Derived Digital Terrain Model Research Articles

High-resolution digital outcrop model of the faults, fractures, and stratigraphy of the Agardhfjellet Formation cap rock shales at Konusdalen West, central Spitsbergen

Abstract. Structure-from-motion (SfM) photogrammetry has become an important tool for the digitalisation of outcrops as digital outcrop models (DOMs). DOMs facilitate the mapping of stratigraphy and discontinuous structures like folds, faults, and fractures from the centimetre to kilometre scale. With pristine, treeless exposures, the outcropping strata in Svalbard, Arctic Norway, hold exceptional potential for analogue studies and are ideally suited for the acquisition of high-resolution DOMs. Here, we present the acquisition, processing, and integration of the Konusdalen West digital model data set, comprising both DOM and derived digital terrain model (DTM) data. Drone-based image acquisition took place over 2 weeks in July and August 2020. The Konusdalen West DOM and DTM cover a 0.12 km2 area and span a 170 m elevation difference. The DOM covers the upper two-thirds of the mudstone-dominated Late Jurassic–Early Cretaceous Agardhfjellet Formation. The Agardhfjellet Formation and its time equivalents are regional cap rocks for CO2 sequestration and petroleum accumulations on the Norwegian Continental Shelf. A total of 15 differential GNSS control points were used to georeference and quality assure the digital data assets, 5 of which function as reference checkpoints. SfM processing of 5512 acquired images resulted in high-confidence, centimetre-scale resolution point clouds, textured mesh (DOM), tiled model, orthomosaics, and a DTM. The confidence-filtered dense cloud features an average inter-point distance of 1.57 cm and has an average point density of 3824.9 points per metre. The five checkpoints feature root mean square errors of 2.0 cm in X, 1.3 cm in Y, 5.2 cm in Z, and 5.7 cm in XYZ. Increased confidences and densities are present along the western flank of the Konusdalen West outcrop, where a fault fracture network in mudstone-dominated strata is best exposed and photographed most extensively. Top and side view orthomosaics feature maximum resolutions of 8 mm per pixel, enabling the mapping of faults, formation members, marker beds, fractures, and other sub-centimetre features. Additional structural measurements and observations were taken in June 2021 to place the data in the geological context. Data described in this paper can be accessed at Norstore under https://doi.org/10.11582/2022.00027 (Betlem, 2022b).

Modeling Streamflow and Sediment Loads with a Photogrammetrically Derived UAS Digital Terrain Model: Empirical Evaluation from a Fluvial Aggregate Excavation Operation

Soil erosion monitoring is a pivotal exercise at macro through micro landscape levels, which directly informs environmental management at diverse spatial and temporal scales. The monitoring of soil erosion can be an arduous task when completed through ground-based surveys and there are uncertainties associated with the use of large-scale medium resolution image-based digital elevation models for estimating erosion rates. LiDAR derived elevation models have proven effective in modeling erosion, but such data proves costly to obtain, process, and analyze. The proliferation of images and other geospatial datasets generated by unmanned aerial systems (UAS) is increasingly able to reveal additional nuances that traditional geospatial datasets were not able to obtain due to the former’s higher spatial resolution. This study evaluated the efficacy of a UAS derived digital terrain model (DTM) to estimate surface flow and sediment loading in a fluvial aggregate excavation operation in Waukesha County, Wisconsin. A nested scale distributed hydrologic flow and sediment loading model was constructed for the UAS point cloud derived DTM. To evaluate the effectiveness of flow and sediment loading generated by the UAS point cloud derived DTM, a LiDAR derived DTM was used for comparison in consonance with several statistical measures of model efficiency. Results demonstrate that the UAS derived DTM can be used in modeling flow and sediment erosion estimation across space in the absence of a LiDAR-based derived DTM.

Assessing the Performance of ICESat-2/ATLAS Multi-Channel Photon Data for Estimating Ground Topography in Forested Terrain

As a continuation of Ice, Cloud, and Land Elevation Satellite-1 (ICESat-1), the ICESat-2/Advanced Topographic Laser Altimeter System (ATLAS) employs a micro-pulse multi-beam photon counting approach to produce photon data for measuring global terrain. Few studies have assessed the accuracy of different ATLAS channels in retrieving ground topography in forested terrain. This study aims to assess the accuracy of measuring ground topography in forested terrain using different ATLAS channels and the correlation between laser intensity parameters, laser pointing angle parameters, and elevation error. The accuracy of ground topography measured by the ATLAS footprints is evaluated by comparing the derived Digital Terrain Model (DTM) from the ATL03 (Global Geolocated Photon Data) and ATL08 (Land and Vegetation Height) products with that from the airborne Light Detection And Ranging (LiDAR). Results show that the ATLAS product performed well in the study area at all laser intensities and laser pointing angles, and correlations were found between the ATLAS DTM and airborne LiDAR DTM (coefficient of determination––R2 = 1.00, root mean squared error––RMSE = 0.75 m). Considering different laser intensities, there is a significant correlation between the tx_pulse_energy parameter and elevation error. With different laser pointing angles, there is no significant correlation between the tx_pulse_skew_est, tx_pulse_width_lower, tx_pulse_width_upper parameters and the elevation error.

Digital Aerial Photogrammetry (DAP) and Airborne Laser Scanning (ALS) as Sources of Information about Tree Height: Comparisons of the Accuracy of Remote Sensing Methods for Tree Height Estimation

The rapid developments in the field of digital aerial photogrammetry (DAP) in recent years have increased interest in the application of DAP data for extracting three-dimensional (3D) models of forest canopies. This technology, however, still requires further investigation to confirm its reliability in estimating forest attributes in complex forest conditions. The main purpose of this study was to evaluate the accuracy of tree height estimation based on a crown height model (CHM) generated from the difference between a DAP-derived digital surface model (DSM) and an airborne laser scanning (ALS)-derived digital terrain model (DTM). The tree heights determined based on the DAP-CHM were compared with ground-based measurements and heights obtained using ALS data only (ALS-CHM). Moreover, tree- and stand-related factors were examined to evaluate the potential influence on the obtained discrepancies between ALS- and DAP-derived heights. The obtained results indicate that the differences between the means of field-measured heights and DAP-derived heights were statistically significant. The root mean square error (RMSE) calculated in the comparison of field heights and DAP-derived heights was 1.68 m (7.34%). The results obtained for the CHM generated using only ALS data produced slightly lower errors, with RMSE = 1.25 m (5.46%) on average. Both ALS and DAP displayed the tendency to underestimate tree heights compared to those measured in the field; however, DAP produced a higher bias (1.26 m) than ALS (0.88 m). Nevertheless, DAP heights were highly correlated with the heights measured in the field (R2 = 0.95) and ALS-derived heights (R2 = 0.97). Tree species and height difference (the difference between the reference tree height and mean tree height in a sample plot) had the greatest influence on the differences between ALS- and DAP-derived heights. Our study confirms that a CHM computed based on the difference between a DAP-derived DSM and an ALS-derived DTM can be successfully used to measure the height of trees in the upper canopy layer.

Slope stability and rockfall assessment of volcanic tuffs using RPAS with 2-D FEM slope modelling

Abstract. Steep, hardly accessible cliffs of rhyolite tuff in NE Hungary are prone to rockfalls, endangering visitors of a castle. Remote sensing techniques were employed to obtain data on terrain morphology and to provide slope geometry for assessing the stability of these rock walls. A RPAS (Remotely Piloted Aircraft System) was used to collect images which were processed by Pix4D mapper (structure from motion technology) to generate a point cloud and mesh. The georeferencing was made by Global Navigation Satellite System (GNSS) with the use of seven ground control points. The obtained digital surface model (DSM) was processed (vegetation removal) and the derived digital terrain model (DTM) allowed cross sections to be drawn and a joint system to be detected. Joint and discontinuity system was also verified by field measurements. On-site tests as well as laboratory tests provided additional engineering geological data for slope modelling. Stability of cliffs was assessed by 2-D FEM (finite element method). Global analyses of cross sections show that weak intercalating tuff layers may serve as potential slip surfaces. However, at present the greatest hazard is related to planar failure along ENE–WSW joints and to wedge failure. The paper demonstrates that RPAS is a rapid and useful tool for generating a reliable terrain model of hardly accessible cliff faces. It also emphasizes the efficiency of RPAS in rockfall hazard assessment in comparison with other remote sensing techniques such as terrestrial laser scanning (TLS).

Comparing RIEGL RiCOPTER UAV LiDAR Derived Canopy Height and DBH with Terrestrial LiDAR.

In recent years, LIght Detection And Ranging (LiDAR) and especially Terrestrial Laser Scanning (TLS) systems have shown the potential to revolutionise forest structural characterisation by providing unprecedented 3D data. However, manned Airborne Laser Scanning (ALS) requires costly campaigns and produces relatively low point density, while TLS is labour intense and time demanding. Unmanned Aerial Vehicle (UAV)-borne laser scanning can be the way in between. In this study, we present first results and experiences with the RIEGL RiCOPTER with VUX-1UAV ALS system and compare it with the well tested RIEGL VZ-400 TLS system. We scanned the same forest plots with both systems over the course of two days. We derived Digital Terrain Models (DTMs), Digital Surface Models (DSMs) and finally Canopy Height Models (CHMs) from the resulting point clouds. ALS CHMs were on average 11.5 higher in five plots with different canopy conditions. This showed that TLS could not always detect the top of canopy. Moreover, we extracted trunk segments of 58 trees for ALS and TLS simultaneously, of which 39 could be used to model Diameter at Breast Height (DBH). ALS DBH showed a high agreement with TLS DBH with a correlation coefficient of 0.98 and root mean square error of 4.24 . We conclude that RiCOPTER has the potential to perform comparable to TLS for estimating forest canopy height and DBH under the studied forest conditions. Further research should be directed to testing UAV-borne LiDAR for explicit 3D modelling of whole trees to estimate tree volume and subsequently Above-Ground Biomass (AGB).

Effective Acquisition Protocol of Terrestrial Laser Scanning for Underwater Topography in a Steep Mountain Channel

For better risk management, detailed and quantitative measurement of channel and stream-bed structure is required to understand and predict water and sediment flow in mountain channels. Our previous research demonstrated good performance of green-wavelength Terrestrial laser scanning (TLS) for measurement of submerged stream-bed in a steep mountain channel. This paper examines how the acquisition protocol of TLS affects the accuracy of data collected in the mountain channel. First, it was tested whether varying the scanner height, i.e., incident angle affects the data acquisition in terms of point density and accuracy in the pool unit of step-pool channel. Then, the effect of varying the minimum point spacing on the derived Digital terrain model (DTM) was examined. It was also analyzed whether a combination of multiple TLS data acquired from different directions would improve the accuracy of data compared to data acquired by a single measurement. Furthermore, TLS data were acquired over a cascade unit of the channel and examined whether TLS is capable of capturing reliable underwater data. All the acquired underwater data by TLS were corrected for water refraction and validated using manual surveyed data. The results showed that the accuracy of derived DTM was improved when the scanner height was increased or data was acquired from multiple directions, however, acquiring denser point cloud with a minimum point spacing of 1 mm did not improve the accuracy of the data. Accuracy of TLS measurement in the cascade unit was considerably lower. Special consideration is required for this area.

Shallow landslide susceptibility mapping using high-resolution topography for areas devastated by super typhoon Haiyan

Super typhoon Haiyan, considered as one of the most powerful storms recorded in 2013, devastated the central Philippines region on 8 November 2013 with damage amounting to more than USD 2 billion. Hardest hit is the province of Leyte which is located in central Philippines. Rehabilitation of the areas that were devastated requires detailed hazard maps as a basis for well-planned reconstruction. Along with severe wind, storm surge, and flood hazard maps, detailed landslide susceptibility maps for the cities and municipalities of Leyte (7246.7 km2) province are necessary. In order to rapidly assess and delineate areas susceptible to rainfall-induced shallow landslides, Stability INdex MAPping (SINMAP) software was used over a 5-m Interferometric Synthetic Aperture Radar (InSAR)-derived digital terrain model (DTM) grid. Topographic, soil strength, and hydrologic parameters were used for each pixel of a given DTM grid to compute for the corresponding factor of safety. The landslide maps generated using SINMAP are highly consistent with the landslide inventory derived from high-resolution satellite imagery from 2002 to 2014 with a detection percentage of 97.5 % and missing factor of 0.025. These demonstrate that SINMAP performs well despite the lack of an extensive geotechnical and hydrological database in the study area. The detailed landslide susceptibility classification is useful to identify safe and unsafe areas for reconstruction and rehabilitation efforts. These maps complement the debris flow and structurally controlled landslide hazard maps that are also being prepared for rebuilding Haiyan’s devastated areas.

Forest stand age classification using time series of photogrammetrically derived digital surface models

ABSTRACTIn this research, we developed and tested a remote sensing-based approach for stand age estimation. The approach is based on changes in the forest canopy height measured from a time series of photo-based digital surface models that were normalized to canopy height models using an airborne laser scanning derived digital terrain model (DTM). Representing the Karelian countryside, Finland, CHMs from 1944, 1959, 1965, 1977, 1983, 1991, 2003, and 2012 were generated and allow for characterization of forest structure over a 68-year period. To validate our method, we measured stand age from 90 plots (1256 m2) in 2014, whereby producer's accuracy ranged from 25.0% to 100.0% and user's accuracy from 16.7% to 100.0%. The wide range of accuracy found is largely attributable to the quality and characteristics of archival images and intrastand variation in stand age. The lowest classification accuracies were obtained for the images representing the earliest dates. For forest managers and agencies that have access to long-term photo archives and a detailed DTM, the estimation of stand age can be performed, improving the quality and completeness of forest inventory databases.

Prediction of Forest Stand Attributes Using TerraSAR-X Stereo Imagery

Consistent, detailed and up-to-date forest resource information is required for allocation of forestry activities and national and international reporting obligations. We evaluated the forest stand attribute prediction accuracy when radargrammetry was used to derive height information from TerraSAR-X stereo imagery. Radargrammetric elevations were normalized to heights above ground using an airborne laser scanning (ALS)-derived digital terrain model (DTM). Derived height metrics were used as predictors in the most similar neighbor (MSN) estimation approach. In total, 207 field measured plots were used in MSN estimation, and the obtained results were validated using 94 stands with an average area of 4.1 ha. The relative root mean square errors for Lorey’s height, basal area, stem volume, and above-ground biomass were 6.7% (1.1 m), 12.0% (2.9 m2/ha), 16.3% (31.1 m3/ha), and 16.1% (15.6 t/ha). Although the prediction accuracies were promising, it should be noted that the predictions included bias. The respective biases were −4.6% (−0.7 m), −6.4% (−1.6 m2/ha), −9.3% (−17.8 m3/ha), and −9.5% (−9.1 t/ha). With detailed DTM, TerraSAR-X stereo radargrammetry-derived forest information appears to be suitable for providing consistent forest resource information over large areas.

Evaluation of a LIDAR Land-Based Mobile Mapping System for Monitoring Sandy Coasts

The Dutch coast is characterized by sandy beaches flanked by dunes. Understanding the morphology of the coast is essential for defense against flooding of the hinterland. Because most dramatic changes of the beach and the first dune row happen during storms, it is important to assess the state of the coast immediately after a storm. This is expensive and difficult to organize with Airborne Laser Scanning (ALS). Therefore, the performance of a Land-based Mobile Mapping System (LMMS) in mapping a stretch of sandy Dutch coast of 6 km near the municipality of Egmond is evaluated in this research. A test data set was obtained by provider Geomaat using the StreetMapper LMMS system. Both the relative quality of laser point heights and of a derived Digital Terrain model (DTM) are assessed. First, the height precision of laser points is assessed a priori by random error propagation, and a posteriori by calculating the height differences between close-by points. In the a priori case, the result is a theoretical laser point precision of around 5 cm. In the a posteriori approach it is shown that on a flat beach a relative precision of 3 mm is achieved, and that almost no internal biases exist. In the second analysis, a DTM with a grid size of 1 m is obtained using moving least squares. Each grid point height includes a quality description, which incorporates both measurement precision and terrain roughness. Although some problems remain with the scanning height of 2 m, which causes shadow-effect behind low dunes, it is concluded that a laser LMMS enables the acquisition of a high quality DTM product, which is available within two days.

Non‐stationary Approaches for Mapping Terrain and Assessing Prediction Uncertainty

It is well known that terrain may vary markedly over small areas and that statistics used to characterise spatial variation in terrain may be valid only over small areas. In geostatistical terminology, a non‐stationary approach may be considered more appropriate than a stationary approach. In many applications, local variation is not accounted for sufficiently. This paper assesses potential benefits in using non‐stationary geostatistical approaches for interpolation and for the assessment of uncertainty in predictions with implications for sampling design. Two main non‐stationary approaches are employed in this paper dealing with (1) change in the mean and (2) change in the variogram across the region of interest. The relevant approaches are (1) kriging with a trend model (KT) using the variogram of residuals from local drift and (2) locally‐adaptive variogram KT, both applied to a sampled photogrammetrically derived digital terrain model (DTM). The fractal dimension estimated locally from the double‐log variogram is also mapped to illustrate how spatial variation changes across the data set. It is demonstrated that estimation of the variogram of residuals from local drift is worthwhile in this case for the characterisation of spatial variation. In addition, KT is shown to be useful for the assessment of uncertainty in predictions. This is shown to be true even when the sample grid is dense as is usually the case for remotely‐sensed data. In addition, both ordinary kriging (OK) and KT are shown to provide more accurate predictions than inverse distance weighted (IDW) interpolation, used for comparative purposes.