Quality Of Digital Terrain Model Research Articles

Accuracy and hydrographic realism of an under-forest DEM derived from airborne P-band radar interferometry over a wide area in the Brazilian amazon

ABSTRACT P-band radar interferometry is a promising tool for digital terrain modelling in forested areas such as the Amazon due to the ability of P-band to penetrate densely forested areas. The quality of Digital Terrain Models (DTMs) is a primary requirement for many geoscience applications because DTM accuracy is an essential variable for characterizing landform shapes. This article presents a multicriteria evaluation of the overall quality of a digital terrain model produced using P-band SAR interferometric processing. The evaluation considers behaviours related to elevation and slope and analyses the impact of landscape properties such as slope and aspect. The multicriteria accuracy of the study showed promising results about the realism of landforms, according to applied geomorphological criteria, and also in the visual comparison between the produced DTM and the reference. The study provided an estimate of the accuracy of P-band radar DTM in terms of elevation with a standard deviation of 2.36 m and in terms of slope with a mean error of approximately −4°, a standard deviation of 4.74°, and a RMSE (Root Mean Square Error) slope error of 6.14°, using a reference DTM derived from an airborne LiDAR (Light Detection and Ranging) survey. The spatial behaviour of these errors and their sensitivity to slope and aspect were analysed. The investigation of hydrographic inconsistencies in the DTM was conducted based on various criteria, including identifying depressions along watercourses and adhering to Horton’s law. Finally, the effects of the acquisition, processing, and resampling processes are revealed through indicators such as the rose histogram. This multicriteria study demonstrates the suitability of airborne P-band radar interferometry for digital elevation modelling in tropical rainforest environments.

Assessment of the influence of DTM quality on dam rupture simulation processes

Computer programs applied to disaster simulation are widely used and widespread today, taking as input various data types, from specific to the application area to DTMs (Digital Terrain Models). This need for data input and, in particular, data related to relief is very relevant in prediction procedures for forecasting catastrophes, such as the failure of tailings mining deposit dams. Therefore, it is of fundamental importance to know and quantify the quality of this input data in question, in order to effectively serve this application. To this end, in this research, several tests were carried out, using as a reference for best results those obtained with the introduction of DTM from a LIDAR (Light Detection and Ranging) flight survey, this data being used as one of the primary and input into HEC-RAS (Hydrologic Engineering Center-River Analysis System). Subsequently, these same data had their spatial resolution degraded, that is, the pixel size increased, generating models with worse quality for new inputs and obtaining new simulation results of mining dam failures. The test area of the B1 Dam, located in Brumadinho-MG, Brazil, was used as a laboratory, where one of the biggest mining disasters in the world recently occurred and, for which, there are real data from the area affected by the dam collapse. The results obtained demonstrated that the use of an DTM with a spatial resolution of at least 2.5 meters or better, with DTM class A cartographic quality compatible with the most recent Brazilian standard, would guarantee reliable results.

Sensitivity Testing of Stereophotoclinometry for the OSIRIS-REx Mission. II. Effective Observation Geometry for Digital Terrain Modeling

The OSIRIS-REx mission used stereophotoclinometry (SPC) to generate digital terrain models (DTMs) of its target asteroid, Bennu. Here we present a suite of preflight tests conducted to identify the observing geometry and number of images needed to create DTMs that would enable successful navigation around and to the surface of the asteroid. We demonstrate that high-quality DTMs can be generated by using only five images: four that are focused on topography, in which the spacecraft’s viewing geometry brackets the target (north, south, east, and west), and a fifth that measures the target’s albedo variation, taken from near local noon. We further show that the first 10 iterations of the SPC process can meaningfully improve DTM quality, including in the case of a suboptimal input image set, whereas after 10 iterations the DTM quality approaches an asymptotic maximum. We distill our findings into recommendations for observation planning that can be applied by other missions intending to use SPC to model the shape and terrain of their target.

Sensitivity Testing of Stereophotoclinometry for the OSIRIS-REx Mission. I. The Accuracy and Errors of Digital Terrain Modeling

Stereophotoclinometry (SPC) was the prime method of shape modeling for NASA’s OSIRIS-REx mission to asteroid Bennu. Here we describe the extensive testing conducted before launch to certify SPC as NASA Class B flight software, which not only validated SPC for operational use but also quantified the accuracy of this technique. We used a computer-generated digital terrain model (DTM) of a synthetic asteroid as the truth input to render simulated truth images per the planned OSIRIS-REx observing campaign. The truth images were then used as input to SPC to create testing DTMs. Imaging sets, observational parameters, and processing techniques were varied to evaluate their effects on SPC's performance and their relative importance for the quality of the resulting DTMs. We show that the errors in accuracy for SPC models are of the order of the source images’ smallest pixel sizes and that a DTM can be created at any scale, provided there is sufficient imagery at that scale. Uncertainty in the spacecraft’s flight path has minimal impact on the accuracy of SPC models. Subtraction between two DTMs (truth and simulated) is an effective approach for measuring error but has limitations. Comparing the simulated truth images with images rendered from the SPC-derived DTMs provides an excellent metric for DTM quality at smaller scales and can also be applied in flight by using real images of the target. SPC has limitations near steep slopes (e.g., the sides of boulders), leading to height errors of more than 30%. This assessment of the accuracy and sensitivity of SPC provides confidence in this technique and lessons that can be applied to future missions.

The methods of modeling the terrain of fields for precision farming technologies

According to aerial photography and two models of GPS receivers, the digital models of the slope were built using the "ArcGIS" tools. The comparison of the quality of digital terrain models created with use of three sources was carried out in this paper. The data obtained from GPS receivers have a significant altitude error; however, taking this factor into account, new equipment determines the location of a point in space more accurately, minimizing sharp altitude indicators. The quality of terrain models depends on the model of GPS receiver and the number of points, but anyway aerial photography is the best source for creating digital terrain models. Although it has a high accuracy of output data, it is worth considering that this method is very expensive. The resulting models can be used to design elements of precision farming technology.

Improvements to airborne laser scanning data filtering in sandstone landscapes

Sandstone rock outcrops form a unique part of the landscape of Central Europe. Due to climate conditions, they are mostly covered by dense vegetation. With some limitations, laser scanning technology allows the ground to be captured even under the tree canopy, making it a powerful tool for mapping vegetated and inaccessible terrain. A challenge in deriving a digital terrain model from an acquired point cloud lies in filtering, i.e., discrimination between ground and non-ground points. Conventional filtering methods applied on complex high-energy terrain with formations resembling man-made objects, e.g., rock walls, do not provide satisfactory results with respect to the accuracy of point assignment to ground and non-ground classes and consequently terrain modelling. However, the quality of digital terrain models is critical for geomorphometric applications and recognition of spatial patterns. This study proposes three filtering methods adapted to various morphological conditions of sandstone landscape regions i.e., spatially conditioned filtering, object-oriented classification, and filtering with additional terrain data. Spatially conditioned filtering is based on a well-known method of triangulated irregular network densification, but it adjusts selected parameters in an iterative way. This has been proven to be successful in filtering sandstone rocks by the application of distinct sets of parameters to areas with and without rock formations. Object-oriented classification distinguishes between rock pillars and trees in rock cities based on features describing the distribution of points inside these objects. The method achieved an overall accuracy of 85 % with respect to manually filtered data and outperformed the conventional methods. Filtering with additional terrain data requires already filtered and co-registered references for spatial querying. Evaluation by GNSS measurements showed that the digital terrain model derived using this method achieved a higher accuracy than that derived by conventional methods.

Revealing Active Mars with HiRISE Digital Terrain Models

Many discoveries of active surface processes on Mars have been made due to the availability of repeat high-resolution images from the High Resolution Imaging Science Experiment (HiRISE) onboard the Mars Reconnaissance Orbiter. HiRISE stereo images are used to make digital terrain models (DTMs) and orthorectified images (orthoimages). HiRISE DTMs and orthoimage time series have been crucial for advancing the study of active processes such as recurring slope lineae, dune migration, gully activity, and polar processes. We describe the process of making HiRISE DTMs, orthoimage time series, DTM mosaics, and the difference of DTMs, specifically using the ISIS/SOCET Set workflow. HiRISE DTMs are produced at a 1 and 2 m ground sample distance, with a corresponding estimated vertical precision of tens of cm and ∼1 m, respectively. To date, more than 6000 stereo pairs have been acquired by HiRISE and, of these, more than 800 DTMs and 2700 orthoimages have been produced and made available to the public via the Planetary Data System. The intended audiences of this paper are producers, as well as users, of HiRISE DTMs and orthoimages. We discuss the factors that determine the effective resolution, as well as the quality, precision, and accuracy of HiRISE DTMs, and provide examples of their use in time series analyses of active surface processes on Mars.

Overlap influence in images obtained by an unmanned aerial vehicle on a digital terrain model of altimetric precision

ABSTRACT Photogrammetric data are systematically used in several segments. Products such as Digital Terrain Models (DTMs) provide detailed surface information, however the geometric reliability of these products is questionable compared to data collected by topographic survey by GNSS RTK. The present research assesses the quality of DTMs obtained using an Unmanned Aerial Vehicle (UAV) with different parameters, overlap percentages, and flight directions, comparing the results to those of the topography method Global Navigation Satellite System – Real-Time Kinematic (GNSS RTK). Were done twelve flight plans with different overlaps (90x90, 80x80, 80x60, 70x50, 70x30, and 60x40%) and directions (transverse and longitudinal to the planting line). The parameters of height (Above Ground Land- AGL) and speed were fixed at 90 m and 3 m/s respectively and a Ground Sample Distance (GSD) of 0,1 m is obtained for all flights. Overall, the flight with 70x50% overlap in the transverse direction generated the best results, with a total processing time of 12 minutes and 17 seconds (about 1.5 hours faster than 90x90%), an Root Mean Square Error (RMSE) 0.589 m, and meets the minimum overlap required by 60X30% aerophotogrammetry; furthermore, the results did not differ statistically from the high overlaps of 90x90% and 80x80%.

Digital Terrain Modelling by Remotely Piloted Aircraft: Optimization and Geometric Uncertainties in Precision Coffee Growing Projects

The implantation of coffee crop plantations requires cartographic data for dimensioning areas and planning the planting line. Digital terrain models (DTMs) obtained from remotely piloted aircraft (RPA) can contribute to efficient data collection for topography making this technique applicable to precision coffee projects. Aiming to achieve efficiency in the collection, processing and photogrammetric products quality, flight configurations and image processing were evaluated. Two hundred sixty-five points obtained by Global Navigation Satellite System (GNSS) receivers characterized the topographic surface. Then eighteen flight missions were carried out by RPA in the configurations of altitude above ground level (AGL) and frontal and lateral image overlay. In addition, different point cloud formats evaluated the image processing (time) efficiency in DTM. Flights performed at 120 m AGL and 80 × 80% overlap showed higher assertiveness and efficiency in generation DTMs. The 90 m AGL flight showed great terrain detail, causing significant surface differences concerning the topography obtained by GNSS. An increase in image overlap requires longer processing times, not contributing linearly to the geometric quality of orthomosaic. Slope ranges up to 20% are considered reliable for precision coffee growing projects; above 20% overestimates the slope values of the land. Changes in flight settings and image processing are satisfactory for precision coffee projects. Image overlap reduction was significant in reducing the processing time without influencing the quality of the DTMs. In addition, image processing performed in shallow point clouds did not interfere with the DTMs quality.

How Well Do We Know Europa’s Topography? An Evaluation of the Variability in Digital Terrain Models of Europa

Jupiter’s moon Europa harbors one of the most likely environments for extant extraterrestrial life. Determining whether Europa is truly habitable requires understanding the structure and thickness of its ice shell, including the existence of perched water or brines. Stereo-derived topography from images acquired by NASA Galileo’s Solid State Imager (SSI) of Europa are often used as a constraint on ice shell structure and heat flow, but the uncertainty in such topography has, to date, not been rigorously assessed. To evaluate the current uncertainty in Europa’s topography we generated and compared digital terrain models (DTMs) of Europa from SSI images using both the open-source Ames Stereo Pipeline (ASP) software and the commercial SOCET SET® software. After first describing the criteria for assessing stereo quality in detail, we qualitatively and quantitatively describe both the horizontal resolution and vertical precision of the DTMs. We find that the horizontal resolution of the SOCET SET® DTMs is typically 8–11× the root mean square (RMS) pixel scale of the images, whereas the resolution of the ASP DTMs is 9–13× the maximum pixel scale of the images. We calculate the RMS difference between the ASP and SOCET SET® DTMs as a proxy for the expected vertical precision (EP), which is a function of the matching accuracy and stereo geometry. We consistently find that the matching accuracy is ~0.5 pixels, which is larger than well-established “rules of thumb” that state that the matching accuracy is 0.2–0.3 pixels. The true EP is therefore ~1.7× larger than might otherwise be assumed. In most cases, DTM errors are approximately normally distributed, and errors that are several times the derived EP occur as expected. However, in two DTMs, larger errors (differences) occur and correlate with real topography. These differences primarily result from manual editing of the SOCET SET® DTMs. The product of the DTM error and the resolution is typically 4–8 pixel2 if calculated using the RMS image scale for SOCET SET® DTMs and the maximum images scale for the ASP DTMs, which is consistent with recent work using martian data sets and suggests that the relationship applies more broadly. We evaluate how ASP parameters affect DTM quality and find that using a smaller subpixel refinement kernel results in DTMs with smaller (better) resolution but, in some cases, larger gaps, which are sometimes reduced by increasing the size of the correlation kernel. We conclude that users of ASP should always systematically evaluate the choice of parameters for a given dataset.

Utilization of Airborne Topo-Bathymetric LiDAR Technology for Coastline Determination in Western Part of Java Island

Indonesia is the largest archipelagic country consisting of 17,504 islands which have 99,093 km of coastline. From the total, approximately only 10% had mapped. The coastline is essential for several applications such as topographic height reference, a reference in the delimitation of the marine management area, coastal boundaries, etc. Law number 4 of 2011 (UUIG), in article 13 paragraph 2 concerning Geospatial Information, mentioned three types of coastlines, namely: (a) the lowest astronomical tide, (b) the highest astronomical tide, and (c) the mean sea level. The existing method for determining the coastlines is observing a tide gauge over a long period at several places, then densify the point height by levelling method. This method is less effective due to time, cost, and amount of sample points. This paper presents our experience on coastlines determination by extracting it from a digital terrain model (DTM). The Airborne Topo-Bathymetric LiDAR technology is utilized to provide DTM that covers land and seabed. The points cloud, which is the output of this technology, was transformed to the geoid and corrected by tidal datum before those three types of coastlines were determined and delineated. The Western Part of Java Island is a study area. The project covers 1,000 km of coastline. The DTM quality was validated using several independent check-points along the coastline and hundreds of shorelines transect points at two locations. The result shows that vertical accuracy within the decimeter level.

ANALYSIS OF GEOMETRIC AND ORTHOGONAL CORRECTION ACCURACY FOR CAS-500 SATELLITE IMAGES

Abstract. This paper reports on geolocation accuracy of image products generated from Precision Image Processing (PIP) system developed for CAS-500 Satellite images. CAS-500, launched on 22 March, 2021, will be used mainly for land monitoring and 1:5000 scale mapping over the Korean Peninsula. For this purpose, ground control points (GCPs) and a Digital Terrain Model (DTM) have been collected over the Peninsula and integrated into the PIP for the generation of precision image product in an automated manner. The goal of this paper is to analyze the geolocation accuracy of image products generated from the PIP. Target geolocation accuracy of the PIP was set as 2 pixel RMSE using the internal GCP DB and DTM. Since CAS-500 images were not distributed yet, the analysis was performed using 13 KOMPSAT-3A satellite images, having similar specifications to CAS-500. The result showed that the accuracy of precise sensor models were about 1.797 pixels in South Korea and 1.907 pixels in North Korea. The accuracy of orthoimages were about 1.24 meters in South Korea and 1.59 meters in North Korea. Overall, the geolocation over North Korea was not as good as that over South Korea. It was judged that the quality of GCPs and DTM over North Korea affected the geolocation accuracy and, however, the accuracy gap was not too severe. The PIP system should produce image products within the targeted geolocation accuracy when CAS-500 delivers high resolution images over the Korean Peninsula.

Coastal Mapping Using DJI Phantom 4 RTK in Post-Processing Kinematic Mode

Topographic and geomorphological surveys of coastal areas usually require the aerial mapping of long and narrow sections of littoral. The georeferencing of photogrammetric models is generally based on the signalization and survey of Ground Control Points (GCPs), which are very time-consuming tasks. Direct georeferencing with high camera location accuracy due to on-board multi-frequency GNSS receivers can limit the need for GCPs. Recently, DJI has made available the Phantom 4 Real-Time Kinematic (RTK) (DJI-P4RTK), which combines the versatility and the ease of use of previous DJI Phantom models with the advantages of a multi-frequency on-board GNSS receiver. In this paper, we investigated the accuracy of both photogrammetric models and Digital Terrain Models (DTMs) generated in Agisoft Metashape from two different image datasets (nadiral and oblique) acquired by a DJI-P4RTK. Camera locations were computed with the Post-Processing Kinematic (PPK) of the Receiver Independent Exchange Format (RINEX) file recorded by the aircraft during flight missions. A Continuously Operating Reference Station (CORS) located at a 15 km distance from the site was used for this task. The results highlighted that the oblique dataset produced very similar results, with GCPs (3D RMSE = 0.025 m) and without (3D RMSE = 0.028 m), while the nadiral dataset was affected more by the position and number of the GCPs (3D RMSE from 0.034 to 0.075 m). The introduction of a few oblique images into the nadiral dataset without any GCP improved the vertical accuracy of the model (Up RMSE from 0.052 to 0.025 m) and can represent a solution to speed up the image acquisition of nadiral datasets for PPK with the DJI-P4RTK and no GCPs. Moreover, the results of this research are compared to those obtained in RTK mode for the same datasets. The novelty of this research is the combination of a multitude of aspects regarding the DJI Phantom 4 RTK aircraft and the subsequent data processing strategies for assessing the quality of photogrammetric models, DTMs, and cross-section profiles.

Airborne laser scanning for terrain modeling in the Amazon forest

ABSTRACT Very few studies have been devoted to understanding the digital terrain model (DTM) creation for Amazon forests. DTM has a special and important role when airborne laser scanning is used to estimate vegetation biomass. We examined the influence of pulse density, spatial resolution, filter algorithms, vegetation density and slope on the DTM quality. Three Amazonian forested areas were surveyed with airborne laser scanning, and each original point cloud was reduced targeting to 20, 15, 10, 8, 6, 4, 2, 1, 0.75, 0.5 and 0.25 pulses per square meter based on a random resampling process. The DTM from resampled clouds was compared with the reference DTM produced from the original LiDAR data by calculating the deviation pixel by pixel and summarizing it through the root mean square error (RMSE). The DTM from resampled clouds were also evaluated considering the level of agreement with the reference DTM. Our study showed a clear trade-off between the return density and the horizontal resolution. Higher forest canopy density demanded higher return density or lower DTM resolution.

IMPLEMENTING SIFT AND BI-TRIANGULAR PLANE TRANSFORMATION FOR INTEGRATING DIGITAL TERRAIN MODELS

Abstract. Since their inception in the middle of the twentieth century, Digital Terrain Models (DTMs) have played an important role in many fields and applications that are used by geospatial professionals, ranging from commercial companies to government agencies. Thus, both the scientific community and the industry have introduced many methods and technologies for DTM generation and data handling. These resulted in a high volume and variety of DTM databases, each having different coverage and data-characteristics, such as accuracy, resolution, level-of-detail – amongst others. These various factors can cause a dilemma for scientists, mappers, and engineers that now have to choose a DTM to work with, let alone if several of these representations exist for a specified area. Traditionally, researchers tackled this problem by using only one DTM (e.g., the most accurate or detailed one), and only rarely tried to implement data fusion approaches, combining several DTMs into one cohesive unit. Although to some extent this was successful in reducing errors and improving the overall integrated DTM accuracy, two prominent problems are still scarcely addressed. The first is that the horizontal datum distortions and discrepancies between the DTMs are mostly ignored, with only the height dimension taken into account, even though in most cases these are evident. The second is that most approaches operate on a global scale, and thus do not address the more localized variations and discrepancies that are presented in the different DTMs. Both problems affect the resulting integrated DTM quality, which retains these unresolved distortions and discrepancies, resulting in a representation that is to some extent inferior and ambiguous. In order to tackle this, we propose an image based fusion approach: using the SIFT algorithm for matching and registration of the different representations, alongside localized morphing. Implementing the proposed approach and algorithms on various DTMs, the results are promising, with the capacity correctly geospatially align the DTMs, thus reducing the mean height difference variance between the databases to close to zero, as well as reducing the standard deviation between them by more than 30 %.

Accuracy evaluation of digital terrain model based on different flying altitudes and conditional of terrain using UAV LiDAR technology

Unmanned Aerial Vehicle (UAV) with Light Detecting Radar (LiDAR) sensor can be used to obtained high ground resolution data and generate good quality of Digital Terrain Model (DTM) as much can decrease the cost of data acquisition and processing time. This study aims to evaluate the influences of flying altitude and terrain on DTM accuracies obtained with UAV-based LiDAR. In this study, point clouds from UAV AL3 S1000 and AL3 – 32 LiDAR were used for generating DTM on two different terrains (i.e. flat, slope and overall) with three different flying altitudes (i.e. 20m, 40m and 60m) and validate with ground control points by using 129 reference points which taken from ground survey technique (GPS, total station and optical levelling). The Root Mean Square Error (RMSE) of point clouds elevation obtained at different altitudes for the flat area are 0.015m, 0.027m and 0.105m at the altitudes of 20m, 40m and 60m, respectively. Meanwhile, RMSE values for slope area are 0.267m, 0.298m and 0.343m at the altitudes of 20m, 40m and 60m, respectively. Overall study area gives the RMSE values of 0.323m, 0.450m and 0.616m at 20m, 40m and 60m altitude, respectively. The result shows that the change of RMSE values influenced by the different of altitude and terrain, which provides accurate and faster results.

Assessing the potential for measuring Europa's tidal Love number h2 using radar sounder and topographic imager data

The tidal Love number h2 is a key geophysical measurement for the characterization of Europa's interior, especially of its outer ice shell if a subsurface ocean is present. We performed numerical simulations to assess the potential for estimating h2 using altimetric measurements with a combination of radar sounding and stereo imaging data. The measurement principle exploits both delay and Doppler information in the radar surface return in combination with topography from a digital terrain model (DTM). The resulting radar range measurements at cross-over locations can be used in combination with radio science Doppler data for an improved trajectory solution and for estimating the h2 Love number. Our simulation results suggest that the absolute accuracy of h2 from the joint analysis of REASON (Radar for Europa Assessment and Sounding: Ocean to Near-surface) surface return and EIS (Europa Imaging System) DTM data will be in the range of 0.04–0.17 assuming full radio link coverage. The error is controlled by the SNR budget and DTM quality, both dependent on the surface properties of Europa. We estimate that this would unambiguously confirm (or reject) the global ocean hypothesis and, in combination with a nominal radio-science based measurement of the tidal Love number k2, constrain the thickness of Europa's outer ice shell to up to ±15 km.

Structure-from-Motion Using Historical Aerial Images to Analyse Changes in Glacier Surface Elevation

The application of structure-from-motion (SfM) to generate digital terrain models (DTMs) derived from different image sources has strongly increased, the major reason for this being that processing is substantially easier with SfM than with conventional photogrammetry. To test the functionality in a demanding environment, we applied SfM and conventional photogrammetry to archival aerial images from Zmuttgletscher, a mountain glacier in Switzerland, for nine dates between 1946 and 2005 using the most popular software packages, and compared the results regarding bundle adjustment and final DTM quality. The results suggest that by using SfM it is possible to produce DTMs of similar quality as with conventional photogrammetry. Higher point cloud density and less noise allow a higher ground resolution of the final DTM, and the time effort from the user is 3–6 times smaller, while the controls of the commercial software packages Agisoft PhotoScan (Version 1.2; Agisoft, St. Petersburg, Russia) and Pix4Dmapper (Version 3.0; Pix4D, Lausanne, Switzerland) are limited in comparison to ERDAS photogrammetry. SfM performs less reliably when few images with little overlap are processed. Even though SfM facilitates the largely automated production of high quality DTMs, the user is not exempt from a thorough quality check, at best with reference data where available. The resulting DTM time series revealed an average change in surface elevation at the glacier tongue of −67.0 ± 5.3 m. The spatial pattern of changes over time reflects the influence of flow dynamics and the melt of clean ice and that under debris cover. With continued technological advances, we expect to see an increasing use of SfM in glaciology for a variety of purposes, also in processing archival aerial imagery.

Impact of Slope, Aspect, and Habitat-Type on LiDAR-Derived Digital Terrain Models in a Near Natural, Heterogeneous Temperate Forest

Developments in airborne LiDAR data acquisition have provided better horizontal and vertical ground information in the form of 3D point clouds. This has led to satisfactory results of LiDAR-derived digital terrain models (DTMs), also across complex ecosystems like natural forest stands. However, data and site-driven factors such as spatial resolution (point density), topography (slope and aspect), and variation in forest habitat types affect the DTM accuracy. In addition, processing steps like ground filtering and interpolation of ground points may also result in differences in DTM quality. Here, a comparative study was designed by extracting DTMs from two LiDAR data sources (high- and low-density point clouds) and three ground-filtering algorithms (adaptive TIN algorithm with and without the use of mirror points as well as an interpolation-based algorithm). The accuracy of the DTMs was assessed in association with terrain parameter and forest habitat types across heterogeneous forest sites of Bavarian Forest National Park in southeastern Germany. Qualitative analysis was carried out by taking 8300 independent sets of DGPS-recorded sample points. In addition to deriving root-mean-square error (RMSE) and bias, analysis of variance (ANOVA) type II was conducted in a factorial design to assess the influential factors on the observed DTM random error. Results revealed these errors in the DTMs with occasional over- and underestimations up to 1.98 m compared to reference elevation values. DTMs produced from high pulse density LiDAR data were more accurate than those extracted from low pulse density. Furthermore, topographic and forest habitat-type factors significantly contributed to the DTM accuracy. Slope increment showed a direct relationship with DTM error, with higher errors observed in south, southwest, and west aspects. Furthermore, stands dominated by deciduous trees were associated with higher DTM error than other forest habitat types. The applied adaptive TIN ground-filtering algorithms with mirror points and the interpolation-based algorithm both produced comparatively lower error rates, which are, therefore, suggested to reduce interpolation error in DTMs across rugged and heterogeneous forested terrains.

COMPARING UNIFORM AND RANDOM DATA REDUCTION METHODS FOR DTM ACCURACY

The digital cartographic representation of the elevation of the earth's surface created from discrete elevation points is defined as a digital terrain model (DTM). DTMs have been used in a wide range of applications, such as civil planning, flood control, transportation design, navigation, natural hazard risk assessment, hydraulic simulation, visibility analysis of the terrain, topographic change quantification, and forest characterization. Remote sensing, laser scanning, and radar interferometry become efficient sources for constructing high-accuracy DTMs by the developments in data processing technologies. The accuracy, the density, and the spatial distribution of elevation points, the terrain surface characteristics, and the interpolation methods have an influence on the accuracy of DTMs. In this study, uniform and random data reduction methods are compared for DTMs generated from airborne Light Detection and Ranging (LiDAR) data. The airborne LiDAR data set is reduced to subsets by using uniform and random methods, representing the 75%, 50%, and 25% of the original data set. Over the Mount St. Helens in southwest Washington State as the test area, DTM constructed from the original airborne LiDAR data set is compared with DTMs interpolated from reduced data sets by Kriging interpolation method. The results show that uniform data reduction method can be used to reduce the LiDAR datasets to 50% density level while still maintaining the quality of DTM.