Vertical RMSE Research Articles

Design and Application Research of a UAV-Based Road Illuminance Measurement System

This paper presents a UAV-based road illumination measurement system and evaluates its performance through experiments. The system employs a HUBSAN Zino 2+ UAV, STM32F103RCT6 microcontroller, BH1750 illuminance sensor, and GPS and integrates flight, processing, measurement, cloud platform, obstacle avoidance, communication, and power supply units via the OneNET cloud platform. Both hardware and software designs were implemented, using the Z-score algorithm to handle outliers in illumination data. The system showed a single-point measurement error rate of 1.14% and a MAPE of 5.08% for multi-point measurements. In experiments, the system’s horizontal and vertical illuminance RMSE were 1.92 lx and 1.75 lx, respectively. The real-time visualization interface improved operational efficiency, cutting labor costs by half and time costs by nearly four-fifths. UAV control and monitoring from the roadside ensured safety during measurements. The system’s efficiency and wide measurement range enabled extended experiments, collecting illuminance data across multiple horizontal and vertical planes. This resulted in the creation of both horizontal and innovative vertical-plane illuminance distribution maps. These findings provide valuable data for evaluating road lighting quality, enhancing road traffic safety, and improving road illumination design.

Effects of camera calibration on the accuracy of Unmanned Aerial Vehicle sensor products

Utilization of Unmanned Aerial Vehicles (UAV) mounted with non-metric consumer grade digital cameras is on the rise globally due to their affordability and ease of operation. For high-accuracy UAV products, there is a need for accurate camera parameters determined through camera calibration. Camera calibration can be performed before (pre-calibration) or during the bundle block adjustment (self-calibration). This study aims to analyze the effect of camera calibration parameters on the accuracy of UAV products namely Digital Elevation Model (DEM) and orthoimage. Camera calibration parameters are estimated using two approaches namely self-calibration which deploys 3D image information of the scene in a bundle adjustment and a 2D reference object-based approach known as Zhang’s technique which requires image information of a planar pattern. A DJI FC220 camera mounted on a DJI Mavic Pro UAV was used. Self-calibration was deployed in Agisoft Metashape software based on Brown’s method and Zhang’s technique was deployed in MATLAB and OpenCV. Based on internal measures of accuracy, OpenCV yields the least reprojection error of 0.14 followed by MATLAB (0.79) and self-calibration (1.21). Processing without calibration yields the highest reprojection error of 2.18. Based on external measures of accuracy, that is the geometric accuracy of UAV products, self-calibration yields the least RMSE of 8.2 and 1.4 cm, for the horizontal and vertical, respectively, followed by Zhang’s technique with 9.6 and 2.3 cm in MATLAB and 13.5 and 4.3 cm in OpenCV. Processing without calibration yields the highest vertical RMSE of 20.0 and 22.9 cm for the horizontal and vertical, respectively. Comparison of accuracy of UAV mapping products computed with and without calibration emphasizes the need for camera calibration to optimize accuracy of UAV products. This study recommends assessing other photogrammetric mapping software and camera calibration approaches and the effect of flying heights on calibration parameters and mapping accuracy.

UAV Photogrammetry in Intertidal Mudflats: Accuracy, Efficiency, and Potential for Integration with Satellite Imagery

The rapid, up-to-date, cost-effective acquisition and tracking of intertidal topography are the fundamental basis for timely, high-priority protection and restoration of the intertidal zone. The low cost, ease of use, and flexible UAV-based photogrammetry have revolutionized the monitoring of intertidal zones. However, the capability of the RTK-assisted UAV photogrammetry without ground control points, the impact of flight configuration difference, the presence of surface water in low-lying intertidal areas on the photogrammetric accuracy, and the potential of UAV/satellite Synergy remain unknown. In this paper, we used an RTK-assisted UAV to assess the impact of the above-mentioned considerations quantitatively on photogrammetric results in the context of annual monitoring of the Chongming Dongtan Nature Reserve, China based on an optimal flight combination. The results suggested that (1) RTK-assisted UAVs can obtain high-accuracy topographic data with a vertical RMSE of 3.1 cm, without the need for ground control points. (2) The effect of flight altitude on topographic accuracy was most significant and also nonlinear. (3) The elevation obtained by UAV photogrammetry was overestimated by approximately 2.4 cm in the low-lying water-bearing regions. (4) The integration of UAV and satellite observations can increase the accuracy of satellite-based waterline methods by 51%. These quantitative results not only provide scientific insights and guidelines for the balance between accuracy and efficiency in utilizing UAV-based intertidal monitoring, but also demonstrate the great potential of combined UAV and satellite observations in identifying coastal erosion hotspots. This establishes high-priority protection mechanisms and promotes coastal restoration.

Applying UAV-Based Remote Sensing Observation Products in High Arctic Catchments in SW Spitsbergen

In the age of remote sensing, particularly with new generation Uncrewed Aerial Vehicles (UAVs), there is a broad spectrum of applications, especially in remote and rapidly changing areas such as the Arctic. Due to challenging conditions in this region, there is a scarcity of detailed spatial studies with data that may be used to estimate changes in glacier volume and geomorphological changes caused by permafrost freeze–thaw cycles. Drone-based Digital Elevation Models (DEM) offer a finer spatial resolution with higher accuracy than airborne and satellite-based products that can be used for acquiring, interpreting, and precisely representing spatial data in broad studies. In this study, we evaluate a UAV-based DEM of two High Arctic catchments, Fuglebekken and Ariebekken, located on Spitsbergen Island. The surveys were carried out in July 2022 using a DJI Matrice 300 RTK drone equipped with a photogrammetric Zenmuse P1 camera. A total of 371 images were taken, covering an area of 7.81 km2. The DEM was created by the Structure-from-Motion technique and achieved a centimetre-level accuracy by overlapping very high-resolution images. The final resolution of the DEM was found to be 0.06 m in Fuglebekken and 0.07 m in Ariebekken, with a horizontal and vertical RMSE of 0.09 m and 0.20 m, respectively. The DJI Matrice 300 RTK drone-based DEM is compared and correlated with the aerial mission of the Svalbard Integrated Arctic Earth Observing System (SIOS) conducted in July 2020 and the satellite-based ArcticDEM acquired in July 2018. This allowed the detection of elevation changes and identification of landscape evolution, such as moraine breaches and coastal erosion. We also highlight the usage of DEM in providing detailed morphometric characteristics and hydrological parameters, such as the delineation of catchments and stream channels. The final products are available at the IG PAS Data Portal.

Horizontal And Vertical Measurement of UAV Aerial Photo Exposures Results In The Senowo River Area, Krinjing Village, of The Merapi Volcano, Magelang District of Central Java Indonesia

This study aims to examine the acquisition of small format aerial photography with UAVs and to display orthophoto data for elevation data extraction. The research area was conducted in a part of the Senowo River north of Merapi volcano in Central Java. The Photogrammetric methods using UAV planes need to be done for horizontal and vertical accuracy studies. This accuracy study was carried out by referring to the height of the flying plane and the geometry accuracy of the Rupa Bumi Indonesia (RB I= Standardized Topographic Map of Indonesia) map. The results of this study are accuracy testing based on the comparison of the coordinates of the test points with the results of aerial photo processing obtained by horizontal RMSE of 0.034 meter and vertical RMSE of 0.598 meter with an accuracy of 98%. RMSE value is used to determine the value of Circural Error 90 (CE90) and Linear Error (LE90). The value obtained by CE90 is 0.25 meter and the LE90 value is 0.99 meter. The accuracy of the orthophoto map that can be made is a scale of 1: 2,500 in class 1st for horizontal accuracy and a scale of 1: 5,000 in class 1st for vertical accuracy. Therefore, in the selection of optimal scale orthophoto maps, the recommended scale is 1: 5,000.* PT. Wijaya Karya Jakarta Indonesia**Assc. Prof. of the Geography Department of Social Science Faculty UM

Applicability of the global TanDEM-X elevation data for terrain modelling of a forested karst area: a case study from Slovak Karst

New interferometric radar data of the TanDEM-X space mission have become recently available as a global digital elevation model providing 0.4 arc second spatial resolution (ca. 12 meters). The TanDEM-X dataset brings new options into geoscientific research across multiple scales. However, the accuracy and suitability of this data have not been evaluated in such an extensive manner as, for example, the widely used SRTM data which resolution is 1 arc second (ca. 30 m). We present a validation of the vertical accuracy of TanDEM-X DEM product and an evaluation of its suitability for landform classification in a forested karst area. The DEM segmentation using geomorphons was used for the automated object-based landform classification. We focused on the identification of dolines for which polygons of dolines mapped by an expert-driven approach were used for validation. Airborne lidar data in the form of DSM and DTM were used as the reference dataset for validation of the TanDEM-X DEM vertical accuracy. The results from the study area show that the vertical RMSE of the TanDEM-X data is 3.42 m with respect to the lidar DSM and 9.64 m in comparison with lidar DTM. The identification of dolines by the geomorphon approach achieved 73 % with TanDEM-X, lower than for the lidar DTM (85 %). The TanDEM-X elevation errors were strongly correlated with the canopy height derived from the lidar data suggesting limited suitability of the TanDEM-X data for mapping fine-scale geomorphological features under forests while there was a good match with the lidar DTM terrain in open areas. URL: https://www.gcass.science.upjs.sk/

A fully automated method for monitoring the intertidal topography using Video Monitoring Systems

Coastal systems are extremely dynamic environments exposed to many hazards, making accurate and regular monitoring a major challenge, particularly in the context of global change and sea level rise. In this frame of reference, high-frequency, high-resolution coastal Video Monitoring Systems (VMS) have been installed on three megatidal (tidal amplitude > 9 m) sites of Normandy (France) including a sandy beach at Villers-sur-Mer, a pebble beach at Etretat and a composite beach at Hautot-sur-Mer. This article proposes the use of Mask R–CNN to process images acquired at these sites and perform the automatic segmentation of the visible bodies of water in order to extract the waterline. The extracted waterlines are associated with a measured water level, which makes it possible to reconstruct the topography of the beaches at the scale of the tidal cycle. After training the neural network on manually labeled data, the segmentation by Mask R–CNN is very efficient by achieving a satisfactory segmentation on 69.87% of the images of Villers-sur-Mer, on 67.11% at Hautot-sur-Mer, and on 97.33% at Etretat. Once the waterlines have been extracted and georeferenced, the reproduction of the beaches’ morphology is satisfactory (averaged vertical RMSE = 28 cm). These results confirm that segmentation by Mask R–CNN is a particularly powerful tool that allows efficient and low-cost monitoring of the evolution of beach morphology, particularly in response to marine conditions. Its capabilities to detect and segment bodies of water while not being affected by the various sources of noise make it a notably effective tool for coastal science applications.

Evidence of inverted gravity-driven variation in predictive sensorimotor function.

We move our eyes to place the fovea into the part of a viewed scene currently of interest. Recent evidence suggests that each human has signature patterns of eye movements like handwriting which depend on their sensitivity, allocation of attention and experience. Use of implicit knowledge of how earth's gravity influences object motion has been shown to aid dynamic perception. We used a projected ball-tracking task with a plain background offering no context cues to probe the effect of acquired experience about physical laws of gravitation on performance differences of 44 participants under a simulated gravity and an atypical (upward) antigravity condition. Performance measured by the unsigned difference between instantaneous eye and stimulus positions (RMSE) was consistently worse in the antigravity condition. In the vertical RMSE, participants took about 200ms longer to improve to the best performance for antigravity compared to gravity trials. The antigravity condition produced a divergence of individual performance which was correlated with levels of questionnaire-based quantified traits of schizotypy but not control traits. Grouping participants by high or low traits revealed a negative relationship between schizotypy trait level and both initiation and maintenance of tracking, a result consistent with trait-related impoverished sensory prediction. The findings confirm for the first time that where cues enabling exact estimation of acceleration are unavailable, knowledge of gravity contributes to dynamic prediction improving motion processing. With acceleration expectations violated, we demonstrate that antigravity tracking could act as a multivariate diagnostic window into predictive brain function.

Mapping erosion and deposition in an agricultural landscape: Optimization of UAV image acquisition schemes for SfM-MVS

Structure-from-motion (SfM) and multi-view stereo (MVS) algorithms coupled with the use of unmanned aerial vehicles (UAVs) have become a popular tool in the geosciences for modelling complex landscapes on-demand allowing for high-resolution topographic change-detection studies to be conducted at minimal cost. To identify the effects of UAV image orientation on the accuracy of SfM-MVS 3D surface models, we tested four different UAV image acquisition schemes that incorporated both nadir and oblique imagery of an agricultural field. The coupling of nadir and oblique imaging angles led to the highest surface model accuracy in the absence of ground control points (GCPs; vertical RMSE: 0.047 m, horizontal RMSE: 0.019 m), while with a normative distribution of GCPs the nadir-only image sets had similar accuracy metrics (vertical RMSE 0.028 m, horizontal RMSE 0.017 m) to surface models generated with nadir and oblique imaging angles (vertical RMSE 0.028 m, horizontal RMSE 0.013 m). Homologous keypoint matching between nadir and oblique imagery was poor when the survey conditions were bright and the surface texture of the field was homogeneous, leading to broad-scale vertical noise in the generated surface models. Results indicate that a nadir-only image set accompanied with a dense deployment of GCPs is the most ideal for SfM-MVS agricultural 3D surface reconstructions. The diachronic analysis of surface models generated from nadir-only image sets were able to detect surface-change >0.040 m in depth (i.e., rill and gully erosion, depositional zones) and were comparable to results obtained from a terrestrial laser scanner. Stable GCPs should be used where possible to ensure precise co-registration between subsequent UAV surveys.

Comparison analysis of accuracy and precision on GNSS K706 Oem Board and GPS Topcon HiperPro

GNSS technology has been widely used in the field of surveys and mapping. According to Abidin this is because GNSS can be used regardless of time, is not affected by the topography of the survey area, and provides accuracy with a wide spectrum. GNSS technology also has several disadvantages, one of which is price. The tool used to implement GNSS technology has a high price, for example is the geodetic type which has prices ranging from hundreds of millions of rupiah. The last few years have found low-cost GNSS. which has a cheaper price. To find out the quality of low-cost GNSS a test was carried out. In this study a low-cost GN70 Oem Board was tested.This study focuses on testing accuracy and precision. The method used for testing is RTK, and Static for data as a reference. RTK data acquisition uses the NTRIP method with CORS Surabaya as the base. There are 3 test locations in this study. The first is in BM01ITS or “bits”. Both the ITS Stadium or “bstd”, and third Sakura Park or “bskr”.Horizontal and vertical deviation standards on the K706 OEM board has better quality than Topcon HiperPro. This is evidenced by the standard deviation of the K706 superior in 4 research points, while HiperPro only excels at two research points. Horizontal RMSE both devices have the same quality. This is evidenced by the RMSE of the K706 superior in 3 research points, and HiperPro excels in 3 research points. For vertical RMSE, the K706 is better than HiperPro. This is evidenced by the standard deviation of the K706 superior in 5 research points, while HiperPro only excels at one research point.

Canopy and Terrain Height Retrievals with ICESat-2: A First Look

NASA’s Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) launched in fall 2018 and has since collected continuous elevation data over the Earth’s surface. The primary scientific objective is to measure the cryosphere for studies related to land ice and sea ice characteristics. The vantage point from space, however, provides the opportunity to measure global surfaces including oceans, land, and vegetation. The ICESat-2 mission has dedicated products to the represented surface types, including an along-track elevation profile of terrain and canopy heights (ATL08). This study presents the first look at the ATL08 product and the quantitative assessment of the canopy and terrain height retrievals as compared to airborne lidar data. The study also provides qualitative examples of ICESat-2 observations from selected ecosystems to highlight the broad capability of the satellite for vegetation applications. Analysis of the mission’s preliminary ATL08 data product accuracy using an ICESat-2 transect over a vegetated region of Finland indicates a 5 m offset in geolocation knowledge (horizontal accuracy) well within the 6.5 m mission requirement. The vertical RMSE for the terrain and canopy height retrievals for one transect are 0.85 m and 3.2 m respectively.

Estimating Discharge in Low‐Order Rivers With High‐Resolution Aerial Imagery

AbstractRemote sensing of river discharge promises to augment in situ gauging stations, but the majority of research in this field focuses on large rivers (>50 m wide). We present a method for estimating volumetric river discharge in low‐order (<50 m wide) rivers from remotely sensed data by coupling high‐resolution imagery with one‐dimensional hydraulic modeling at so‐called virtual gauging stations. These locations were identified as locations where the river contracted under low flows, exposing a substantial portion of the river bed. Topography of the exposed river bed was photogrammetrically extracted from high‐resolution aerial imagery while the geometry of the remaining inundated portion of the channel was approximated based on adjacent bank topography and maximum depth assumptions. Full channel bathymetry was used to create hydraulic models that encompassed virtual gauging stations. Discharge for each aerial survey was estimated with the hydraulic model by matching modeled and remotely sensed wetted widths. Based on these results, synthetic width‐discharge rating curves were produced for each virtual gauging station. In situ observations were used to determine the accuracy of wetted widths extracted from imagery (mean error 0.36 m), extracted bathymetry (mean vertical RMSE 0.23 m), and discharge (mean percent error 7% with a standard deviation of 6%). Sensitivity analyses were conducted to determine the influence of inundated channel bathymetry and roughness parameters on estimated discharge. Comparison of synthetic rating curves produced through sensitivity analyses show that reasonable ranges of parameter values result in mean percent errors in predicted discharges of 12%–27%.

Control quality of open source Digital Elevation Models (DEMs) in Tunisia

Digital Elevation Models (DEMs) are an invaluable source of information in large area studies. Some of the DEMs such as Advanced Spaceborne Thermal Emission Radiometer-Global Digital Elevation Model (ASTER GDEM), shuttle radar topography mission (SRTM), and Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) are freely available for the scientific community worldwide. Prior to any application, global datasets of DEMs should be evaluated using reference data of higher accuracy. Therefore, the main objective of this study is to assess the quality of the ASTER GDEM (version 2), SRTM (version 4) and systematic subsample GMTED2010 in Tunisia. The validation process, adopted here, is based on two main approaches: internal and external validations. The internal validation is achieved by performing visual inspection of shaded relief images extracted from the three DEMs. At this level, results show that SRTM is essentially similar to ASTER GDEM2 in term of relief features representation. In the second alternative, the vertical accuracy of each DEM is evaluated using 60 Global Positioning System (GPS) validation points. The overall vertical accuracy shows RMSE error of 11.96 m, 8.65 m and 10.86 m for ASTER GDEM2, SRTM and GMTED2010 DEM respectively, in comparison with GPS elevation points.

Modelling turbulent vertical mixing sensitivity using a 1-D version of NEMO

Abstract. Through two numerical experiments, a 1-D vertical model called NEMO1D was used to investigate physical and numerical turbulent-mixing behaviour. The results show that all the turbulent closures tested (k+l from Blanke and Delecluse, 1993, and two equation models: generic length scale closures from Umlauf and Burchard, 2003) are able to correctly reproduce the classical test of Kato and Phillips (1969) under favourable numerical conditions while some solutions may diverge depending on the degradation of the spatial and time discretization. The performances of turbulence models were then compared with data measured over a 1-year period (mid-2010 to mid-2011) at the PAPA station, located in the North Pacific Ocean. The modelled temperature and salinity were in good agreement with the observations, with a maximum temperature error between −2 and 2 °C during the stratified period (June to October). However, the results also depend on the numerical conditions. The vertical RMSE varied, for different turbulent closures, from 0.1 to 0.3 °C during the stratified period and from 0.03 to 0.15 °C during the homogeneous period. This 1-D configuration at the PAPA station (called PAPA1D) is now available in NEMO as a reference configuration including the input files and atmospheric forcing set described in this paper. Thus, all the results described can be recovered by downloading and launching PAPA1D. The configuration is described on the NEMO site (http://www.nemo-ocean.eu/Using-NEMO/Configurations/C1D_PAPA). This package is a good starting point for further investigation of vertical processes.

The potential of small unmanned aircraft systems and structure-from-motion for topographic surveys: A test of emerging integrated approaches at Cwm Idwal, North Wales

Novel topographic survey methods that integrate both structure-from-motion (SfM) photogrammetry and small unmanned aircraft systems (sUAS) are a rapidly evolving investigative technique. Due to the diverse range of survey configurations available and the infancy of these new methods, further research is required. Here, the accuracy, precision and potential applications of this approach are investigated. A total of 543 images of the Cwm Idwal moraine–mound complex were captured from a light (<5kg) semi-autonomous multi-rotor unmanned aircraft system using a consumer-grade 18 MP compact digital camera. The images were used to produce a DSM (digital surface model) of the moraines. The DSM is in good agreement with 7761 total station survey points providing a total vertical RMSE value of 0.517m and vertical RMSE values as low as 0.200m for less densely vegetated areas of the DSM. High-precision topographic data can be acquired rapidly using this technique with the resulting DSMs and orthorectified aerial imagery at sub-decimetre resolutions. Positional errors on the total station dataset, vegetation and steep terrain are identified as the causes of vertical disagreement. Whilst this aerial survey approach is advocated for use in a range of geomorphological settings, care must be taken to ensure that adequate ground control is applied to give a high degree of accuracy.

장애물 위치에 따른 GPS 기준국 측위정확도 변화분석

이 연구에서는 GPS 기준국 주변에 존재하는 장애물의 방향과 고도각이 좌표 정확도 변화에 미치는 영향을 시뮬레이션을 통해 분석하고자 한다. 최적의 관측환경에 있는 기준국의 정밀좌표를 산출한 뒤 고도각 <TEX>$10^{\circ}$</TEX>부터 <TEX>$70^{\circ}$</TEX>까지의 장애물이 동, 서, 남 방향에 각각 존재한다고 가정하고 관측자료를 재구성하였다. 10일간의 관측자료를 이용하여 일단위와 시간단위로 각각 처리하였다. 일단위 처리결과에서는 RMSE가 10mm 내외였으나 시간단위 결과에서는 100mm 수준까지 증가하였다. 장애물의 고도각이 높아질수록 수평 및 수직방향 RMSE는 증가하였고 높이 추정값은 감소하였다. 방향에 따른 분석에서는 동쪽이나 서쪽에 장애물이 존재할 때 남북방향에 비해 동서방향으로 위치오차가 더 크게 증가하였고 남쪽 장애물인 경우에는 동서방향의 오차폭이 상대적으로 작게 나타났다. This paper focuses on GPS positioning accuracy variations according to locations of obstacles which surround GPS station. We derived precise coordinates of a GPS station which has a good visibility. Its observation data was rewritten by assuming signal blocking due to obstacle in the elevation angle of <TEX>$10^{\circ}$</TEX> to <TEX>$70^{\circ}$</TEX>. We processed daily and hourly data for 10 days. In the results using daily data, RMSE was at 10mm level. And RMSE increased to 100mm levels in case of hourly data. As the elevation angle of obstacle increased, the horizontal and vertical RMSE increased, while the height estimates decreased. These results showed the higher the elevation angle of the obstacle increased the loss of large amounts of data by blocking satellite signals direction. In terms of the direction, when the blocking thing was located in the east or west, the coordinate has larger error in the east-west direction. And if signal was blocked at the south direction, the difference between the east-west error and the south-north position error was reduced.

Comparison of Automatic DSM Generation Modules by Processing IKONOS Stereo Data of an Urban Area

This study deals with the evaluation of four different image-processing software modules for the generation of digital surface models from very high-resolution stereo satellite data. The analysis was done in an urban area due to the growing interest in 3-D information over built-up areas. Depending on the different geometric model approaches used by the different software packages, shifts between 3.06-3.27 m between the digital surface models (DSMs) and the reference DSM were measured. The vertical RMSE of the four tested software packages range between 2.96-14.01 m. However, the visual evaluation resulted in a different ranking and does not confirm the quantitative results entirely. The results show that, depending on the building type to be extracted, the choice of software package may vary. The challenges of automatic DSM extraction in urban areas and the performance of current software package modules to address them are discussed. Potential improvements for automatic DSM extraction in urban areas are identified.

Influence of Vegetation, Slope, and Lidar Sampling Angle on DEM Accuracy

Detailed GIS studies across spatially complex rangeland landscapes, including the Aspen Parkland of western Canada, require accurate digital elevation models (DEM). Following the interpolation of last return lidar (light detection and ranging) data into a DEM, a series of 256 reference plots, stratified by vegetation type, slope and lidar sensor sampling angle, were surveyed using a total laser station, differential GPS and 27 interconnected benchmarks to assess variation in DEM accuracy. Interpolation using Inverse Distance Weighting IDW resulted in lower mean error than other methods. Across the study area, overall signed error and RMSE were � 0.02 m and 0.59 m, respectively. Signed errors indicated elevations were over-estimated in forest but under-estimated within meadow habitats. Increasing slope gradient increased vertical absolute errors and RMSE. In contrast, lidar sampling angle had little impact on measured error. These results have implications for the development and use of high-resolution DEM models derived from lidar data.