond procedure, based upon a Digital Terrain Model (DTM) created from ordinary Kriging. Gentle slopes, surface curvature, highlands and lowlands areas are derived from the DTM. Combining this information allows the classification of terrain units (landforms). The procedure is applied to the Ria Formosa basin (Southern Portugal), with five different terrain types classified (plains, tablelands, plains with hills, open hills and hills).