Quality Of Digital Surface Models Research Articles

Novel UAV Flight Designs for Accuracy Optimization of Structure from Motion Data Products

Leveraging low-cost drone technology, specifically the DJI Mini 2, this study presents an innovative method for creating accurate, high-resolution digital surface models (DSMs) to enhance topographic mapping with off-the-shelf components. Our research, conducted near Jena, Germany, introduces two novel flight designs, the “spiral” and “loop” flight designs, devised to mitigate common challenges in structure from motion workflows, such as systematic doming and bowling effects. The analysis, based on height difference products with a lidar-based reference, and curvature estimates, revealed that “loop” and “spiral” flight patterns were successful in substantially reducing these systematic errors. It was observed that the novel flight designs resulted in DSMs with lower curvature values compared to the simple nadir or oblique flight patterns, indicating a significant reduction in distortions. The results imply that the adoption of novel flight designs can lead to substantial improvements in DSM quality, while facilitating shorter flight times and lower computational needs. This work underscores the potential of consumer-grade unoccupied aerial vehicle hardware for scientific applications, especially in remote sensing tasks.

Analysis of PlanetScope Dove Digital Surface Model Accuracy Using Geometrically Simulated Images

Many objectives in geoscience and engineering require Earth surface elevations at greater temporospatial resolution and coverage than are currently available. This may be achieved with stereo imagery from large constellations of “small sats”, such as PlanetScope Doves. Obtaining Digital Surface Models (DSMs) of sufficient quality from these images is challenging due to their lower resolution and weaker stereo geometry relative to stereo mode satellites such as WorldView. The quality can be improved by utilizing their much larger numbers of repeat images, but this requires effective stereopair selection. To determine the stereo geometries required for obtaining quality DSMs from PlanetScope Dove imagery, we apply a new methodology for generating simulated stereo images of varying geometries using adjusted orientation parameters obtained by a self-calibrating bundle adjustment and validated by comparing the resulting rigorous sensor and rational function models. The accuracies of simulated stereo and multi-pair DSMs are then assessed through comparison to a reference DSM, providing the relationship between specific imaging geometries and DSM quality. Our results provide a basis for automated stereo imagery selection to enable large-scale DSM production from PlanetScope Dove imagery. Our methodology can be applied to other sources of stereo imagery and designing future satellite missions. In the future, we will further develop multi-pair matching algorithms for generating DSMs with Dove Classic images to improve both accuracy and quality that are otherwise limited by the weak stereo geometry of single stereo pairs.

ENRICHMENT OF UAV PHOTOGRAMMETRIC POINT CLOUD TO ENHANCE DSM IN A DENSE URBAN REGION

Abstract. Unmanned Arial Vehicle (UAV) have become very cost effective and time efficient technology for surveying, mapping and various other geospatial applications. UAV serves as a platform but the main dependency also lies on which type of the sensor is integrated on it. Optical photogrammetric surveys are more often conducted for generalized purposes and for its advantages. UAV photogrammetry have become very useful tool in creation of 3D city model or Digital twin model. But creating a Digital Surface Model (DSM) through photogrammetry is not that efficient when it comes to very dense urban regions. In this research, the quality of DSM, Noise in the Photogrammetric point cloud are studied, then an experimental approach is tried to enhance the DSM than that of DSM obtained from photogrammetric processing software. From the results, it is observed that the quality of DSM is enhanced in narrow streets/roads, near trees, regions between trees and buildings, regions near building and road, etc. This approach can be utilized for low-cost UAV photogrammetry for accurate 3D modelling of the narrow streets or roads are of critical importance.

ASSESSMENT OF STEREO-EXTRACTED DSM FROM WORLDVIEW-3 OVER DIFFERENT LAND COVERS DEPENDING ON THE IMAGING GEOMETRY

Abstract. WorldView-3's 0.31m resolution in panchromatic mode, makes it one of the highest resolution commercial satellite in the world. This fact, together with its excellent stereo capabilities, make this satellite ideal for digital surface model (DSM) extraction working on very complex morphologies where a higher level of detail is required. In this communication we assess the quality (both completeness and vertical accuracy) of DSM extracted from WorldView-3 stereo pairs depending on the image geometry and sun position. Three different land covers (bare soil, urban areas and agricultural plastic greenhouses) have been tested in the Southeast of Spain (Almería). The well-known semiglobal matching (SGM) algorithm was used for all the extracted DSM. A clear relationship between DSM completeness and the WorldView-3 stereo pair imaging geometry measured as convergence angle was found. The completeness values decreased as convergence angles increased, especially in complex reliefs. In fact, convergence angles lower than 16 degrees is recommended when working on urban or greenhouse land covers. Moreover, sun light can cause glint effect in greenhouse areas. In this land cover, the attained results suggest to use stereo pairs taken when the sun presented a very low elevation. In Almería, the last happens in winter. The best results in all the tested land covers can be obtained by fusing DSM extracted from more than one stereo pair.

Radargrammetric DSM Generation by Semi-Global Matching and Evaluation of Penalty Functions

Radargrammetry is a useful approach to generate Digital Surface Models (DSMs) and an alternative to InSAR techniques that are subject to temporal or atmospheric decorrelation. Stereo image matching in radargrammetry refers to the process of determining homologous points in two images. The performance of image matching influences the final quality of DSM used for spatial-temporal analysis of landscapes and terrain. In SAR image matching, local matching methods are commonly used but usually produce sparse and inaccurate homologous points adding ambiguity to final products; global or semi-global matching methods are seldom applied even though more accurate and dense homologous points can be yielded. To fill this gap, we propose a hierarchical semi-global matching (SGM) pipeline to reconstruct DSMs in forested and mountainous regions using stereo TerraSAR-X images. In addition, three penalty functions were implemented in the pipeline and evaluated for effectiveness. To make accuracy and efficiency comparisons between our SGM dense matching method and the local matching method, the normalized cross-correlation (NCC) local matching method was also applied to generate DSMs using the same test data. The accuracy of radargrammetric DSMs was validated against an airborne photogrammetric reference DSM and compared with the accuracy of NASA’s 30 m SRTM DEM. The results show the SGM pipeline produces DSMs with height accuracy and computing efficiency that exceeds the SRTM DEM and NCC-derived DSMs. The penalty function adopting the Canny edge detector yields a higher vertical precision than the other two evaluated penalty functions. SGM is a powerful and efficient tool to produce high-quality DSMs using stereo Spaceborne SAR images.

Debris Flow and Rockslide Analysis with Advanced Photogrammetry Techniques Based on High-Resolution RPAS Data. Ponte Formazza Case Study (NW Alps)

The use of a Remotely Piloted Aircraft System (RPAS) for the characterization and monitoring of landslides has been widely improved in the last decade. In particular, the use of this system is particularly effective for the study of areas prone to geohazards. Zones affected by landslides, such as rock slides and debris flows, are often quite critical in terms of accessibility due to unstable blocs that can strongly limit the direct access to the studied area. In this paper, we present the case study of Ponte Formazza in NW Italian Alps. In June 2019, a massive and complex debris flow re-mobilized about 300,000 m3 of a rockslide deposit that occurred in 2009. In this particular environment, we tested traditional, direct and mixed photogrammetric approaches using various configurations of Ground Control Points (GCPs) of the photogrammetric block and by calculating the relative errors. The minimum configuration of GCPs was established to reduce in situ measurements without degrading the accuracy of the cartographic products. The images of three RPAS campaigns (2017, 2018 and 2019), processed with a Structure from Motion (SfM) technique, allowed us to obtain very high-resolution orthophoto and digital surface models (DSMs) before and after the 2019 event. A few GCPs, geolocated with a Global Navigation Satellite System (GNSS), improved the orthophoto and DSM quality (Root Mean Squared Error RMSE 5 cm) even in the areas far from the drone deployment. The availability of high-resolution models has been fundamental for the identification of the volume changes. Furthermore, the 3D view supported and completed the geomorphological mapping of affected areas, particularly in the areas where the field survey is dangerous. The use of ancillary meteorological data and Sentinel-2 satellite images allows for a better definition of the kinematics and the predisposal and triggering factors of the 2019 debris flow.

Detection of Standing Deadwood from Aerial Imagery Products: Two Methods for Addressing the Bare Ground Misclassification Issue

Deadwood mapping is of high relevance for studies on forest biodiversity, forest disturbance, and dynamics. As deadwood predominantly occurs in forests characterized by a high structural complexity and rugged terrain, the use of remote sensing offers numerous advantages over terrestrial inventory. However, deadwood misclassifications can occur in the presence of bare ground, displaying a similar spectral signature. In this study, we tested the potential to detect standing deadwood (h > 5 m) using orthophotos (0.5 m resolution) and digital surface models (DSM) (1 m resolution), both derived from stereo aerial image matching (0.2 m resolution and 60%/30% overlap (end/side lap)). Models were calibrated in a 600 ha mountain forest area that was rich in deadwood in various stages of decay. We employed random forest (RF) classification, followed by two approaches for addressing the deadwood-bare ground misclassification issue: (1) post-processing, with a mean neighborhood filter for “deadwood”-pixels and filtering out isolated pixels and (2) a “deadwood-uncertainty” filter, quantifying the probability of a “deadwood”-pixel to be correctly classified as a function of the environmental and spectral conditions in its neighborhood. RF model validation based on data partitioning delivered high user’s (UA) and producer’s (PA) accuracies (both > 0.9). Independent validation, however, revealed a high commission error for deadwood, mainly in areas with bare ground (UA = 0.60, PA = 0.87). Post-processing (1) and the application of the uncertainty filter (2) improved the distinction between deadwood and bare ground and led to a more balanced relation between UA and PA (UA of 0.69 and 0.74, PA of 0.79 and 0.80, under (1) and (2), respectively). Deadwood-pixels showed 90% location agreement with manually delineated reference to deadwood objects. With both alternative solutions, deadwood mapping achieved reliable results and the highest accuracies were obtained with deadwood-uncertainty filter. Since the information on surface heights was crucial for correct classification, enhancing DSM quality could substantially improve the results.

Quality assessment and validation of TerraSAR-X digital surface model using LiDAR for urban areas in Jakarta

Digital Surface Models (DSMs) are highly important product obtained from either conversional measurements or from remote sensing imagery. The estimation of height modelling of the earth’s surface is measured using interferometry synthetic aperture radar (InSAR). This radar technique uses phase information to provide the peak of the surface. The accuracy of the DSMs produced by InSAR depends on shadow mask of the area, layover, and the coherent difference between the images. This paper proposes a quality of DSMs derived from the InSAR method, which is from ascending paths using high resolution TerraSAR-X. In this research we generate DSMs in Urban area in Jakarta. Generating DSMs was done by the InSAR method which covers the same test area and came from one pair of ascending TerraSAR-X images. The quality level of elevation to be validated compared to validation datasets and application requirements. The comparison of the two DSMs from the ascending has been done by validating with LiDAR. The images pairs with 37 degrees incidence angle for ascending path. The results show error distribution within different terrain characteristics, which are presented using various ways including statistics, error maps and profiles. There is significant reduction in missing pixel counts due to layover, shadow and low coherences after co-registered. These include terrain characteristics, vegetation and land cover. For different slope we found accuracy to decrease with slope increase with an average standard deviation between a very low slope class and very steep slope class. The study area where we analyse is Jakarta for urban area.

AIRCRAFT BASED REAL TIME BUNDLE ADJUSTMENT AND DIGITAL SURFACE MODEL GENERATION

Abstract. This paper introduces a system for real-time generation of digital surface models (DSM) based on an optical multi-camera system flown on board of a manned airplane or helicopter. The system consists of high end consumer cameras, GNSS/IMU system, and on-board computers for real-time data processing. Usually, generation of digital surface models from aerial imagery is done in an off-line process, leading to delayed availability of height data. The proposed system processes data in real time on board of the aircraft and downlinks the generated DSM to a ground station. This paper evaluates the GNSS/IMU on-line solution quality and its impact on dense stereo matching. The proposed real time sliding window based bundle adjustment significantly improves image orientations and DSM quality, allowing generation of detailed digital surface models with a resolution of 2*GSD. Experiments using two flight patterns are conducted over the city of Landsberg and the resulting DSMs are evaluated against a LiDAR generated reference point cloud. The online bundle adjustment is shown to minimize the effect of systematic GNSS/IMU offsets while adding only a limited delay.

DSM Quality of Korean Satellite KOMPSAT-3 in Comparison to AW3D30 and Sentinel-1A in Respect of Airborne Laser Scanning

With significant technological improvements on earth observation instruments, three dimensional space-borne remote sensing data became indispensable for modelling large areas and continents. To acquire high resolution 3D earth data, actual optical and synthetic aperture radar (SAR) satellite missions are launched frequently. Korean Multi-Purpose Satellite 3 (KOMPSAT-3), which was launched in May, 2012 by Korea Aerospace Research Institute (KARI), is a high-resolution optical observation mission. The 0.7 m ground sampling distance (GSD) and stereo imaging capability of the satellite enables to derive qualified digital surface models (DSM). We generated a 5 m spacing KOMPSAT-3 DSM in Istanbul historic peninsula and estimated its quality by comprehensively analysing the absolute and relative accuracies and the morphological detail description capability. In the analysis, 1 m spacing airborne laser scanning (ALS) DSM was used as reference. Additionally, the ALOS (Advanced Land Observation Satellite) World 3D 30 m (AW3D30) and Sentinel-1A (S-1A) DSMs have been used in comparison with the KOMPSAT-3 DSM. As accuracy metrics, standard deviation (SZ) and normalized median absolute deviation (NMAD) of height differences between KOMPSAT-3, AW3D30, S-1A and ALS reference DSM were used. The results demonstrated that KOMPSAT-3 DEM quality is better than AW3D30 and S-1A both in accuracy and morphologic detail analysis.

Digital Surface Model Interpolation Based on 3D Mesh Models

A digital surface model (DSM) is an important geospatial infrastructure used in various fields. In this paper, we deal with how to improve the quality of DSMs generated from stereo image matching. During stereo image matching, there are outliers due to mismatches, and non-matching regions due to match failure. Such outliers and non-matching regions have to be corrected accurately and efficiently for high-quality DSM generation. This process has been performed by applying a local distribution model, such as inverse distance weight (IDW), or by forming a triangulated irregular network (TIN). However, if the area of non-matching regions is large, it is not trivial to interpolate elevation values using neighboring cells. In this study, we proposed a new DSM interpolation method using a 3D mesh model, which is more robust to outliers and large holes. We compared mesh-based DSM with IDW-based DSM and analyzed the characteristics of each. The accuracy of the mesh-based DSM was a 2.80 m root mean square error (RMSE), while that for the IDW-based DSM was 3.22 m. While the mesh-based DSM successfully removed empty grid cells and outliers, the IDW-based DSM had sharper object boundaries. Because of the nature of surface reconstruction, object boundaries appeared smoother on the mesh-based DSM. We further propose a method of integrating the two DSMs. The integrated DSM maintains the sharpness of object boundaries without significant accuracy degradation. The contribution of this paper is the use of 3D mesh models (which have mainly been used for 3D visualization) for efficient removal of outliers and non-matching regions without a priori knowledge of surface types.

Using Digital Surface Models from UAS Imagery of Fire Damaged Sphagnum Peatlands for Monitoring and Hydrological Restoration

The sub-alpine and alpine Sphagnum peatlands in Australia are geographically constrained to poorly drained areas c. 1000 m a.s.l. Sphagnum is an important contributor to the resilience of peatlands; however, it is also very sensitive to fire and often shows slow recovery after being damaged. Recovery is largely dependent on a sufficient water supply and impeded drainage. Monitoring the fragmented areas of Australia’s peatlands can be achieved by capturing ultra-high spatial resolution imagery from an unmanned aerial systems (UAS). High resolution digital surface models (DSMs) can be created from UAS imagery, from which hydrological models can be derived to monitor hydrological changes and assist with rehabilitation of damaged peatlands. One of the constraints of the use of UAS is the intensive fieldwork required. The need to distribute ground control points (GCPs) adds to fieldwork complexity. GCPs are often used for georeferencing of the UAS imagery, as well as for removal of artificial tilting and doming of the photogrammetric model created by camera distortions. In this study, Tasmania’s northern peatlands were mapped to test the viability of creating hydrological models. The case study was further used to test three different GCP scenarios to assess the effect on DSM quality. From the five scenarios, three required the use of all (16–20) GCPs to create accurate DSMs, whereas the two other sites provided accurate DSMs when only using four GCPs. Hydrological maps produced with the TauDEM tools software package showed high visual accuracy and a good potential for rehabilitation guidance, when using ground- controlled DSMs.

COMPARISON OF UAS-BASED PHOTOGRAMMETRY SOFTWARE FOR 3D POINT CLOUD GENERATION: A SURVEY OVER A HISTORICAL SITE

Abstract. Nowadays, Unmanned Aerial System (UAS)-based photogrammetry offers an affordable, fast and effective approach to real-time acquisition of high resolution geospatial information and automatic 3D modelling of objects for numerous applications such as topography mapping, 3D city modelling, orthophoto generation, and cultural heritages preservation. In this paper, the capability of four different state-of-the-art software packages as 3DSurvey, Agisoft Photoscan, Pix4Dmapper Pro and SURE is examined to generate high density point cloud as well as a Digital Surface Model (DSM) over a historical site. The main steps of this study are including: image acquisition, point cloud generation, and accuracy assessment. The overlapping images are first captured using a quadcopter and next are processed by different software to generate point clouds and DSMs. In order to evaluate the accuracy and quality of point clouds and DSMs, both visual and geometric assessments are carry out and the comparison results are reported.

GEOMETRIC ACCURACY ANALYSIS OF WORLDDEM IN RELATION TO AW3D30, SRTM AND ASTER GDEM2

Abstract. In a project area close to Istanbul the quality of WorldDEM, AW3D30, SRTM DSM and ASTER GDEM2 have been analyzed in relation to a reference aerial LiDAR DEM and to each other. The random and the systematic height errors have been separated. The absolute offset for all height models in X, Y and Z is within the expectation. The shifts have been respected in advance for a satisfying estimation of the random error component. All height models are influenced by some tilts, different in size. In addition systematic deformations can be seen not influencing the standard deviation too much. The delivery of WorldDEM includes information about the height error map which is based on the interferometric phase errors, and the number and location of coverage’s from different orbits. A dependency of the height accuracy from the height error map information and the number of coverage’s can be seen, but it is smaller as expected. WorldDEM is more accurate as the other investigated height models and with 10 m point spacing it includes more morphologic details, visible at contour lines. The morphologic details are close to the details based on the LiDAR digital surface model (DSM). As usual a dependency of the accuracy from the terrain slope can be seen. In forest areas the canopy definition of InSAR X- and C-band height models as well as for the height models based on optical satellite images is not the same as the height definition by LiDAR. In addition the interferometric phase uncertainty over forest areas is larger. Both effects lead to lower height accuracy in forest areas, also visible in the height error map.

Quality of Digital Elevation Models obtained from Unmanned Aerial Vehicles for Precision Viticulture

<p style="text-align: justify;"><strong>Aims:</strong> This work aims to study the quality of low cost Digital Surface Models (DSMs) obtained with Unmanned Aerial Vehicle (UAV) images and to test whether these DSMs meet common requirements of the wine industry.</p><p style="text-align: justify;"><strong>Methods and results: </strong>Experiments were carried out on a 4-ha vineyard located 10 km north of Beziers (France). The experimental site presents slope and aspect variations representative of mechanised commercial vineyards in Languedoc Roussillon. DSMs were provided by three UAV companies selected for the diversity of their solutions in terms of image capture altitude, type of UAV and image processing software. DSMs were obtained by photogrammetry and correspond to commercial products usually delivered by UAV companies. DSMs from UAV were compared to a reference Digital Elevation Model (DEM) acquired by a laser tachymeter. Four indicators were used to test the quality of DSMs: the mean error and its dispersion in the XY plane and in elevation Z. Results show a good georeferencing of the DSMs (MeanErrorXY<10 cm) and a similar quality in elevation (MeanErrorZ<10 cm) estimation. Results also show that the error in elevation is highly spatially structured. The spatial patterns observed did not depend on the elevation and could be related to algorithms used to compute the DSMs.</p><p style="text-align: justify;"><strong>Conclusion: </strong>Data acquisition and processing methods have an impact on the quality of the DSMs provided by the UAV companies. DSM qualities are good enough to meet commercial vineyard requirements. The tested DSMs fit the requirements to assess field characteristics (elevation, slope, aspects) which may be important for terroir characterisation purposes.</p><p style="text-align: justify;"><strong>Significance and impact of the study:</strong> This study proves that elevation data derived from UAV present an accuracy equivalent to the reference system used in this study. The rapidity, the low cost and the high spatial resolution of these data offer significant opportunities for the development of new services for the wine industry for field characterisation.</p>

Quality of Digital Elevation Models obtained from Unmanned Aerial Vehicles for Precision Viticulture

Aims: This work aims to study the quality of low cost Digital Surface Models (DSMs) obtained with Unmanned Aerial Vehicle (UAV) images and to test whether these DSMs meet common requirements of the wine industry.Methods and results: Experiments were carried out on a 4-ha vineyard located 10 km north of Beziers (France). The experimental site presents slope and aspect variations representative of mechanised commercial vineyards in Languedoc Roussillon. DSMs were provided by three UAV companies selected for the diversity of their solutions in terms of image capture altitude, type of UAV and image processing software. DSMs were obtained by photogrammetry and correspond to commercial products usually delivered by UAV companies. DSMs from UAV were compared to a reference Digital Elevation Model (DEM) acquired by a laser tachymeter. Four indicators were used to test the quality of DSMs: the mean error and its dispersion in the XY plane and in elevation Z. Results show a good georeferencing of the DSMs (MeanErrorXY<10 cm) and a similar quality in elevation (MeanErrorZ<10 cm) estimation. Results also show that the error in elevation is highly spatially structured. The spatial patterns observed did not depend on the elevation and could be related to algorithms used to compute the DSMs.Conclusion: Data acquisition and processing methods have an impact on the quality of the DSMs provided by the UAV companies. DSM qualities are good enough to meet commercial vineyard requirements. The tested DSMs fit the requirements to assess field characteristics (elevation, slope, aspects) which may be important for terroir characterisation purposes.Significance and impact of the study: This study proves that elevation data derived from UAV present an accuracy equivalent to the reference system used in this study. The rapidity, the low cost and the high spatial resolution of these data offer significant opportunities for the development of new services for the wine industry for field characterisation.

Ground-Control Networks for Image Based Surface Reconstruction: An Investigation of Optimum Survey Designs Using UAV Derived Imagery and Structure-from-Motion Photogrammetry

The use of small UAV (Unmanned Aerial Vehicle) and Structure-from-Motion (SfM) with Multi-View Stereopsis (MVS) for acquiring survey datasets is now commonplace, however, aspects of the SfM-MVS workflow require further validation. This work aims to provide guidance for scientists seeking to adopt this aerial survey method by investigating aerial survey data quality in relation to the application of ground control points (GCPs) at a site of undulating topography (Ennerdale, Lake District, UK). Sixteen digital surface models (DSMs) were produced from a UAV survey using a varying number of GCPs (3-101). These DSMs were compared to 530 dGPS spot heights to calculate vertical error. All DSMs produced reasonable surface reconstructions (vertical root-mean-square-error (RMSE) of <0.2 m), however, an improvement in DSM quality was found where four or more GCPs (up to 101 GCPs) were applied, with errors falling to within the suggested point quality range of the survey equipment used for GCP acquisition (e.g., vertical RMSE of <0.09 m). The influence of a poor GCP distribution was also investigated by producing a DSM using an evenly distributed network of GCPs, and comparing it to a DSM produced using a clustered network of GCPs. The results accord with existing findings, where vertical error was found to increase with distance from the GCP cluster. Specifically vertical error and distance to the nearest GCP followed a strong polynomial trend (R2 = 0.792). These findings contribute to our understanding of the sources of error when conducting a UAV-SfM survey and provide guidance on the collection of GCPs. Evidence-driven UAV-SfM survey designs are essential for practitioners seeking reproducible, high quality topographic datasets for detecting surface change.

Assessing the Accuracy of High Resolution Digital Surface Models Computed by PhotoScan® and MicMac® in Sub-Optimal Survey Conditions

For monitoring purposes and in the context of geomorphological research, Unmanned Aerial Vehicles (UAV) appear to be a promising solution to provide multi-temporal Digital Surface Models (DSMs) and orthophotographs. There are a variety of photogrammetric software tools available for UAV-based data. The objective of this study is to investigate the level of accuracy that can be achieved using two of these software tools: Agisoft PhotoScan® Pro and an open-source alternative, IGN© MicMac®, in sub-optimal survey conditions (rugged terrain, with a large variety of morphological features covering a range of roughness sizes, poor GPS reception). A set of UAV images has been taken by a hexacopter drone above the Rivière des Remparts, a river on Reunion Island. This site was chosen for its challenging survey conditions: the topography of the study area (i) involved constraints on the flight plan; (ii) implied errors on some GPS measurements; (iii) prevented an optimal distribution of the Ground Control Points (GCPs) and; (iv) was very complex to reconstruct. Several image processing tests are performed with different scenarios in order to analyze the sensitivity of each software package to different parameters (image quality, numbers of GCPs, etc.). When computing the horizontal and vertical errors within a control region on a set of ground reference targets, both methods provide rather similar results. A precision up to 3–4 cm is achievable with these software packages. The DSM quality is also assessed over the entire study area comparing PhotoScan DSM and MicMac DSM with a Terrestrial Laser Scanner (TLS) point cloud. PhotoScan and MicMac DSM are also compared at the scale of particular features. Both software packages provide satisfying results: PhotoScan is more straightforward to use but its source code is not open; MicMac is recommended for experimented users as it is more flexible.

Area-based quality control of airborne laser scanning 3D models for different land classes using terrestrial laser scanning: sample survey in Houston, USA

Airborne laser scanning (ALS) is a remote-sensing technique that provides scale-accurate 3D models consisting of dense point clouds with x, y planimetric coordinates and altitude z. Using ALS, very high-resolution (VHR) digital surface models (DSMs) have been widely used for commercial and scientific applications since the early 1990s. Although there is widespread usage, there has been little comprehensive investigation of quality control for ALS DSMs in the literature, as most studies have been limited to assessing point-based vertical accuracy. This article is dedicated to investigating the quality of ALS DSMs for different land classes using statistical and visual approaches based on absolute and relative vertical accuracy metrics. Rather than a limited number of ground control points (GCP), the model-to-model-based approach is applied and DSMs derived from terrestrial laser scanning (TLS) point clouds that have around 5 mm absolute and 3 mm relative geolocation accuracy were used as the reference data for comparison. The results demonstrate that in open, grass, and building land classes, the ALS DSMs reached both standard deviation (σ) and normalized median absolute deviation (NMAD) of 3–5 cm after the elimination of any systematic biases. This result sufficiently satisfies the vertical accuracy requirements for 1/1000-scale topographic maps determined by National Digital Elevation Program (NDEP) specifications. In tall vegetation, a higher number of discrepancies larger than 0.5 m exist, reversing the relation between σ and NMAD. These vegetation errors also do not appear to be normally distributed. As an additional investigation, the performance of ALS DEMs under dense high-vegetation areas was assessed. These under-canopy ALS DEMs, created using only classified ground returns, offer both σ and NMAD of 12–14 cm, a performance level that is difficult to achieve under-canopy using photogrammetric techniques.

Assessing the quality of DSM from ALOS optical and radar data for automatic drainage extraction

The hydrological network analysis was based for many years on topographic maps or on aerial photos. The evolution of GIS software and the existence of plenty of satellite sensors collecting data with high spatial resolution made possible the creation of quite accurate Digital Surface Models (DSM) and the automatic drainage extraction. In this study the suitability and the accuracy of drainage network derived from ALOS optical and radar data are validated with reference to the respective information from the topographic maps of 1/50.000. DSM from ALOS PALSAR and ALOS PRISM are created, evaluated for both vertical and horizontal accuracy and used for automatic drainage extraction. A fifth order basin of Alfios River in Western Peloponese, Greece was selected for the validation. Hydrological parameters such as the stream length, the drainage frequency and the drainage density were used for the evaluation of seven DSMs. It was proved that the DSMs of the ALOS optical data are more suitable for hydrological analysis and that the vertical high accuracy of the DSM doesn’t guarantee its suitability for automatic drainage extraction.