Spatial Resolution Digital Elevation Model Research Articles

Monitoring river morphology & bank erosion using UAV imagery – A case study of the river Buëch, Hautes-Alpes, France

River morphology dynamics and river bank erosion were mapped using multi-temporal images acquired in June 2014 and June 2015 by an Unmanned Airborne Vehicle (UAV). The selected study sites are located in two dynamic parts of the floodplain of the river Buëch in the Hautes-Alpes province in south-eastern France. The images were processed using the Structure from Motion algorithm into high spatial resolution OrthoMosaics of 5 cm pixel size and DEMs (Digital Elevation Model) of 10 cm pixel size. The positional and vertical accuracy of the UAV products were evaluated using Real Time Kinematic GPS (RTK-GPS) points measurements of markers laid out in the floodplain during image acquisition. Obtained accuracies are centimeters to decimeters. River morphology such as channel displacements, gravel bank displacement and avulsions were evaluated using the OrthoMosaics. The Buëch river shows mainly braided river properties but at locations some meandering river properties were observed. Bank erosion volume calculations were made by comparing the high spatial resolution DEMs of 2014 and 2015. Accuracy of bank erosion assessment was evaluated using RTK-GPS transects of known sites of bank erosion. Bank retreat could be mapped at centimeter to decimeter detail but sometimes hampered by overhanging vegetation, water glitter and shadows. Our conclusions are that time-series of high spatial resolution UAV images can be acquired in a flexible and easy way, the individual images can nowadays be processed in a straightforward way into suitable products i.e. OrthoMosaics and DEMs which are valuable products for land administrators having a responsibility to survey and monitor rivers and control them. Accuracy of the UAV products is high in XYZ direction and sufficient for river monitoring purposes and for designing management measures.

Modeling Anisotropic Reflectance Over Composite Sloping Terrain

Heterogeneous terrain significantly complicates signals received by airborne or satellite sensors. It has been demonstrated that both solar direct beam and diffuse skylight illumination conditions are significant factors influencing the anisotropy of reflectance over mountainous areas. Several models and methods have been developed to account for topographic effects on surface reflectance at the pixel level in remote sensing. However, subtopographic effects are generally neglected for low-spatial-resolution pixels due to the complex law of radiative transfer and the limitations of higher spatial resolution digital elevation models, which can lead to deviations in reflectance estimation. Accurately estimating the subtopographic effects on anisotropic reflectance over composite sloping terrain under different illumination conditions presents a challenge for remote sensing models and applications. In this paper, the diffused equivalent slope model (dESM) was developed, which is an anisotropic reflectance simulation model coupled with diffuse skylight over composite sloping terrain. The corresponding subtopographic impact factor was also proposed to exhibit how microslope topography affects reflectance over composite sloping terrain under different illumination conditions. Simulated reflectance data sets simulated by the radiosity method and Moderate Resolution Imaging Spectroradiometer reflectance data were used to evaluate the performance of the dESM model. The results reveal that the dESM model can accurately capture the reflectance anisotropy over composite sloping terrain under different illumination conditions, and the subtopographic impact factor can account for the effects of microslope topography, shadow, and illumination conditions.

Using portable OSL reader to obtain a time scale for soil accumulation and erosion in archaeological terraces, the Judean Highlands, Israel

Abstract Current conventions on the fate of agricultural bench terraces in the mountainous Mediterranean climatic zones, assume that after abandonment terraces undergo rapid degradation and soil loss. First walls crumble, followed by soil washed out of breaches in the walls by runoff, resulting in rapid erosion of soil from the slopes downhill into the streams. Additionally, soil erosion may explain why previous optically stimulated luminescence (OSL) dating of terrace soils in the Judean Highlands, Israel, found mostly young soils dating to the past 700 years, and only occasionally were older ages obtained for soils at the very base of these terraces. In contrast, observations made in the same region show that slopes with degraded terraces appear to still retain much soil even though only faint remains of the terraces exist. To test if terraces and soils indeed erode entirely and how long this might take, a relatively smooth hill slope showing remains of highly degraded sets of terraces was studied. Samples were collected from excavated pits for full OSL dating, in addition to samples densely collected for OSL measurements using a portable OSL reader (PR). Air-born photogrammetry was used to obtain high spatial resolution Digital Elevation Model. Results show that the main body of terraces was first built ∼800 years ago and maintained until 175-100 years age when they were abandoned and subsequently degraded. Since then 30–45% of soil volume was lost to erosion, however steady-state was reached at a relatively high slope of 65%, with stabilization by vegetation. The thick soil present on most of the slope suggests that after the first stage of rapid degradation the slopes reache equilibrium, most likely due to vegetation that reduces direct soil erosion, so most of the soil is retained on the slope. Finally, the PR allows for a much more nuanced understanding of terrace soil history.

UAV-based remote sensing surveys of lava flow fields: a case study from Etna’s 1974 channel-fed lava flows

During an eruption, time scales of topographic change are fast and involve vertical and planimetric evolution of millimeters to meters as the event progresses. Repeat production of high spatial resolution terrain models of lava flow fields over time scales of a few hours is thus a high-value capability in tracking the buildup of the deposit. Among the wide range of terrestrial and aerial methods available to collect such topographic data, the use of an unmanned aerial vehicle (UAV) as an acquisition platform, together with structure from motion (SfM) photogrammetry, has become especially useful. This approach allows high-frequency production of centimeter-scale terrain models over kilometer-scale areas, including dangerous and inaccessible zones, with low cost and minimal hazard to personnel. This study presents the application of such an integrated UAV-SfM method to generate a high spatial resolution digital terrain model and orthomosaic of Mount Etna’s January–February 1974 lava flow field. The SfM method, applied to images acquired using a UAV platform, enabled the extraction of a very high spatial resolution (20 cm) digital elevation model and the generation of a 3-cm orthomosaic covering an area of 1.35 km2. This spatial resolution enabled us to analyze the morphology of sub-meter-scale features, such as folds, blocks, and cracks, over kilometer-scale areas. The 3-cm orthomosaic allowed us to further push the analysis to centimeter-scale grain size distribution of the lava surface. Using these data, we define three types of crust structure and relate them to positions within a channel-fed ʻaʻā flow system. These crust structures are (i) flow parallel shear lines, (ii) raft zones, and (iii) folded zones. Flow parallel shear lines are found at the channel edges, and are 2-m-wide and 0.25-m-deep zones running along the levee base and in which cracking is intense. They result from intense shearing between the moving channel lava and the static levee lava. In zones where initial levees are just beginning to form, these subtle features are the only marker that delimits the moving lava from the stagnant marginal lava. Rafts generally form as the system changes from a stable to a transitional channel regime. Over this 170-m-long zone, the channel broadens from 8 to 70 m and rafts are characterized by topographically higher and poorly cracked areas, surrounded by lower, heavily cracked areas. We interpret the rafts as forming due to breakup of crust zones, previously moving in a coherent manner in the narrow proximal channel reach. Folded zones involve arcuate, cross-flow ridges with their apexes pointing down-flow, where ridges have relatively small clasts and depressions are of coarser-grained breccia. Our folds have wavelengths of 10 m and amplitudes of 1 m; are found towards the flow front, down-flow of the raft zones; and are associated with piling up of lava behind a static or slowly moving flow front. The very high spatial resolution topographic data available from UAV-SfM allow us to resolve surfaces where roughness has a vertical and horizontal scale of variation that is less than 1 m. This is the case over pāhoehoe and ʻaʻā flow surfaces, and thus allows us to explore those new structures that are only apparent in the sub-metric data. Moreover, during future eruptions, the possibility to acquire such information in near-real time will allow a prompt analysis of developing lava flow fields and structures therein, such as developing lava channel systems, so as to contribute to timely hazard assessment, modeling, and projections.

Selection of optimal scales for soil depth prediction on headwater hillslopes: A modeling approach

Landform attributes derived from digital elevation models (DEMs) are the most commonly used factors to predict soil depths on hillslopes. However, the selection of an appropriate algorithm to calculate terrain attributes and identify an optimal DEM resolution remains ambiguous. In this study, we propose a method to use high-resolution DEM and spatial soil depth data to obtain terrain attributes and identify the optimal DEM resolution to predict soil depths at hillslope scales. A geophysical method (ground penetrating radar, GPR) was used to investigate the reasons for the optimal DEM resolution findings. Point-scale soil depth from 116 sites and elevation data were collected from two adjacent headwater hillslopes (H1: 0.42ha and H2: 0.31ha) at the Hemuqiao hydrological experimental station in Southeast China. The elevation datasets were collected using a total station at a variable spacing level and were then used to derived DEMs at nine spatial resolutions: 0.25, 0.50, 0.75, 1.00, 2.00, 3.50, 5.00, 7.50 and 10.00m. Nine primary and secondary topographic attributes using the nine spatial resolution DEMs were then derived. Two different algorithms (D8 and D∞) for calculating contributing areas and related secondary topographic attributes were compared. We used and compared both linear (multiple linear regression, MLR) and non-linear (artificial neural network, ANN) models for soil depth prediction. Results demonstrated that the two models performed well for predicting soil depth. Specifically, MLR performed better than the non-linear model of ANNs. Additionally, we found that the multiple-direction algorithm (D∞) allowed flow divergence and avoided abrupt changes in soil depth predictions (orphan cells) and should be adopted for model construction. The D∞ algorithm performed better in divergent areas, such as ridges and side slopes, and the D∞ algorithm also worked well in convergent areas, such as valleys. Moreover, our results demonstrated that moderate (e.g., 2.00m) resolution topographic attributes, instead of the finest resolution, achieved the best prediction with the lowest root mean square error (RMSE) and mean absolute error (MAE) and the highest values of the coefficient of determination (R2). Moreover, the GPR results indicated that the valley accumulated more soils than side-slope areas, and a sharp increase in soil depth was found in areas adjacent to the valley. Comparing the optimal DEM resolution and valley width obtained by GPR, we found that average valley width (AVW) should be considered a good measure for choosing the optimal DEM resolution for soil depth prediction.

Monitoring the dynamics of surface water fraction from MODIS time series in a Mediterranean environment

Detailed spatial information of changes in surface water extent is needed for water management and biodiversity conservation, particularly in drier parts of the globe where small, temporally-variant wetlands prevail. Although global surface water histories are now generated from 30m Landsat data, for many locations they contain large temporal gaps particularly for longer periods (>10years) due to revisit intervals and cloud cover. Daily Moderate Resolution Imaging Spectrometer (MODIS) imagery has potential to fill such gaps, but its relatively coarse spatial resolution may not detect small water bodies, which can be of great ecological importance. To address this problem, this study proposes and tests options for estimating the surface water fraction from MODIS 16-day 500m Bidirectional Reflectance Distribution Function (BRDF) corrected surface reflectance image composites. The spatial extent of two Landsat tiles over Spain were selected as test areas. We obtained a 500m reference dataset on surface water fraction by spatially aggregating 30m binary water masks obtained from the Landsat-derived C-version of Function of Mask (CFmask), which themselves were evaluated against high-resolution Google Earth imagery. Twelve regression tree models were developed with two approaches, Random Forest and Cubist, using spectral metrics derived from MODIS data and topographic parameters generated from a 30m spatial resolution digital elevation model. Results showed that accuracies were higher when we included annual summary statistics of the spectral metrics as predictor variables. Models trained on a single Landsat tile were ineffective in mapping surface water in the other tile, but global models trained with environmental conditions from both tiles can provide accurate results for both study areas. We achieved the highest accuracy with Cubist global model (R2=0.91, RMSE=11.05%, MAE=7.67%). Our method was not only effective for mapping permanent water fraction, but also in accurately capturing temporal fluctuations of surface water. Based on this good performance, we produced surface water fraction maps at 16-day interval for the 2000–2015 MODIS archive. Our approach is promising for monitoring surface water fraction at high frequency time intervals over much larger regions provided that training data are collected across the spatial domain for which the model will be applied.

DEM generation from contours and a low-resolution DEM

A digital elevation model (DEM) is a virtual representation of topography, where the terrain is established by the three-dimensional co-ordinates. In the framework of sparse representation, this paper investigates DEM generation from contours. Since contours are usually sparsely distributed and closely related in space, sparse spatial regularization (SSR) is enforced on them. In order to make up for the lack of spatial information, another lower spatial resolution DEM from the same geographical area is introduced. In this way, the sparse representation implements the spatial constraints in the contours and extracts the complementary information from the auxiliary DEM. Furthermore, the proposed method integrates the advantage of the unbiased estimation of kriging. For brevity, the proposed method is called the kriging and sparse spatial regularization (KSSR) method. The performance of the proposed KSSR method is demonstrated by experiments in Shuttle Radar Topography Mission (SRTM) 30 m DEM and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 30 m global digital elevation model (GDEM) generation from the corresponding contours and a 90 m DEM. The experiments confirm that the proposed KSSR method outperforms the traditional kriging and SSR methods, and it can be successfully used for DEM generation from contours.

Optimizing landslide susceptibility zonation: Effects of DEM spatial resolution and slope unit delineation on logistic regression models

We perform landslide susceptibility zonation with slope units using three digital elevation models (DEMs) of varying spatial resolution of the Ubaye Valley (South French Alps). In so doing, we applied a recently developed algorithm automating slope unit delineation, given a number of parameters, in order to optimize simultaneously the partitioning of the terrain and the performance of a logistic regression susceptibility model. The method allowed us to obtain optimal slope units for each available DEM spatial resolution. For each resolution, we studied the susceptibility model performance by analyzing in detail the relevance of the conditioning variables. The analysis is based on landslide morphology data, considering either the whole landslide or only the source area outline as inputs. The procedure allowed us to select the most useful information, in terms of DEM spatial resolution, thematic variables and landslide inventory, in order to obtain the most reliable slope unit-based landslide susceptibility assessment.

LIDAR-based detection of the post-typhoon recovery of a meso-macro-tidal beach in the Beibu Gulf, China

Because of global sea-level rising with frequent storm activities, most beaches in the world experience widespread erosion, which poses a significant hazard to beach management. The morphodynamic process of the evolution of a beach in response to storm activities is of increasing concern. Using a terrestrial laser scanner, the topography of Yintan beach was continuously observed for 33days with a 25cm spatial resolution digital elevation model (DEM) of that covered an area of 15ha before and after typhoon Rammasun. The short-term beach recovery was explored using a comprehensive approach, which included grey relational analysis, terrain analysis, Gaussian fitting, Gamma fitting, and Delft3D wave simulation methods. The results show that the Yintan beach recovery process can be divided into three stages with two transition points. Stage one began at the end of Rammasun, which indicated a weakly stable state with an average daily net erosion of −588m3, a mean beach slope that ranged from 0.96° to 1.28°, and a landform with no obvious alterations. After the vast accretion of 6874m3 of first transition, stage two, which was characterized by oscillations, occurred in the region with an average daily net erosion of −396m3 and a conspicuous beach slope reconstruction in the range of 0.94°–2.16°. During this stage, sandbar reconstruction played a key role. The second transition event arose at the end of stage two with a vast accretion of 5762m3. Afterwards, the daily net accretion of 200m3 and the beach slope range of 0.93°–1.74° dominated the region during stage three, and the beach surface became similar to that of the pre-Rammasun. Within the entire observation period, intense beach elevation changes that ranged from −15cm to −6cm and 6cm to 15cm mainly occurred in the sandbar and foreshore zones, respectively. Additionally, slight elevation changes (ranging from −4cm to 4cm) were densely distributed in the backshore and dunes, and moderate elevation changes (ranging from −6cm to −4cm and 4cm to 6cm) emerged along the entire beachface. It was concluded that the spatial distribution of the bottom shear stress that was induced by wave action was responsible for the reconstruction of the foreshore and sandbar after Rammasun, whereas the short-term beach recovery process was affected by the beach states in various wave breaking conditions.

Pluvial Flooding in European Cities—A Continental Approach to Urban Flood Modelling

Pluvial flooding is caused by localized intense rainfall and the flood models used to assess it are normally applied on a city (or part of a city) scale using local rainfall records and a high resolution digital elevation model (DEM). Here, we attempt to model pluvial flooding on a continental scale and calculate the percentage of area flooded for all European cities for a 10-year return period for hourly rainfall (RP10). Difficulties in obtaining hourly rainfall records compromise the estimation of each city RP10 and the Europe-wide DEM spatial resolution is low relative to those typically used for individual case-studies. Nevertheless, the modelling capabilities and necessary computing power make this type of continental study now possible. This is a first attempt at continental city flooding modelling and our methodology was designed so that our results can easily be updated as better/more data becomes available. The results for each city depend on the interplay of rainfall intensity, the elevation map of the city and the flow paths that are created. In general, cities with lower percentage of city flooded are in the north and west coastal areas of Europe, while the higher percentages are seen in continental and Mediterranean areas.

Validation of digital elevation models (DEMs) and comparison of geomorphic metrics on the southern Central Andean Plateau

Abstract. In this study, we validate and compare elevation accuracy and geomorphic metrics of satellite-derived digital elevation models (DEMs) on the southern Central Andean Plateau. The plateau has an average elevation of 3.7 km and is characterized by diverse topography and relief, lack of vegetation, and clear skies that create ideal conditions for remote sensing. At 30 m resolution, SRTM-C, ASTER GDEM2, stacked ASTER L1A stereopair DEM, ALOS World 3D, and TanDEM-X have been analyzed. The higher-resolution datasets include 12 m TanDEM-X, 10 m single-CoSSC TerraSAR-X/TanDEM-X DEMs, and 5 m ALOS World 3D. These DEMs are state of the art for optical (ASTER and ALOS) and radar (SRTM-C and TanDEM-X) spaceborne sensors. We assessed vertical accuracy by comparing standard deviations of the DEM elevation versus 307 509 differential GPS measurements across 4000 m of elevation. For the 30 m DEMs, the ASTER datasets had the highest vertical standard deviation at > 6.5 m, whereas the SRTM-C, ALOS World 3D, and TanDEM-X were all < 3.5 m. Higher-resolution DEMs generally had lower uncertainty, with both the 12 m TanDEM-X and 5 m ALOS World 3D having < 2 m vertical standard deviation. Analysis of vertical uncertainty with respect to terrain elevation, slope, and aspect revealed the low uncertainty across these attributes for SRTM-C (30 m), TanDEM-X (12–30 m), and ALOS World 3D (5–30 m). Single-CoSSC TerraSAR-X/TanDEM-X 10 m DEMs and the 30 m ASTER GDEM2 displayed slight aspect biases, which were removed in their stacked counterparts (TanDEM-X and ASTER Stack). Based on low vertical standard deviations and visual inspection alongside optical satellite data, we selected the 30 m SRTM-C, 12–30 m TanDEM-X, 10 m single-CoSSC TerraSAR-X/TanDEM-X, and 5 m ALOS World 3D for geomorphic metric comparison in a 66 km2 catchment with a distinct river knickpoint. Consistent m∕n values were found using chi plot channel profile analysis, regardless of DEM type and spatial resolution. Slope, curvature, and drainage area were calculated and plotting schemes were used to assess basin-wide differences in the hillslope-to-valley transition related to the knickpoint. While slope and hillslope length measurements vary little between datasets, curvature displays higher magnitude measurements with fining resolution. This is especially true for the optical 5 m ALOS World 3D DEM, which demonstrated high-frequency noise in 2–8 pixel steps through a Fourier frequency analysis. The improvements in accurate space-radar DEMs (e.g., TanDEM-X) for geomorphometry are promising, but airborne or terrestrial data are still necessary for meter-scale analysis.

Modeling streamflow and sediment responses to climate change and human activities in the Yanhe River, China

Abstract Quantifying the impact of climate change and human activities on hydrological processes is of great importance for regional water-resource management. In this study, trend analysis and analysis of the short-term variations in annual streamflow and sediment load in the Yanhe River Basin (YRB) during the period 1972–2011 were conducted using linear regression and the Pettitt test. The Soil and Water Assessment Tool (SWAT) was employed to simulate the hydrological processes. The results show that both annual mean streamflow and annual mean sediment load in the YRB significantly decreased (P < 0.05) during the study period. The relative contributions from climate change and human activities to YRB streamflow decline between 1996 and 2011 were estimated to be 55.8 and 44.2%, respectively. In contrast to the results for streamflow, the dominant cause of YRB sediment-load decline was human activity (which explained 64% of the decrease), rather than climate change. The study also demonstrates that topographical characteristics (watershed subdivision threshold value, digital elevation model spatial resolution) can cause uncertainties in the simulated streamflow and sediment load. The results presented in this paper will increase understanding of the mechanisms of soil loss and will enable more efficient management of water resources in the YRB.

Using a landform evolution model to study ephemeral gullying in agricultural fields: the effects of rainfall patterns on ephemeral gully dynamics

AbstractWater driven soil erosion is a major cause of land degradation worldwide. Ephemeral gullies (EGs) are considered key contributors to agricultural catchment soil loss. Despite their importance, the parameters and drivers controlling EG dynamics have not been adequately quantified. Here we investigate the effects of rainfall characteristics on EGs, using the physically based landform evolution model (LEM) CAESAR‐Lisflood. An initial goal of this study was to test the feasibility of using a LEM to estimate EG dynamics based on an easily obtainable and moderate spatial resolution (2 × 2 m) Digital Elevation Model (DEM). EG evolution was simulated for two rainfall seasons in a 0.37 km2 agricultural plot situated in a semiarid catchment in central Israel. The 2014 rainfall season was used to calibrate the model and the 2015 season was used for validation. The model overall well predicted the EG network structure and average depth but tended to underestimate the EG length. The effects of rainfall characteristics on EG dynamics were investigated by comparing simulations employing seven rainfall scenarios. Four of these scenarios differ in their overall rainfall volume relative to observed precipitation (+20%, +10%, −10%, −20%). The remaining three scenarios vary in the temporal distribution of rainfall during each storm, allowing us to isolate the effect of rainfall intensity on EG evolution. The results show that: (1) EG dynamics strongly correlated with changes in rainfall volume; (2) small‐scale morphological behavior varies between rainfall scenarios, resulting in different meandering and connectivity variability; (3) EG evolution is divided into two main stages, an initial rapid development occurring after the first two weeks of the rainy season, followed by a stable development period; (4) a 12 mm h−1 intensity threshold was observed to initiate and, later, modify EGs; and (5) inner storm rainfall variability can have a considerable effect on EG evolution. Copyright © 2016 John Wiley & Sons, Ltd.

Comparing 1D and combined 1D/2D hydraulic simulations using high-resolution topographic data: a case study of the Koiliaris basin, Greece

ABSTRACTThe development of high spatial resolution digital elevation models takes place via the use of GeoEye-1 stereo-pair imagery, providing highly accurate geometrical representations of complex riverine systems. The combination of geographic information systems with hydraulic models facilitates the exploitation of satellite topographic information throughout the cross-section extraction process. One-dimensional HEC-RAS and combined 1D/2D HEC-RAS models are adjusted by making use of the resulting high-resolution input. Several hydraulic simulations are effectuated in order to test how significantly DEM resolution affects hydraulic modelling results, with regard also to the model dimensionality. The ability of the combined 1D/2D model, based mainly on the high-accuracy input data, provides an accurate estimate of the flood hazard area. Flood-prone areas could take advantage of high-accuracy results and facilitate the effective management of extreme events and sufficient decision making.

Landform classification using a sub-pixel spatial attraction model to increase spatial resolution of digital elevation model (DEM)

The purpose of the present study is preparing a landform classification by using digital elevation model (DEM) which has a high spatial resolution. To reach the mentioned aim, a sub-pixel spatial attraction model was used as a novel method for preparing DEM with a high spatial resolution in the north of Darab, Fars province, Iran. The sub-pixel attraction models convert the pixel into sub-pixels based on the neighboring pixels fraction values, which can only be attracted by a central pixel. Based on this approach, a mere maximum of eight neighboring pixels can be selected for calculating of the attraction value. In the mentioned model, other pixels are supposed to be far from the central pixel to receive any attraction. In the present study by using a sub-pixel attraction model, the spatial resolution of a DEM was increased. The design of the algorithm is accomplished by using a DEM with a spatial resolution of 30m (the Advanced Space borne Thermal Emission and Reflection Radiometer; (ASTER)) and a 90m (the Shuttle Radar Topography Mission; (SRTM)). In the attraction model, scale factors of (S=2, S=3, and S=4) with two neighboring methods of touching (T=1) and quadrant (T=2) are applied to the DEMs by using MATLAB software. The algorithm is evaluated by taking the best advantages of 487 sample points, which are measured by surveyors. The spatial attraction model with scale factor of (S=2) gives better results compared to those scale factors which are greater than 2. Besides, the touching neighborhood method is turned to be more accurate than the quadrant method. In fact, dividing each pixel into more than two sub-pixels decreases the accuracy of the resulted DEM. On the other hand, in these cases DEM, is itself in charge of increasing the value of root-mean-square error (RMSE) and shows that attraction models could not be used for S which is greater than 2. Thus considering results, the proposed model is highly capable of increasing the spatial resolution of DEM (the new DEM with high spatial resolution). In the next step, in order to prepare the geomorphology map using topographic position index (TPI), the DEM with scale factor of (S=2) was used, touching neighborhood serves as input. The landform classes were extracted by using TPI with the new DEM; consequently, the attraction model extraction showed details of landforms that make them more separable than the landform map prepared by utilizing the 90m spatial resolution DEM. Moreover, the results showed that the landform of the 90m spatial resolution DEM (S=2, T=2) and ASTER DEM 30m were similar to each other, these results indicate a high accuracy of the proposed attraction model.

DEM sourcing guidelines for computing 1 Eö accurate terrain corrections for airborne gravity gradiometry

In this paper we investigate digital elevation model (DEM) sourcing requirements to compute gravity gradiometry terrain corrections accurate to 1Eötvös (Eö) at observation heights of 80m or more above ground. Such survey heights are typical in fixed-wing airborne surveying for resource exploration where the maximum signal-to-noise ratio is sought. We consider the accuracy of terrain corrections relevant for recent commercial airborne gravity gradiometry systems operating at the 10Eö noise level and for future systems with a target noise level of 1Eö. We focus on the requirements for the vertical gradient of the vertical component of gravity (Gdd) because this element of the gradient tensor is most commonly interpreted qualitatively and quantitatively.Terrain correction accuracy depends on the bare-earth DEM accuracy and spatial resolution. The bare-earth DEM accuracy and spatial resolution depends on its source. Two possible sources are considered: airborne LiDAR and Shuttle Radar Topography Mission (SRTM). The accuracy of an SRTM DEM is affected by vegetation height. The SRTM footprint is also larger and the DEM resolution is thus lower. However, resolution requirements relax as relief decreases. Publicly available LiDAR data and 1arc-second and 3arc-second SRTM data were selected over four study areas representing end member cases of vegetation cover and relief.The four study areas are presented as reference material for processing airborne gravity gradiometry data at the 1Eö noise level with 50m spatial resolution. From this investigation we find that to achieve 1Eö accuracy in the terrain correction at 80m height airborne LiDAR data are required even when terrain relief is a few tens of meters and the vegetation is sparse. However, as satellite ranging technologies progress bare-earth DEMs of sufficient accuracy and resolution may be sourced at lesser cost. We found that a bare-earth DEM of 10m resolution and 2m accuracy are sufficient for achieving 1Eö accuracy in the terrain correction independent of relief or vegetation cover. For AGG systems operating at greater noise levels the 3arc-second SRTM is adequate for areas having tens of meters of relief and sparse vegetation and even for areas of greater relief and sparse vegetation if a constant elevation survey is flown at 80m above terrain peak.

Mapeamento digital de areia, argila e carbono orgânico por modelos Random Forest sob diferentes resoluções espaciais

Resumo O objetivo deste trabalho foi avaliar a influência da resolução espacial do modelo digital de elevação e da eficiência de modelos Random Forest sobre a predição dos teores de areia, argila e carbono orgânico, com uso de número reduzido de amostras. O trabalho foi realizado em área de Cerrado com diversidade litológica, no Estado do Mato Grosso do Sul, tendo-se utilizado atributos morfométricos, dados do sensor TM Landsat 5 e litologia como covariáveis preditoras. Dados da camada superficial (0,0-0,2 m) de 175 perfis de solos (0,009 perfis km-2) e de 26 covariáveis preditoras foram utilizados com resolução espacial de 30 (conjunto 1) e 90 m (conjunto 2). A análise realizada pelo Random Forest mostrou que as covariáveis de nível de base do canal de drenagem, da elevação e da litologia foram as mais importantes para explicar a variabilidade. A validação dos modelos apresentou similaridade entre os conjuntos quanto à predição de areia, argila e carbono orgânico, o que explica os seguintes valores de variabilidade espacial, respectivamente: 44, 40 e 33%, para a resolução de 30 m; e de 45, 46 e 33%, para a resolução de 90 m. A resolução espacial das covariáveis preditoras tem pouca influência sobre a predição dos atributos, e a abordagem por Random Forest apresenta potencial de utilização para estimar atributos do solo.

Flood inundation mapping sensitivity to riverine spatial resolution and modelling approach

An innovative approach in the investigation of complex landscapes for hydraulic modelling applications is the use of terrestrial laser scanner (TLS) that can lead to a high-resolution digital elevation model (DEM). Another notable factor in flood modelling is the selection of the hydrodynamic model (1D, 2D and 1D/2D), especially in complex riverine topographies, that can influence the accuracy of flood inundation area and mapping. This paper uses different types of hydraulic–hydrodynamic modelling approaches and several types of river and riparian area spatial resolution for the implementation of a sensitivity analysis for floodplain mapping and flood inundation modelling process at ungauged watersheds. Four data sets have been used for the construction of the river and riparian areas: processed and unprocessed TLS data, topographic land survey data and typical digitized contours from 1:5000-scale topographic maps. Modelling approaches combinations consist of: one-dimensional hydraulic models (HEC-RAS, MIKE 11), two-dimensional hydraulic models (MIKE 21, MIKE 21 FM) and combinations of coupled hydraulic models (MIKE 11/MIKE 21) within the MIKE FLOOD platform. Historical flood records and estimated flooded area derived from an observed extreme flash-flood event have been used in the validation process using 2 × 2 contingency tables. Flood inundation maps have been generated for each modelling approach and landscape configuration at the lower part of Xerias River reach at Volos, Greece, and compared for assessing the sensitivity of input data and model structure uncertainty. Results provided from contingency table analysis indicate the sensitivity of floodplain modelling on the DEM spatial resolution and the hydraulic modelling approach.

USLE LS 인자 구축시 DEM 해상도가 미치는 영향

Digital Elevation Models (DEMs) have been used to represent the effects of topography on soil erosion. A DEM of 30 m resolution is frequently used in hydrology and soil erosion studies because the National Water Management Information System (WAMIS) provides a 30 m resolution DEM at national scale on its web site. However, the Ministry of Environment recommends the use of a DEM with 10 m resolution for evaluation of soil erosion due to the fact that soil erosion estimation is to some degree affected by the spatial resolution of DEM. In this regard, a DEM with 5 m resolution was resampled for 10 × 10 m, 20 × 20 m, 30 × 30 m, 50 × 50 m, 70 × 70 m, and 100 × 100 m resolutions, respectively. USLE LS factors and soil erosion values were evaluated using these datasets. Use of a DEM with at least 30 m resolution provided reasonable LS factors and soil erosion values at a watershed.

Geometric evolution of the Horcones Inferior Glacier (Mount Aconcagua, Central Andes) during the 2002–2006 surge

AbstractThe Central Andes of Chile and Argentina (31–35°S) contain a large number and variety of ice masses, but only two surging glaciers have been studied in this region. We analyzed the 2002–2006 surge of the Horcones Inferior Glacier, Mount Aconcagua, Argentina, based on medium spatial resolution (15–30 m) satellite images and digital elevation models. During the buildup phase the glacier was stagnant, with velocities lower than 0.1 m/d. In the active‐phase velocities reached 14 m/d and the glacier front advanced 3.1 km. At the peak of the active phase (2003–2004), the area‐averaged elevation change was −42 m in the reservoir zone (2.53 km2) and +30 m in the receiving zone (3.31 km2). The estimated ice flux through a cross section located at 4175 meter above sea level was 108 m3 during a period of 391 days, a flux that suggests a mean glacier thickness at this location of ~90 m. The depletion phase showed a recovery of the reservoir zone elevation, the down wasting of the receiving zone (−17 m, 2007–2014), and a return to quiescent velocities. The short active phase, the abrupt change in the velocities, and the high level of the proglacial stream indicate a hydrological switch (Alaska type) trigger. The 2002–2006 and 1984–1990 surges of Horcones Inferior were synchronous with the surges of nearby Grande del Nevado Glacier. These events occurred after periods of positive mass balance, so we hypothesize a climate driver.