High-resolution Digital Terrain Models Research Articles

Assessment of Image-Based Point Cloud Products to Generate a Bare Earth Surface and Estimate Canopy Heights in a Woodland Ecosystem

We examine the utility of Structure from Motion (SfM) point cloud products to generate a digital terrain model (DTM) and estimate canopy heights in a woodland ecosystem in the Texas Hill Country, USA. Very high spatial resolution images were acquired with a Canon PowerShot A800 digital camera mounted on an unmanned aerial system. Image mosaicking and dense point matching were accomplished using Agisoft PhotoScan. The resulting point cloud was classified according to ground/non-ground classes and used to interpolate a high resolution DTM which was both compared to a DTM from an existing lidar dataset and used to model vegetation height for fifteen 20 × 20 m plots. Differences in the interpolated DTM surfaces demonstrate that the SfM surface overestimates lidar-modeled ground height with a mean difference of 0.19 m and standard deviation of 0.66 m. Height estimates obtained solely from SfM products were successful with R2 values of 0.91, 0.90, and 0.89 for mean, median, and maximum canopy height, respectively. Use of the lidar DTM in the analyses resulted in R2 values of 0.90, 0.89, and 0.89 for mean, median, and maximum canopy height. Our results suggest that SfM-derived point cloud products function as well as lidar data for estimating vegetation canopy height for our specific study area.

English

During the implementation of the EU Flood directive, high resolution (Lidar) digital terrain models (DTM) were produced massively on nearly all the French coast. With those date, the methods used to map sea flooding on the Mediterranean coast were the simple superposition of a sea level on the natural terrain. The methods currently implementing allow, comparing the previous results and the areas actually connected to the sea for a given level, to determine the protected area for this level. The next step is to determine, where appropriate, the protection system. The algorithm developed for this purpose can locate it and determine its level of protection.

Flood protection structure detection with Lidar: examples on French Mediterranean rivers and coastal areas

This paper aims at presenting different topographic analysis conducted with GIS software in order to detect flood protection structures, natural or artificial, in river floodplains but also in coastal zones. Those computations are relevant because of the availability of high-resolution lidar digital terrain model (DTM). An automatic detection permits to map the footprint of those structures. Then detailed mapping of structure crest is achieved by implementing a least cost path analysis on DTM but also on other terrain aspects such as the curvature. On coastal zones, the analysis is going further by identifying flood protected areas and the level of protection regarding sea level. This article is illustrated by examples on French Mediterranean rivers and coastal areas.

Micro Hydro Potential Modelling: Integrating GIS into Energy Alternatives for Climate Change Mitigation

This research focused on integrating GIS into energy alternatives for climate change mitigation by creating a GIS-based hydrologic model that can be used to identify sites that have significant potential for micro hydropower development within the River Perkerra catchment area. Hydropower is a clean and renewable energy source that remains largely untapped in the country and its development can be used to mitigate anthropogenic climate change by reducing reliance on fossil or biomass derived fuels. This research established the extent of this resource and whether the available sites with significant micro hydropower potential within the study area were amply copious to warrant further development. Currently, such identification is done physically using means that are menial, costly and significantly time consuming. A 90-metre resolution Digital Terrain Model (DTM) data obtained from the Shuttle Radar Topography Mission and various GIS tools were used to create a hydrologic framework which was used to identify potential sites along River Perkerra that suited any desired head requirement for the purposes of locating micro hydropower plants. The derived model demonstrated that it was possible to identify sites at discrete geographic locations along any stream drainage network using GIS. In addition, the model also provides a decision support system that integrates a powerful graphical user interface, spatial database management system and a generalized river basin network flow model for the purposes of exploiting and developing micro hydropower. With sufficient data on catchment discharge and use of higher resolution DTM, the model can be further enhanced to accurately obtain the total microhydro potential of River Perkerra by aggregating the respective potentials of every steam segment.

Coupling scenarios of urban growth and flood hazards along the Emilia-Romagna coast (Italy)

Abstract. The extent of coastline urbanization reduces their resilience to flooding, especially in low-lying areas. The study site is the coastline of the Emilia-Romagna region (Italy), historically affected by marine storms and floods. The main aim of this study is to investigate the vulnerability of this coastal area to marine flooding by considering the dynamics of the forcing component (total water level) and the dynamics of the receptor (urban areas). This was done by comparing the output of the three flooding scenarios (10, 100 and > 100 year return periods) to the output of different scenarios of future urban growth up to 2050. Scenario-based marine flooding extents were derived by applying the Cost–Distance tool of ArcGIS® to a high-resolution digital terrain model. Three scenarios of urban growth (similar-to-historic, compact and sprawled) up to 2050 were estimated by applying the cellular automata-based SLEUTH model. The results show that if the urban growth progresses compactly, flood-prone areas will largely increase with respect to similar-to-historic and sprawled growth scenarios. Combining the two methodologies can be useful for identification of flood-prone areas that have a high potential for future urbanization, and is therefore crucial for coastal managers and planners.

Micro-topography driven vegetation patterns in open mosaic landscapes

Elevation models based on remotely sensed data, especially high-resolution Digital Terrain Models (DTMs) generated using airborne laser scanner (ALS) data, are increasingly being used for the analysis of plant diversity patterns in open landscapes. The vegetation pattern of alkali landscapes shows a high correlation with the position of water table and salt accumulation, which are strongly correlated with topographic variations occurring at a small spatial scale of a few decimetres (micro-topography). In this study we classified eight grassland associations in an alkali landscape based on a DTM generated from ALS data at a pixel size of 0.25m, and 30 variables derived from the DTM, using an ensemble learning method (Random Forest). Our aim was to identify the micro-topographic variables which could be indicators of vegetation pattern in alkali landscapes. The associations range from Cynodon pastures (short dry grasslands on soil with low salt content) occupying the highest elevations to Beckmannia meadows (wet grasslands on soils with moderate salt content composed of tall grass species) at the lowest elevations, with an elevation difference of approximately 1.2m between the two. Apart from slope, aspect and curvature, we used Topographic Wetness Index (TWI), and Topographic Position Indices (TPI) at various kernel sizes ranging from 50cm to 500m for the classification. The eight associations were also grouped into four aggregated categories — loess grasslands, alkali steppes, open alkali swards and alkali meadows — for further analysis. Vegetation of the studied alkali landscape could be classified into the eight associations with an accuracy of κ: 0.56, and into the four aggregated categories with an accuracy of κ: 0.77 using all the variables. Sequential backward and forward selections of variables were implemented to reduce the number of variables while maximising the accuracies, resulting in increased accuracies of κ: 0.72 and κ: 0.83 for the associations and aggregated categories using six and three variables respectively. TPI at different kernel sizes, previously used to explain vegetation distribution in mountainous areas, was found to be a better indicator of vegetation types than absolute elevations in lowlands where the elevation differences are more subtle. Two characteristic features of the study area — erosional channels and alkali steps — could also be delineated using micro-topographic variables. The results point to the possibility of large-area mapping and monitoring of grasslands where micro-topography is an indicator of vegetation, using only the elevation data from ALS.

Estimation of Forest Biomass From Two-Level Model Inversion of Single-Pass InSAR Data

A model for aboveground biomass estimation from single-pass interferometric synthetic aperture radar (InSAR) data is presented. Forest height and canopy density estimates Δh and η <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> , respectively, obtained from two-level model (TLM) inversion, are used as biomass predictors. Eighteen bistatic VV-polarized TanDEM-X (TDM) acquisitions are used, made over two Swedish test sites in the summers of 2011, 2012, and 2013 (nominal incidence angle: 41°; height-of-ambiguity: 32-63 m) . Remningstorp features a hemiboreal forest in southern Sweden, with flat topography and where 32 circular plots have been sampled between 2010 and 2011 (area: 0.5 ha; biomass: 42-242 t/ha; height: 14-32 m) . Krycklan features a boreal forest in northern Sweden, 720-km north-northeast from Remningstorp, with significant topography and where 31 stands have been sampled in 2008 (area: 2.4-26.3 ha; biomass: 23-183 t/ha; height: 7-21 m) . A high-resolution digital terrain model has been used as ground reference during InSAR processing. For the aforementioned plots and stands and if the same acquisition is used for model training and validation, the new model explains 65%-89% of the observed variance, with root-mean-square error (RMSE) of 12%-19% (median: 15%) . By fixing two of the three model parameters, accurate biomass estimation can also be done when different acquisitions or different test sites are used for model training and validation, with RMSE of 12%-56% (median: 17%) . Compared with a simple scaling model computing biomass from the phase center elevation above ground, the proposed model shows significantly better performance in Remningstorp, as it accounts for the large canopy density variations caused by active management. In Krycklan, the two models show similar performance.

Analysis of dolines using multiple methods applied to airborne laser scanning data

Delineating dolines is not a straightforward process especially in densely vegetated areas. This paper deals quantitatively with the surface karst morphology of a Miocene limestone occurrence in the Styrian Basin, Austria. The study area is an isolated karst mountain with a smooth morphology (former planation surface of Pliocene age), densely vegetated (mixed forest) and with a surface area of 1.3km2. The study area is located near the city of Wildon and is named “Wildoner Buchkogel”. The aim of this study was to test three different approaches in order to automatically delineate dolines. The data basis for this was a high resolution digital terrain model (DTM) derived from airborne laser scanning (ALS) and with a raster resolution of 1×1m. The three different methods for doline boundary delineation are: (a) the “traditional” method based on the outermost closed contour line; (b) boundary extraction based on a drainage correction algorithm (filling up pits), and (c) boundary extraction based on hydrologic modelling (watershed). Extracted features are integrated in a GIS environment and analysed statistically regarding spatial distribution, shape geometry, elongation direction and volume. The three methods lead to different doline boundaries and therefore investigated parameters show significant variations. The applied methods have been compared with respect to their application purpose. Depending on delineation process, between 118 and 189 dolines could be defined. The high density of surface karst features demonstrates that solutional processes are major factors in the landscape development of the Wildoner Buchkogel. Furthermore the correlation to the landscape evolution of the Grazer Bergland is discussed.

HOMOGENEOUS GEOVISUALIZATION OF COASTAL AREAS FROM HETEROGENEOUS SPATIO-TEMPORAL DATA

Abstract. On coastal areas, recent increase in production of open-access high-quality data over large areas reflects high interests in modeling and geovisualization, especially for applications of sea level rise prediction, ship traffic security and ecological protection. Research interests are due to tricky challenges from the intrinsic nature of the coastal area, which is composed of complex geographical objects of which spatial extents vary in time, especially in the intertidal zone (tides, sands, etc.). Another interest is the complex modeling of this area based on imprecise cartographic objects (coastline, highest/lowest water level, etc.). The challenge of visualizing such specific area comes thus from 3D+t information, i.e. spatio-temporal data, and their visual integration. In this paper, we present a methodology for geovisualization issues over coastal areas. The first challenge consists in integrating multi-source heterogeneous data, i.e. raster and vector, terrestrial and hydrographic data often coming from various ‘paradigms’, while providing a homogeneous geovisualization of the coastal area and in particular the phenomenon of the water depth. The second challenge consists in finding various possibilities to geovisualize this dynamic geographical phenomenon in controlling the level of photorealism in hybrid visualizations. Our approach is based on the use of a high-resolution Digital Terrain Model (DTM) coming from high resolution LiDAR data point cloud, tidal and topographic data. We present and discuss homogeneous hybrid visualizations, based on LiDAR and map, and on, LiDAR and orthoimagery, in order to enhance the realism while considering the water depth.

Clast mobility within boulder beaches over two winters in Galicia, northwestern Spain

A micro-drone was used to make low altitude flights over boulder beaches at Laxe Brava and Oia in Galicia, northwestern Spain. Flights were made in July 2012, May 2013, and spring 2014. High resolution digital terrain models and orthophotographs, combined with GIS mapping, were used to monitor changes in the position of thousands of boulders. Maximum storm wave height was higher in the winter of 2013–2014 than in winter 2012–2013, and this was reflected in an increase in the proportion of the boulders that moved in the two winters, from 17% to almost 48% at Laxe Brava, and from 53% to almost 88% at Oia. The greater mobility of the boulders at Oia can be attributed in part to their generally smaller size, although there was considerable overlap between the size of boulders that moved and those that did not move within and between the two beaches. There were mobile boulders in areas up to several metres above the high tidal level on both beaches, and boulder transport in the shore-normal and alongshore directions triggered some changes in the beach profiles, particularly in the middle to upper parts of the beaches. Estimates of threshold transport conditions, scaled to boulder mass, breaker height, and other variables, suggested that all but the very largest boulders on the two beaches should have been mobile, even during the summer months when the waves were much lower than in winter. Model over-prediction can be attributed to a number of factors, including: constraints on movement imposed by surrounding boulders; differences in boulder size and their effect on pivoting angles and on the degree to which boulders are exposed or sheltered from wave impact; and difficulties in assigning appropriate values to model coefficients.

The potential of flood forecasting using a variable-resolution global Digital Terrain Model and flood extents from Synthetic Aperture Radar images

A basic data requirement of a river flood inundation model is a Digital Terrain Model (DTM) of the reach being studied. The scale at which modeling is required determines the accuracy required of the DTM. For modeling floods in urban areas, a high resolution DTM such as that produced by airborne LiDAR (Light Detection And Ranging) is most useful, and large parts of many developed countries have now been mapped using LiDAR. In remoter areas, it is possible to model flooding on a larger scale using a lower resolution DTM, and in the near future the DTM of choice is likely to be that derived from the TanDEM-X Digital Elevation Model (DEM). A variable-resolution global DTM obtained by combining existing high and low resolution data sets would be useful for modeling flood water dynamics globally, at high resolution wherever possible and at lower resolution over larger rivers in remote areas. A further important data resource used in flood modeling is the flood extent, commonly derived from Synthetic Aperture Radar (SAR) images. Flood extents become more useful if they are intersected with the DTM, when water level observations (WLOs) at the flood boundary can be estimated at various points along the river reach. To illustrate the utility of such a global DTM, two examples of recent research involving WLOs at opposite ends of the spatial scale are discussed. The first requires high resolution spatial data, and involves the assimilation of WLOs from a real sequence of high resolution SAR images into a flood model to update the model state with observations over time, and to estimate river discharge and model parameters, including river bathymetry and friction. The results indicate the feasibility of such an Earth Observation-based flood forecasting system. The second example is at a larger scale, and uses SAR-derived WLOs to improve the lower-resolution TanDEM-X DEM in the area covered by the flood extents. The resulting reduction in random height error is significant.

A new hierarchical moving curve-fitting algorithm for filtering lidar data for automatic DTM generation

Recent advances in laser scanning hardware have allowed rapid generation of high-resolution digital terrain models (DTMs) for large areas. However, the automatic discrimination of ground and non-ground light detection and ranging (lidar) points in areas covered by densely packed buildings or dense vegetation is difficult. In this paper, we introduce a new hierarchical moving curve-fitting filter algorithm that is designed to automatically and rapidly filter lidar data to permit automatic DTM generation. This algorithm is based on fitting a second-degree polynomial surface using flexible tiles of moving blocks and an adaptive threshold. The initial tile size is determined by the size of the largest building in the study area. Based on an adaptive threshold, non-ground points and ground points are classified and labelled step by step. In addition, we used a multi-scale weighted interpolation method to estimate the bare-earth elevation for non-ground points and obtain a recovered terrain model. Our experiments in four study areas showed that the new filtering method can separate ground and non-ground points in both urban areas and those covered by dense vegetation. The filter error ranged from 4.08% to 9.40% for Type I errors, from 2.48% to 7.63% for Type II errors, and from 5.01% to 7.40% for total errors. These errors are lower than those of triangulated irregular network filter algorithms.

Quantitative risk analysis for hyperconcentrated flows in Nocera Inferiore (southern Italy)

This paper reports on a quantitative estimation of the risk to residents at the toe of Mount Albino, a carbonatic relief covered by shallow deposits of pyroclastic soils, which threatens the municipality of Nocera Inferiore (southern Italy). The quantitative risk analysis (QRA) focuses on one type of mass transport phenomena typical for the context at hand, namely the hyperconcentrated flows. The methodological approach includes three main steps: hazard analysis, consequence analysis and risk estimation. Based on historical incident data, the hazard analysis makes use of a high-resolution digital terrain model and advanced models that incorporate relevant geological and geotechnical input data collected via in situ investigations and laboratory tests. The consequence analysis takes into account information on the exposed persons (age, gender) and their vulnerability. The estimated risk to life is calculated at the individual level (risk to the average and most exposed person). The reported procedure is one of the first QRA’s applications to instabilities which potentially affect natural slopes in Italy, and it was successfully used as technical basis for a public participatory process in Nocera Inferiore, designed and developed to support decisions about risk mitigation measures.

MAD: robust image texture analysis for applications in high resolution geomorphometry

The analysis of surface textures plays an important role in the geomorphometric analysis of high-resolution digital terrain models. Surface textures can be analyzed by means of geostatistical variogram-based indices. The use of variogram-based indices is promising because of their ability to consider the multiscale and anisotropic character of morphometric data. However, similar to other variance-type statistics, variogram-based indices are sensitive to the presence of hotspots and non-stationary data. Consequently, we present a multi-scale and directional image texture analysis operator (MAD or Median Absolute Differences) derived from a modification of a variogram estimator. MAD has been specifically developed to improve the robustness of variogram-based surface indices with a special focus on strongly non-stationary and often noisy spatial data representing solid earth surface morphology. Although the operator has been specifically developed for the analysis of high-resolution digital terrain models, it can be applied to the texture analysis of any type of image. Consequently MAD could be of interest in the broader context of remote sensing as well as for all disciplines for which image texture analysis is relevant. The theoretical presentation of the surface texture operator is accompanied by a working software prototype. The software prototype has been implemented in the Python scripting language for use in ArcGIS (ESRI) using its Spatial Analyst functions. The prototype architecture is concise and can be easily coded in different software environments, such as GIS mapping and image analysis software. The software prototype proposed has been developed to facilitate the development of ad hoc surface texture indices capable of adapting to the special needs of the study at hand. The MAD operator represents an improvement over variogram-based surface texture indices, offering a robust description of relevant aspects of surface texture, including surface roughness.

Estimation of Forest Height and Canopy Density From a Single InSAR Correlation Coefficient

A two-level model (TLM) is introduced and investigated for the estimation of forest height and canopy density from a single ground-corrected InSAR complex correlation coefficient. The TLM models forest as two scattering levels, namely, ground and vegetation, separated by a distance Δh and with area-weighted backscatter ratio μ. The model is evaluated using eight VV-polarized bistatic-interferometric TanDEM-X image pairs acquired in the summers of 2011, 2012, and 2013 over the managed hemi-boreal test site Remningstorp, which is situated in southern Sweden. Ground phase is removed using a highresolution digital terrain model. Inverted TLM parameters for thirty-two 0.5-ha plots of four different types (regular plots, sparse plots, seed trees, and clear-cuts) are studied against reference lidar data. It is concluded that the level distance Δh can be used as an estimate of the 50th percentile forest height estimated from lidar (for regular plots: r > 0.95 and root-mean-square difference (σ) <; 10%, or 1.8 m). Moreover, the uncorrected area fill factor n0 = 1/(1 + μ) can be used as an estimate of the vegetation ratio, which is a canopy density estimate defined as the fraction of lidar returns coming from the canopy to all lidar returns (for regular plots: r > 0.59 and σ ≈ 10%, or 0.07).

Coastal landforms and the Holocene evolution of the Island of Samsø, Denmark

The geomorphology of a coastal landscape may reveal an indication of past shoreline configurations. The spatial arrangement of the preserved morphologies may further contain indications on the importance of the different key parameters influencing shoreline evolution over millennial timescales, such as palaeo sea-level position, longshore currents, energy gradients, and sediment supply. This paper presents the results and observations of a surveying and mapping study conducted for the island of Samsø at a scale of 1:75,000. The objective of the work is to support the interpretation of core sample data and to extract information on the factors determining the morpho-sedimentary development of moraine-embedded coastal lagoon systems during the Holocene. The map is based on an airborne LiDAR-derived high-resolution digital terrain model that is combined with spatial information on bathymetry, surface geology and other features from archived geodata and maps.

Evaluation of the dynamic processes of a landslide with laser scanners and Bayesian methods

This paper deals with the study of the dynamics of a landslide from two different but complementary point of views. The landslide is situated within the Miozza basin, an area of approximately 10.7 km2 located in the Alpine region of Carnia (Italy). In the first part of the paper, the macro-scale analysis of volumetric changes occurred after the reactivation of landslide in 2004 is addressed by using a two-epoch laser scanning surveys from airborne (ALS) and terrestrial (TLS) platforms. airborne laser scanning (ALS) data were collected in 2003 (before reactivation of the phenomenon) with an ALTM 3033 OPTECH sensor while terrestrial laser scanning (TLS) measurements were acquired in 2008 with a Riegl LMS-Z620. The second part of the paper deals with the study of dynamic processes of the landslide at micro-scale. To this aim, a global navigation satellite system (GNSS)-based monitoring network is analysed using a statistical approach to discriminate between measurement noise and possible actual displacements. This task is accomplished using both “classical” statistical testing and a Bayesian approach. The second method has been employed to verify some apparent vertical displacements detected by the classical test.As regards the first topic of the paper, achieved results show that long-range TLS instruments can be profitably used in mountain areas to provide high-resolution digital terrain models (DTMs) with superior quality and detail with respect to aerial light detection and ranging data only, even in areas with very low accessibility. Moreover, ALS- and TLS-derived DTMs can be combined each other in order to fill gaps in ALS data, mainly due to the complexity of terrain morphology, and to perform quite accurate calculations of volume changes due to landslide phenomenon. Finally, the outcomes of the application of Bayesian inference demonstrate the effectiveness of this method to better detect statistically significant displacements of a GNSS monitoring network points. However, the application of this method in the geodetic field requires the identification of a preferring direction of displacements, what is not always feasible in advance.

Terrain Model Resolution Effect on Sight Distance on Roads

Available sight distance is a key factor on road design. This research is focused on the effect of Digital Terrain Model (DTM) resolution on available sight distance. In addition, the effect of distance between calculation points along the vehicle path is also considered. The available sight distance is calculated using a Geographic Information System (GIS). Three high resolution DTMs, based on airborne LiDAR (Light Detection and Ranging), are used. Vehicle path is collected by a Global Navigation Satellite System (GNSS) mounted in a vehicle travelling along the road. Twelve combinations of DTM resolution and distance between calculation points along the vehicle path are studied. Results are statistically analysed and each case study is compared to a reference case which is considered close to reality. The analysis made shows that DTM resolution has a larger effect on the quality of the results than distance between calculation points. Practical issues are discussed.

Using airborne LiDAR sensing technology and aerial orthoimages to unravel roman water supply systems and gold works in NW Spain (Eria valley, León)

LiDAR technology, based on Earth's surface scanning, allows the compilation of high resolution digital terrain models. Recently used in archaeological works for the discovery and description of heritage features such as ancient human-made structures and building ruins, it is particularly effective in areas with dense vegetation or difficult access, where surveying becomes complicated. Among its main advantages over other traditional methods of archaeological research, it highlights the possibility of controlling display parameters, which in turn facilitates data analysis and interpretation. In this study we present an integrated LiDAR and aerial photography data analysis in order to obtain a detailed map of ancient mining works within a small sector of the Roman mining district in northwestern Spain. The presence of gold deposits led to intensive extractive work during the first century b.p.t. Although many of the mining activities were focused on the northwestern area of Las Médulas and Omañas, large deposits were also found along the Duerna and Eria river valleys. Our results complement previous work carried out in the Eria area (Valdería), providing new insights into the hydraulic engineering techniques and the geometry of the main Roman exploitations. This work highlights the scope of the ancient mining works and their impact on the landscape, which are much greater and more important than previously thought.

Hydrogeophysics and remote sensing for the design of hydrogeological conceptual models in hard rocks – Sardón catchment (Spain)

Abstract Hard rock aquifers are highly heterogeneous and hydrogeologically complex. To contribute to the design of hydrogeological conceptual models of hard rock aquifers, we propose a multi-techniques methodology based on a downward approach that combines remote sensing (RS), non-invasive hydrogeophysics and hydrogeological field data acquisition. The proposed methodology is particularly suitable for data scarce areas. It was applied in the pilot research area of Sardon catchment (80 km2) located west of Salamanca (Spain). The area was selected because of hard-rock hydrogeology, semi-arid climate and scarcity of groundwater resources. The proposed methodology consisted of three main steps. First, we detected the main hydrogeological features at the catchment scale by processing: (i) a high resolution digital terrain model to map lineaments and to outline fault zones; and (ii) high-resolution, multispectral satellite QuickBird and WorldView-2 images to map the outcropping granite. Second, we characterized at the local scale the hydrogeological features identified at step one with: i) ground penetrating radar (GPR) to assess groundwater table depth complementing the available monitoring network data; ii) 2D electric resistivity tomography (ERT) and frequency domain electromagnetic (FDEM) to retrieve the hydrostratigraphy along selected survey transects; iii) magnetic resonance soundings (MRS) to retrieve the hydrostratigraphy and aquifer parameters at the selected survey sites. In the third step, we drilled 5 boreholes (25 to 48 m deep) and performed slug tests to verify the hydrogeophysical interpretation and to calibrate the MRS parameters. Finally, we compiled and integrated all acquired data to define the geometry and parameters of the Sardon aquifer at the catchment scale. In line with a general conceptual model of hard rock aquifers, we identified two main hydrostratigraphic layers: a saprolite layer and a fissured layer. Both layers were intersected and drained by fault zones that control the hydrogeology of the catchment. The spatial discontinuities of the saprolite layer were well defined by RS techniques while subsurface geometry and aquifer parameters by hydrogeophysics. The GPR method was able to detect shallow water table at depth between 1 and 3 m b.g.s. The hydrostratigraphy and parameterization of the fissured layer remained uncertain because ERT and FDEM geophysical methods were quantitatively not conclusive while MRS detectability was restricted by low volumetric water content. The proposed multi-technique methodology integrating cost efficient RS, hydrogeophysics and hydrogeological field investigations allowed us to characterize geometrically and parametrically the Sardon hard rock aquifer system, facilitating the design of hydrogeological conceptual model of the area.