Towards a three-dimensional cost-effective registration of the archaeological heritage

In this study, we compared the accuracies of above-ground biomass (AGB) estimated by integrating ALOS (Advanced Land Observing Satellite) PALSAR (Phased-Array-Type L-Band Synthetic Aperture Radar) data and TanDEM-X-derived forest heights (TDX heights) at four scales from 1/4 to 25 ha in a hemi-boreal forest in Japan. The TDX heights developed in this study included nine canopy height models (CHMs) and three model-based forest heights (ModelHs); the nine CHMs were derived from the three digital surface models (DSMs) of (I) TDX 12 m DEM (digital elevation model) product, (II) TDX 90 m DEM product and (III) TDX 5 m DSM, which we developed from two TDX–TSX (TerraSAR-X) image pairs for reference, and the three digital terrain models (DTMs) of (i) an airborne Light Detection and Ranging (LiDAR)-based DTM (LiDAR DTM), (ii) a topography-based DTM and (iii) the Shuttle Radar Topography Mission (SRTM) DEM; the three ModelHs were developed from the two TDX-TSX image pairs used in (III) and the three DTMs (i to iii) with the Sinc inversion model. In total, 12 AGB estimation models were developed for comparison. In this study, we included the C-band SRTM DEM as one of the DTMs. According to Walker et al. (2007), the SRTM DEM serves as a DTM for most of the Earth’s surface, except for the areas with extensive tree and/or shrub coverage, e.g., the boreal and Amazon regions. As our test site is located in a hemi-boreal zone with medium forest cover, we tested the ability of the SRTM DEM to serve as a DTM in our test site. This study especially aimed to analyze the capability of the two TDX DEM products (I and II) to estimate AGB in practice in the hemi-boreal region, and to examine how the different forest height creation methods (the simple DSM and DTM subtraction for the nine CHMs and the Sinc inversion model-based approach for the three ModelHs) and the different spatial resolutions of the three DSMs and three DTMs affected the AGB estimation results. We also conducted the slope-class analysis to see how the varying slopes influenced the AGB estimation accuracies. The results show that the combined use of the PALSAR data and the CHM derived from (I) TDX 12 m DEM and (i) LiDAR DTM achieved the highest AGB estimation accuracies across the scales (R2 ranged from 0.82 to 0.97), but the CHMs derived from (I) TDX 12 m DEM and another two DTMs, (ii) and (iii), showed low R2 values at any scales. In contrast, the two CHMs derived from (II) TDX 90 m DEM and both (i) LiDAR DTM and (iii) SRTM DEM showed high R2 values > 0.87 and 0.78, respectively, at the scales > 9.0 ha, but they yielded much lower R2 values at smaller scales. The three ModelHs gave the lowest R2 values across the scales (R2 ranged from 0.39 to 0.60). Analyzed by slope class at the 1.0 ha scale, however, all the 12 AGB estimation models yielded high R2 values > 0.66 at the lowest slope class (0° to 9.9°), including the three ModelHs (R2 ranged between 0.68 to 0.69). The two CHMs derived from (II) TDX 90 m DEM and both (i) LiDAR DTM and (iii) SRTM DEM showed R2 values of 0.80 and 0.71, respectively, at the lowest slope class, while the CHM derived from (I) TDX 12 m DEM and (i) LiDAR DTM showed high R2 values across the slope classes (R2 > 0.82). The results show that (I) TDX 12 m DEM had a high capability to estimate AGB, with a high accuracy across the scales and the slope classes in the form of CHM, but the use of (i) LiDAR DTM was required. On the other hand, (II) TDX 90 m DEM was able to achieve high AGB estimation accuracies not only with (i) LiDAR DTM, but also with (iii) SRTM DEM in the form of CHM, but it was limited to large scales > 9.0 ha; however, all the models developed in this study have the possibility to achieve higher AGB estimation accuracies at the 1.0 ha scale in flat terrains with slope < 10°. The analysis showed the strengths and limitations of each model, and it also indicates that the data creation methods, the spatial resolutions of datasets and topographic features affects the effective spatial scales for AGB mapping, and the optimal combinations of these features should be chosen to obtain high AGB estimation accuracies.

Digital terrain models (DTMs) are digital elevation models (DEMs) that represent the bare ground surface. They are created by multiple sources, including satellite remote sensing, aerial photography, and ground-based surveys, and are often combined with other data sources to create highly detailed models. As the demand for accurate and detailed information about the Earth's surface continues to grow, DTMs have become an increasingly important tool for researchers in different fields. This study aims to create a DTM with a spatial resolution of 0.50 m for São Caetano do Sul, São Paulo, Brazil, integrated with a topobathymetric map of three water courses running along the borders of the study area. For the conventional DTM generation, a WV-2 stereo pair was used. A total of 55 ground control points (GCPs) were collected using the GNSS-RTK method, being 60% used for model building and 40% employed for validation. The topobathymetric survey was accomplished using a GNSS-RTK device placed along the analyzed open streams. For validation purposes, we used bias and MAE metrics. Overall, the methodology presented in this article provides a useful approach for generating high-resolution DTMs that can be used in a range of applications, especially in urban hydrodynamic studies.

Problem. Fast and high-quality development of project solutions for transport infrastructure objects and other linear artificial structures is based on the application of automated design systems. Modern automated design systems use digital 2D and 3D terrain models as input data. The development of digital terrain modeling is motivated by both the development of automated design systems and the development of specialized geodesic equipment. Functional capabilities of modern geodetic equipment in combination with systems for automated processing of geodetic measurement results make it possible to significantly reduce the time of measurement and processing of results and significantly improve the quality of the obtained results. Goal. The goal is to analyze the features of building a digital 3D model of the terrain of linear structures based on the results of measurements by a mobile laser scanner. Methodology. The technical parameters and functional capabilities of the Trimble MX2 mobile laser 3D scanner were analyzed. The Trimble MX2 mobile laser scanner is a high-speed and productive scanning system designed for installation in a vehicle. Results. The Trimble MX2 mobile laser 3D scanner allows you to perform laser scanning of the road surface and the surrounding area and create output data for building a digital terrain model. A digital terrain model using this technology can be created without stopping traffic flow. The Trimble MX2 mobile laser 3D scanner is mounted on the base of a passenger car and requires the involvement of one driver and one surveyor operator. The main elements of the system – an inertial sensor, GNSS receivers and scanning heads allow obtaining a cloud of points with high positioning accuracy. The system is managed through the operator's console in the car interior. With the help of systems for automated processing of measurement results, the cloud of points is transformed into a geospatial model of the area, which allows you to obtain a digital model of the area many times faster than using traditional measurement methods. Originality. Thanks to the available Trimble MX2 GNSS receivers in the scanning system and with the help of the Trident Imaging Hub software complex, the obtained measurement results are linked to the desired coordinate system and the scanning system route is visualized, which enables to link all the obtained results with absolutely clear positioning on the terrain. Practical value. With the use of the Trimble MX2 scanning system, road surveys of Ukraine are already being carried out, which allows to quickly and qualitatively develop capital repair and reconstruction projects and to determine the necessary measures for the proper operational maintenance of road sections.

3D-Building Height Extraction from Stereo IKONOS Data - Quantitative and Qualitative Validation of Digital Surface Models - Derivation of Building Height and Building Outlines

Whether planning urban development, conducting a hydrological construction in different terrain conditions, or analyzing terrain features for oil and gas exploration: accurate elevation information is vital. Digital Terrain Model Digital Terrain Model Digital Terrain Model(DTM) and Digital Surface Model (DSM) is the elevation model that provides elevation information of terrain and earth features (object), respectively. This study aims to assess the elevation accuracy of some of the most preferred Uncrewed Aerial Vehicle (UAV) data processing software from ESRI, Pix4DsoftwarePix4Dmapper, and Agisoft Photoscan. In this study, DJI Phantom 4 is used to collect 147 very high-resolution overlapped images in the selected study area (Department of Civil Engineering, IIT-Roorkee, India) at the defined height. Collected images are processed using all the selected platform elevation datasets, i.e. Digital Surface Model Digital Surface Model DSM(DSM) is generated. Vertical elevation error is estimated by elevation profile and statistical comparisons of UAV-derived elevation in the DSM datasets. This study helps to select the best UAV data processing software for the project that requires high elevation accuracy in topographical mapping or urban object utilization.

Many freely available global or quasi-global digital elevation model (DEM) datasets, including Advanced Land Observing Satellite (ALOS) World 3 Dimensions (3D) 30 m DEM (AW3D30 DEM), Advanced Spaceborne Thermal Emission and Reflection Radiometer DEM (ASTER DEM), Shuttle Radar Topography Mission DEM (SRTM DEM), Multiple-Error-Removed-Improved-Terrain DEM (MERIT DEM), and TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X) DEM (TanDEM-X DEM), are extremely useful products for many applications, so it is necessary to make a reasonable analysis of the quality of these DEMs. The quality of these DEMs is affected by both horizontal and vertical errors. However, most related researches have paid little attention to the effects of horizontal errors on the vertical accuracy of DEMs. Herein, after analysing the horizontal errors caused in the data acquisition process from optical stereo pairs and interferometry, experiments were proposed to assess the horizontal errors in DEMs. Then, we used the high accuracy digital surface model (DSM) of the Changsha area generated from the ZiYuan-3 triplet stereos to investigate the impact of horizontal errors on the accuracy of the five freely available DEMs. The subpixel level horizontal errors of the five DEMs were calculated, showing that the TanDEM-X DEM has systematic offsets and the other four DEMs have strip-like geometric errors. All the DEMs, except ASTER DEM, attained an accuracy increase of approximately 10% after the horizontal errors were removed. In mountainous areas, correcting the horizontal errors could eliminate the elevation errors caused by the imaging geometry of the optical camera and radar system. Generally, AW3D30 DEM has the best performance in terms of overall elevation accuracy and geometric accuracy after eliminating horizontal errors, and so it can have wide-ranging applications. These findings demonstrate the importance of removing horizontal errors to improve the elevation accuracy in practical applications using these global freely available DEMs.

With the development of specialized software applications it was possible to approach and resolve complex problems concerning automating and process optimization for which are being used field data. Computerized representation of the shape and dimensions of the Earth requires a detailed mathematical modeling, known as "digital terrain model". The paper aims to present the digital terrain model of Vulcan mining, Hunedoara County, Romania. Modeling consists of a set of mathematical equations that define in detail the surface of Earth and has an approximate surface rigorously and mathematical, that calculated the land area. Therefore, the digital terrain model means a digital representation of the earth's surface through a mathematical model that approximates the land surface modeling, which can be used in various civil and industrial applications in. To achieve the digital terrain model of data recorded using linear and nonlinear interpolation method based on point survey which highlights the natural surface studied. Given the complexity of this work it is absolutely necessary to know in detail of all topographic elements of work area, without the actions to be undertaken to project and manipulate would not be possible. To achieve digital terrain model, within a specialized software were set appropriate parameters required to achieve this case study. After performing all steps we obtained digital terrain model of Vulcan Mine. Digital terrain model is the complex product, which has characteristics that are equivalent to the specialists that use satellite images and information stored in a digital model, this is easier to use.

The scope of this paper is to summarize previous research pertaining to the use of digital elevation models (DEMs) and digital terrain models (DTMs) in the study of rockfalls and landslides. Research from 1983 to 2020 was surveyed in order to understand how the spatial resolution of DEMs and DTMs affects landslide detection, validation, and mapping. Another major question examined was the relationship between the DEM resolution and the extent of the rockfall or landslide event. It emerged from the study that, for landslides, the majority of researchers used DEMs with a spatial resolution of between 10 m and 30 m, while for rockfalls, they used DEMs with a spatial resolution of between 5 m and 20 m. We concluded that DEMs with a very high resolution (less than 5 m) are suitable for local-scale occurrences, while medium-resolution (from 20 m to 30 m) DEMs are suitable for regional-scale events. High resolution is associated with high accuracy and detailed structural characteristics, while medium accuracy better illustrates the topographic features. A low pixel size (more than 90 m) is not recommended for this type of research. Susceptibility maps, inventory maps, hazard risk zones, and vulnerability assessments are some of the main tools used in landslide/rockfall investigations, and topographic indexes, methods, models, and software optimize the reliability of the results. All of these parameters are closely related to DEMs and DTMs as the cell size affects the credibility of the final outcome.

The availability of high accuracy GCPs (ground control points) and DEMs (digital elevation models) becomes the key issue for successful implementation of an image orthorectification project. It is a very difficult task for collecting a large number of high quality GCPs by using traditional methods to meet all the requirements for digital photogrammetric and orthorectification process. Airborne light detection and ranging (LiDAR) - also referred to as airborne laser scanning (ALS), provides an alternative for high-density and high-accuracy three-dimensional terrain point data acquisition. One of the appealing features in the LiDAR output is the direct availability of three dimensional coordinates of points and intensity data in object space. With LiDAR data, high- accuracy and high-resolution intensity image, hillshade DSM (digital surface model) image, and DEM can be generated. Due to high planimetric accuracy characteristics of LiDAR data, ground truth can be extracted from these LiDAR-derived products (e.g., hillshade image and intensity image). This study investigated the feasibility of using LiDAR-derived hillshade DSM image and intensity image to extract ground truth for aerial image orthorectification. Two sets of GCPs were extracted from hillshade image and intensity image separately, and then were used as the inputs for aerial triangulation processing. LiDAR- derived DEM was then employed for differential rectification to produce the final orthoimage. The assessment of the planimetric accuracy of orthorectified images by using different set of GCPs was conducted by comparing the coordinates of some checking points from orthoimages and correspondent GPS surveyed coordinates.

Pleiades satellite imagery is very high resolution. with 0.5 m spatial resolution in the panchromatic band and 2.5 m in the multispectral band. Digital elevation models (DEM) are digital models that represent the shape of the Earth's surface in three-dimensional (3D) form. The purpose of this study was to assess DEM accuracy from panchromatic Pleaides imagery. The process conducted was orthorectification using ground control points (GCPs) and the rational function model with rational polynomial coefficient (RFC) parameters. The DEM extraction process employed photogrammetric methods with different parallax concepts. Accuracy assessment was made using 35 independent check points (ICPs) with an RMSE accuracy of ± 0.802 m. The results of the Pleaides DEM image extraction were more accurate than the National DEM (DEMNAS) and SRTM DEM. Accuracy testing of DEMNAS results showed an RMSE of ± 0.955 m. while SRTM DEM accuracy was ± 17.740 m. Such DEM extraction from stereo Pleiades panchromatic images can be used as an element on base maps with a scale of 1: 5.000.

The paper discusses a method for obtaining a digital terrain model when designing the routes of a linear object (oil pipeline) using a specific example. The relevance of the topic and the current state of the issue being studied are indicated. The sequence of work is described and the necessary equipment is provided. The purpose of the research is to study the means and techniques for creating a digital terrain model (DTM).
 Creating digital terrain models involves converting cartographic information from analogue to digital form. The digital form of storage on electronic media is currently more progressive. It allows you to quickly record and enter into a digital model changes that have occurred on the ground, as well as automate many processes of topographic and geodetic production. Due to the availability of fast computer processing of huge amounts of data, the task of creating a digital model as close to reality as possible becomes feasible. A digital terrain model (DTM) consists of a digital terrain model (DEM) and a digital situation model (DSM).
 The studies have developed a sequence for compiling a digital terrain model using a specific example, which will reduce the cost and time for work, increase the information content of the materials.

Digital Surface Models (DSMs) are commonly built using data collected via remote sensing techniques such as aerial photogrammetry, LiDAR, and InSAR. DSM accuracy mainly depends upon the type of data used beside the methodology followed. The highest accuracy can be achieved when using a land surveying data which takes more time and costs a lot. The objective of this study is to present a quick approach for constructing high resolution DSM for road elements based on land surveying data. This approach is called Field-To-Finish (FTF), it is a process of converting surveying data into final graphical files based on the characteristics of the points and the accompanying code. To illustrate the proposed approach and assess the accuracy comparing with the traditional method, a case study was presented. We found that the FTF is superior to the traditional method on more than one level. The number of observed points, the time for surveying field work and for drafting were reduced. The methodology adopted in this study for obtaining DSM has proven to produce a digital model which is suitable for production engineering charts of scale 1: 100 that can be used in many scientific and practical applications related to civil infrastructure.

The Geoscience Laser Altimeter System (GLAS) instrument onboard the Ice, Cloud and land Elevation Satellite (ICESat) provides elevation data with very high accuracy which can be used as ground data to evaluate the vertical accuracy of an existing Digital Elevation Model (DEM). In this article, we examine the differences between ICESat elevation data (from the 1064 nm channel) and Shuttle Radar Topography Mission (SRTM) DEM of 3 arcsec resolution (90 m) and map-based DEMs in the Qinghai-Tibet (or Tibetan) Plateau, China. Both DEMs are linearly correlated with ICESat elevation for different land covers and the SRTM DEM shows a stronger correlation with ICESat elevations than the map-based DEM on all land-cover types. The statistics indicate that land cover, surface slope and roughness influence the vertical accuracy of the two DEMs. The standard deviation of the elevation differences between the two DEMs and the ICESat elevation gradually increases as the vegetation stands, terrain slope or surface roughness increase. The SRTM DEM consistently shows a smaller vertical error than the map-based DEM. The overall means and standard deviations of the elevation differences between ICESat and SRTM DEM and between ICESat and the map-based DEM over the study area are 1.03 ± 15.20 and 4.58 ± 26.01 m, respectively. Our results suggest that the SRTM DEM has a higher accuracy than the map-based DEM of the region. It is found that ICESat elevation increases when snow is falling and decreases during snow or glacier melting, while the SRTM DEM gives a relative stable elevation of the snow/land interface or a glacier elevation where the C-band can penetrate through or reach it. Therefore, this makes the SRTM DEM a promising dataset (baseline) for monitoring glacier volume change since 2000.

Urban waterlogging is a natural disaster that occurs in developed cities globally and has inevitably become severe due to urbanization, densification, and climate change. The digital elevation model (DEM) is an important component of urban waterlogging risk prediction. However, previous studies generally focused on optimizing hydrological models, and there is a potential improvement in DEM by fusing remote sensing data and hydrological data. To improve the DEM accuracy of urban roads and densely built-up areas, a multisource data fusion approach (MDF-UNet) was proposed. Firstly, Fuzhou city was taken as an example, and the satellite remote sensing images, drainage network, land use, and DEM data of the study area were collected. Secondly, the U-Net model was used to identify buildings using remote sensing images. Subsequently, a multisource data fusion (MDF) method was adopted to reconstruct DEM by fusing the buildings identification results, land use, and drainage network data. Then, a coupled one-dimensional (1D) conduit drainage and two-dimensional (2D) hydrodynamic model was constructed and validated. Finally, the simulation results of the MDF-UNet approach were compared with the raw DEM data, inverse distance weighting (IDW), and MDF. The results indicated that the proposed approach greatly improved the simulation accuracy of waterlogging points by 29%, 53%, and 12% compared with the raw DEM, IDW, and MDF. Moreover, the MDF-UNet method had the smallest median value error of 0.08 m in the inundation depth simulation. The proposed method demonstrates that the credibility of the waterlogging model and simulation accuracy in roads and densely built-up areas is significantly improved, providing a reliable basis for urban waterlogging prevention and management.

In this study, some of the widely used data for elevation models were compared based on hydrological parameters such as slope, aspect, flow direction, and slope length and steepness factor (LS factor). The study considers the comparison among ASTER GDEM, SRTM DEM, topographic maps, and aerial photography at 430239 predetermined tests points. Bilinear interpolation technique was used to interpolate the data at these testing points. The result shows the digital elevation model (DEM) from topographic maps has relatively higher vertical accuracy (RMSE = 5.40 m), compared to ASTER GDEM (7.10 m) and SRTM DEM (15.07 m), while comparing with digital surface model (DSM) from stereo pairs. For validation, we used 47 ground control points (GCPs) using GPS. The results show the vertical accuracy are relatively higher for DSM (RMSE = 1.11 m), followed by DEMs from topographic maps (4.10 m), ASTER GDEM (7.36 m), and SRTM DEM (12.22 m). The DSM matches closely with the result of topographic DEM in case of slope, LS factor curves, aspect, and flow direction. The result with ASTER DEM matches better than results with SRTM data in all the parameters but both of them show poor match with the results from DSM data.