Digital Elevation Models (DEMs) contribute to geomorphological and hydrological applications. DEMs can be derived using different remote sensing-based datasets, such as Interferometric Synthetic ...Aperture Radar (InSAR) (e.g., Advanced Land Observing Satellite (ALOS) Phased Array type L-band SAR (PALSAR) and Shuttle Radar Topography Mission (SRTM) DEMs). In addition, there is also the Digital Surface Model (DSM) derived from optical tri-stereo ALOS Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) imagery. In this study, we evaluated satellite-based DEMs, SRTM (Global) GL1 DEM V003 28.5 m, ALOS DSM 28.5 m, and PALSAR DEMs 12.5 m and 28.5 m, and their derived channel networks/orders. We carried out these assessments using Light Detection and Ranging (LiDAR) Digital Surface Models (DSMs) and Digital Terrain Models (DTMs) and their derived channel networks and Strahler orders as reference datasets at comparable spatial resolutions. We introduced a pixel-based method for the quantitative horizontal evaluation of the channel networks and Strahler orders derived from global DEMs utilizing confusion matrices at different flow accumulation area thresholds (ATs) and pixel buffer tolerance values (PBTVs) in both ±X and ±Y directions. A new Python toolbox for ArcGIS was developed to automate the introduced method. A set of evaluation metrics—(i) producer accuracy (PA), (ii) user accuracy (UA), (iii) F-score (F), and (iv) Cohen’s kappa index (KI)—were computed to evaluate the accuracy of the horizontal matching between channel networks/orders extracted from global DEMs and those derived from LiDAR DTMs and DSMs. PALSAR DEM 12.5 m ranked first among the other global DEMs with the lowest root mean square error (RMSE) and mean difference (MD) values of 4.57 m and 0.78 m, respectively, when compared to the LiDAR DTM 12.5 m. The ALOS DSM 28.5 m had the highest vertical accuracy with the lowest recorded RMSE and MD values of 4.01 m and –0.29 m, respectively, when compared to the LiDAR DSM 28.5 m. PALSAR DEM 12.5 m and ALOS DSM 28.5 m-derived channel networks/orders yielded the highest horizontal accuracy when compared to those delineated from LiDAR DTM 12.5 m and LiDAR DSM 28.5 m, respectively. The number of unmatched channels decreased when the PBTV increased from 0 to 3 pixels using different ATs.
Understory topography serves as a crucial data source, playing an instrumental role in numerous forest ecosystem applications. However, the use of synthetic aperture radar interferometry and optical ...stereo for the acquisition of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), SRTM (Shuttle Radar Topography Mission), and GLO-30 (Copernicus Digital Elevation Model) DEM presents unique challenges, particularly in forested environments. These challenges are primarily due to limitations in penetration capability and the effects of foreshortening. ICESat-2/ATLAS, with its higher spatial sampling rate and strong penetrability, presents a new opportunity for estimating forest height parameters and understory terrain. We assessed the vertical accuracy of ASTER, SRTM, GLO-30, and ATLAS in the forest study areas of the United States compared to the reference dataset DTM provided by G-LiHT and we will further discuss the influence of different ground altitudes, forest types, slopes, and aspects on vertical accuracy. The study reveals that in a forested environment, ICESat-2 ATL03 exhibits the highest accuracy at the footprint scale, with a correlation coefficient (R2) close to 1 and Root Mean Square Error (RMSE) = 1.96 m. SRTM exhibits the highest accuracy at the regional scale, with an R2 close to 0.99, RMSE = 11.09 m. A significant decrease in accuracy was observed with increasing slope, especially for slopes above 15°. With a sudden increase in altitude, such as in mountainous situations, the accuracy of vertical estimation will significantly decrease. Aspect and forest cover indeed influence the accuracy of the four DEM products, but this influence lacks a clear pattern. Our results show that ICESat-2 and SRTM data might show sufficient and stable vertical accuracy in a forested environment.
Management and monitoring of vulnerable coastal marshes rely on accurate ground height estimates. However, marsh surface characteristics such as vegetation and water presence complicate aerial remote ...sensing of the ground. Towards developing an improved understanding and techniques for these remote sensing efforts, this study established relationships among data collection flight altitude, surface characteristics, and ground height estimate accuracy within Juncus roemerianus Scheele-dominated marshes. Uncrewed Aerial System (UAS) Light Detection and Ranging (LiDAR) sampling was conducted at five altitudes for five marsh sites and one local control site. Survey-grade topographic measurements and marsh surface characteristics were recorded at each site for comparison. Root Mean Square Error (RMSE) and linear mixed-effects modeling were used to quantify relationships among vertical error, altitude, and surface characteristics. For low (24–72 m) and high (96–120 m) altitudes Above Ground Level (AGL), the RMSE values were 49 cm and 17 cm, respectively. Despite this appreciable improvement in accuracy with increasing flight altitude, point density values of these datasets limit applications. Linear mixed-effects modeling further emphasized the complex relationships between sensor footprint size, surface characteristics, and ground height estimates. These findings have direct implications for elevation modeling and monitoring efforts of frequently inundated, coastal marshes.
Forest road maps are a fundamental source of information for the sustainable management, protection, and public utilization of forests. However, the precision of these maps is crucial to their use. ...In this context, we assessed and compared the elevation accuracy of terrain on three forest road surfaces (i.e., asphalt, concrete, and stone), which were derived based on data from three remote sensing technologies (i.e., aerial imaging, airborne laser scanning, and mobile laser scanning) using five geospatial techniques (i.e., inverse distance; natural neighbor; and conversion by average, maximal, and minimal elevation value). Specifically, the elevation accuracy was assessed based on 700 points at which elevation was measured in the field, and these elevations were extracted from fifteen derived forest road maps with a resolution of 0.5 m. The highest precision was found on asphalt roads derived from mobile laser scanning data (RMSE from ±0.01 m to ±0.04 m) and airborne laser scanning data (RMSE from ±0.03 m to ±0.04 m). On the other hand, the lowest precision was found on all roads derived from aerial imaging data (RMSE from ±0.11 m to ±0.23 m). Furthermore, we found significant differences in elevation between the measured and derived terrains. However, the differences in elevation between specific techniques, such as inverse distance, natural neighbor, and conversion by average, were mostly random. Moreover, we found that airborne and mobile laser scanning technologies provided terrain on concrete and stone roads with random elevation differences. In these cases, it is possible to replace a specific technique or technology with one that is similar without significantly decreasing the elevation accuracy (α = 0.05).
Purpose
Aircraft structures are mainly connected by riveting joints, whose quality and mechanical performance are directly determined by vertical accuracy of riveting holes. This paper proposed a ...combined vertical accuracy compensation method for drilling and riveting of aircraft panels with great variable curvatures.
Design/methodology/approach
The vertical accuracy compensation method combines online and offline compensation categories in a robot riveting and drilling system. The former category based on laser ranging is aimed to correct the vertical error between actual and theoretical riveting positions, and the latter based on model curvature is used to correct the vertical error caused by the approximate plane fitting in variable-curvature panels.
Findings
The vertical accuracy compensation method is applied in an automatic robot drilling and riveting system. The result reveals that the vertical accuracy error of drilling and riveting is within 0.4°, which meets the requirements of the vertical accuracy in aircraft assembly.
Originality/value
The proposed method is suitable for improving the vertical accuracy of drilling and riveting on panels or skins of aerospace products with great variable curvatures without introducing extra measuring sensors.
•SRTM DEM has vertically accuracy (±27.58m) less than specified standard (±16m).•Terrain analysis indicates that SRTM DEM and TOPO DEM are hydrological different.•SRTM DEM shows a significantly ...higher sediment yield with lower prediction accuracy.•SRTM and TOPO DEMs have moderate variation for predicted runoff values.•Sediment yield is more sensitive to choice of DEM in comparison to runoff estimation.
The Shuttle Radar Topography Mission (SRTM) data has emerged as a global elevation data in the past one decade because of its free availability, homogeneity and consistent accuracy compared to other global elevation dataset. The present study explores the consistency in hydrological behavior of the SRTM digital elevation model (DEM) with reference to easily available regional 20m contour interpolated DEM (TOPO DEM). Analysis ranging from simple vertical accuracy assessment to hydrological simulation of the studied Maithon catchment, using empirical USLE model and semidistributed, physical SWAT model, were carried out. Moreover, terrain analysis involving hydrological indices was performed for comparative assessment of the SRTM DEM with respect to TOPO DEM. Results reveal that the vertical accuracy of SRTM DEM (±27.58m) in the region is less than the specified standard (±16m). Statistical analysis of hydrological indices such as topographic wetness index (TWI), stream power index (SPI), slope length factor (SLF) and geometry number (GN) shows a significant differences in hydrological properties of the two studied DEMs. Estimation of soil erosion potentials of the catchment and conservation priorities of microwatersheds of the catchment using SRTM DEM and TOPO DEM produce considerably different results. Prediction of soil erosion potential using SRTM DEM is far higher than that obtained using TOPO DEM. Similarly, conservation priorities determined using the two DEMs are found to be agreed for only 34% of microwatersheds of the catchment. ArcSWAT simulation reveals that runoff predictions are less sensitive to selection of the two DEMs as compared to sediment yield prediction. The results obtained in the present study are vital to hydrological analysis as it helps understanding the hydrological behavior of the DEM without being influenced by the model structural as well as parameter uncertainty. It also reemphasized that SRTM DEM can be a valuable dataset for hydrological analysis provided any error/uncertainty therein is being properly evaluated and characterized.
This paper describes in detail the applicability of the developed ground-penetrating radar (GPR) model with a kinematic GPR and self-tracking (robotic) terrestrial positioning system (TPS) surveying ...setup (GPR-TPS model) for the acquisition, processing and visualisation of underground utility infrastructure (UUI) in a real urban environment. The integration of GPR with TPS can significantly improve the accuracy of UUI positioning in a real urban environment by means of efficient control of GPR trajectories. Two areas in the urban part of Celje in Slovenia were chosen. The accuracy of the kinematic GPR-TPS model was analysed by comparing the three-dimensional (3D) position of UUI given as reference values (true 3D position) from the officially consolidated cadastre of utility infrastructure in the Republic of Slovenia and those obtained by the GPR-TPS method. To determine the reference 3D position of the GPR antenna and UUI, the same positional and height geodetic network was used. Small unmanned aerial vehicles (UAV) were used for recording to provide a better spatial display of the results of UUI obtained with the GPR-TPS method. As demonstrated by the results, the kinematic GPR-TPS model for data acquisition can achieve an accuracy of fewer than 15 centimetres in a real urban environment.
Modelos Digitais de Superfícies (MDS) são importantes fontes de dados digitais representativos do relevo terrestre. Para identificar a acurácia vertical de um MDS, é necessário realizar a sua ...validação para a área de interesse. Uma possível fonte de dados com altimetria, disponível para todo o território brasileiro, é a plataforma online e gratuita do SIGEF (Sistema de Gestão Fundiária). Entretanto, a confiabilidade desses dados para o processo de validação de MDS ainda não foi verificada. Esse estudo avalia se o banco de dados do SIGEF pode ser utilizado como dados de referência na validação da acurácia vertical de MDS. Para isso, comparou-se os resultados das validações altimétricas do MDS SRTM 3, com 30 metros (1 arcseg) de resolução espacial, obtidas com os bancos de dados da Fundação ITESP e do SIGEF. As análises estatísticas e os processamentos dos dados foram realizados em softwares livres (PAST 3.25 e QGIS 2.18). O controle de qualidade do MDS SRTM 3 foi baseado no Padrão de Exatidão Cartográfica dos Produtos Cartográficos Digitais (PEC-PCD). Após realizar um processo de filtragem nos dados do SIGEF, obteve-se a classificação B, escala 1:50.000 (PEC menor do que 10,00 m e EP menor do que 6,66 m), para o MDS SRTM 3. Resultados similares foram obtidos com o banco de dados da Fundação ITESP. Sem considerar a filtragem nos dados do SIGEF, obteve-se Classe B, escala 1:100.000. Concluiu-se que os dados altimétricos do SIGEF podem ser utilizados em validações da acurácia vertical de MDS após filtragem e remoção de outliers
Procjenu visinske točnosti neophodno je obaviti kako bi se utvrdila kvaliteta DMT-a. Ta će kvaliteta utjecati na vrstu mjerila i korištenje DMT-a. U studiji se koriste podaci iz DMT-a ALOS PALSAR-2. ...Ova studija procjenjuje visinsku točnost DMT-a ALOS PALSAR-2 s različitim referentnim područjima visine u području Rote Dead Sea, Indonezija. Svaki DMT izrađen je uz pomoć EGM 1996, EGM 2008 i WGM 2012. Tri DMT-a, koja se temelje na referentnim područjima visine, imat će različite ortometrijske visine; zato je potrebna procjena visinske točnosti kako bi se odredila kvaliteta ta tri DMT-a. Oni se uspoređuju s terenskim mjerenjima dobivenima GNSS-niveliranjem. Ovo ispitivanje provodi se u nizinskim i brdskim područjima koristeći 10 testnih točaka. Za nizinsko područje, RMSE (z) u visini na DMT-u je 1,363 m za WGM 2012, 2,017 m za EGM 2008 i 1,934 m za EGM 1996. Za brdsko područje, RMSE (z) u visini na DMT-u je 1,185 m za WGM 2012, 1,201 m za EGM 2008 i 1,432 m za EGM 1996. DMT-WGM 2012 i DMT-EGM 1996 preporučuju se za korištenje u tom području jer imaju veću visinsku točnost. Ispitivanje visinske točnosti u nizinskom području otoka Rote odgovara klasi 2 i klasi 3 u mjerilu 1:10 000. Ispitivanje visinske točnosti u brdskom području otoka Rote odgovara klasi 1 i klasi 2 u mjerilu 1:10 000. Rezultati ispitivanja visinske točnosti DMT-a ALOS PALSAR-2 mogu se koristiti za mjerila kartiranja 1:10 000 – 1:25 000 na otoku Rote.
A digital terrain model (DTM) is a three-dimensional representation of the terrain relief created from discrete points related to each other through their elevations. New technologies such as ...satellite remote sensing, airborne laser scanning and radar interferometry are efficient methods for constructing high-quality DTMs in a cost-effective manner. The accuracy of a DTM is influenced by a number of factors, including the accuracy, density and spatial distribution of elevation points, the terrain surface characteristics, etc. In this paper, direct comparisons of absolute and relative vertical accuracies are made between data reduction algorithms for the generalisation of DTM extracted from airborne Light Detection and Ranging (LiDAR) data. The absolute vertical accuracies are presented in terms of the mean error (ME), the mean absolute error (MAE) and the root mean square error (RMSE) and the relative vertical accuracies are characterised as per cent slope over Mount St Helens in southwest Washington State. The results show that LiDAR datasets can be reduced to 50 per cent density level by a uniform data reduction algorithm using triangulation with a linear interpolation method for the generalisation of DTM while still maintaining the quality of the original data.
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