Оценка цифровых моделей рельефа для картографического обеспечения адаптивно-ландшафтного земледелия на микрозональном уровне с использованием ГИС-технологий

Surface modeling constitutes is a crucial aspect in numerous engineering inquiries and earth observation endeavors. In contemporary times, the acquisition of geospatial data essential for the digital representation of local regions is increasingly facilitated through drone-based methodologies, supplanting conventional terrestrial data gathering techniques. The market presently hosts a plethora of cost-effective, "ready-to-fly" unmanned aerial vehicles (UAVs), offering users the capability to generate photogrammetric outputs, including high geometric precision Digital Elevation Models (DEMs). Moreover, modularly structured drone development kits, designed for multifarious applications, are readily accessible for purchase. These drone kits offer an economically advantageous platform that users can customize to suit their specific needs. Nevertheless, the geometric precision of DEMs created using these kits hinges upon the capabilities of the imaging and navigation systems, in addition to the stabilization of the platform during autonomous flight. In this study, using a drone development kit and a commercial drone, simultaneous image acquisition was performed for the same study area and two different DEMs were produced. The efficacy of the DEM generated using the drone development kit was assessed through a comparative analysis with the DEM obtained from a commercial drone. In addition, geometric accuracy assessment was conducted for both DEMs using ground control points. The findings reveal the usability of drone development kits in precision DEM production, as well as their limitations.

Digital elevation models (DEMs) are essential to provide continuous terrain elevation for water surface elevation (WSE) with a variety of horizontal and vertical accuracies in flood inundation modelling. The WSE forecasting depends on the appropriateness of the DEM data used. The comparative methodology is applied to various DEM sources: LiDAR and IFSAR DEM based on different types of land use at each of the cross-sectional lines. The accuracy of the IFSAR DEMs was assessed with LiDAR data, which is a high-precision DEM and was applied in hydraulic modelling to simulate the WSE in Padang Terap, Kedah, Malaysia. Furthermore, Bjerklie’s model is used as predicted discharge to support the analysis. The relationship of the DEMs is established by natural logarithm (ln). Then, the equation is interpolated on the original and resampled IFSAR DEMs to improve the medium-resolution data for WSE delineation. Next, the WSE was validated with observed WSE obtained along the upstream (Kuala Nerang) to the downstream parts (Kampung Kubu) Kedah using R2, mean absolute error (MAE), and root-mean-square error (RMSE). By applying this method, the WSE can be improved by considering uncertainties and lead to produce a better flood hazard map using medium-high-resolution images.

Potential geohazards triggered by the rock mass deterioration (RMD) of the hydro-fluctuation belt (HFB) in the Three Gorges Reservoir area (TGRA) severely threaten the lives and property of people, it is necessary and urgent to timely identify this kind of potential geohazard. Aiming at this issue, several typical evolution modes of potential RMD-induced geohazards were generalized, and an unmanned aerial vehicle (UAV) photographic method integrating the orthophotography, three-dimensional multi-angle oblique photography and high-precision digital elevation model (DEM) was proposed to early recognize the newly formed potential RMD-induced geohazards. By resolving the problem of poor precision in the orthophotographic images of high steep bank slopes, the proposed method improved the recognition reliability of potential reservoir geohazards in the HFBs. Taking the bank slopes from Zigui County to Badong County as the study area, 116 new potential RMD-induced geohazard sites were identified by the presented approach, including 64 and 52 sites on the left and right bank, respectively. Through field verifications, 17 and 19 sites on the left and right bank were found to be consistent with existing hazards, indicating the effectiveness of the proposed approach in avoiding the false and missing recognitions of potential RMD-induced reservoir geohazards at current levels of knowledge and technology. The study can provide a valuable reference for the early identification of RMD-induced geohazards in reservoir areas.

Characterization and quantification of active faulting in the Roer valley rift system based on high precision digital elevation models

The Digital Elevation Model (DEM) contains elevation and slope information, making interpretation easierso that it is a fundamental element of geospatial data and can be used as a mapping source. The use oftechnology in the field of photogrammetric mapping is demonstrated by the use of Unmanned Aerial Vehicle(UAV) or drones in mapping and Geodetic GPS tied to benchmarks to obtain Ground Control Point (GCP)coordinates as ground control points. This research aims to make the Palangka Raya University DEM usingUAV and Geodetic GPS. In processing aerial photo data, the photogrammetric method is used. The time fortaking aerial photo data begins on 14-21 October 2022 which is divided into 10 flying missions with a flightaltitude of 100 m, overlap and sidelap of 75%, and camera angle of 90 with a total of 7,935 photos. GCP dataretrieval using the Real Time Kinematic (RTK) method with Geodetic GPS was carried out on October 14,2022 with a total of 33 coordinate points. The DEM that has been formed can be seen that mapping usingUAVs/drones and Geodetic GPS produces high-resolution photo data that can be used for making DigitalElevation Models (DEMs) with the highest altitude at Palangka Raya University, namely 90 meters and thelowest altitude at 50 meters. The DEM resolution obtained is 18.1 cm/pixel and the interpolation point densityis 30.7 points/m2.

This study aims to assess the accuracy of digital elevation model (DEM) created with utilization of handheld Global Positioning System (GPS) and comparing with Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM), version 2. It is known that the quality of the DEM is affected by both of accuracy of elevation at each pixel (absolute accuracy) and accuracy of presented morphology (relative accuracy). The University of Baghdad, Al Jadriya campus was selected as a study area to create and analysis the resulting DEM. Additionally, Geographic Information System (GIS) was used to visualize, analyses and interpolate GPS track points (elevation data) of the study area. In this research, three additional DEMs were created using 60%, 30% and 15% of the all GPS track points to deduce the effect of the number of the included points on the accuracy of the resulting DEM. The study findings show a high resolution for the resulting DEM less than 5m when taking into consideration all GPS tracking points that observed in this research. Moreover, the resulting DEM has relative accuracy better than absolute accuracy and reaches to around 2m. By comparing with ground control points (reference points), the quality of handheld GPS DEM shows considerable improvement better than ASTER GDEM. Thus, this study indicates to improve the accuracy level of handheld GPS DEM by about 40% with increasing the observed number of GPS track points to twice.
 

High-precision digital elevation models (DEMs) are the basic data for constructing digital cities. With the acceleration of urbanization, the topography of urban plots is constantly transformed by human activities, so that surface morphology shows the characteristics of diversification and discontinuity. Existing modelling methods focus on the expression of continuous terrain. Constructing high-precision DEM in urban plots is still challenging. A block-based modelling method that considers the morphological characteristics of urban plot elements was proposed. The Jinzhai County urban area was selected as the research area. The elements of urban plots were classified into six types, in which the boundaries and elevation information were extracted with real sense 3D models, Digital Orthophoto Maps (DOMs) and dense matching point cloud data. The DEMs of the 6 types of elements were generated separately with different methods, that are fused to complete the DEM of urban plots. The DEM obtained using the method in this manuscript was consistent with the reality in terms of topographic relief within each element and clarified the boundary of each element. The accuracy assessment showed that the RMSE results of roads, slopes, other terrains and natural terrains are approximately 0.05 m, which meets the elevation accuracy requirements of the 1:1000 large-scale mapping.

In this study, we generated Digital Elevation Model (DEM) from Unmanned Aerial Vehicle (UAV) to confirm the suitability of UAV to the tidal flat study. The DEMs were generated from aerial triangulation method using rotary-wing UAV. For the accurate generation of mosaic images and DEM, the distorted images occurred by interior and exterior orientation were corrected using camera calibration. In addition, we set up a Ground Control Points (GCPs) in order to correct of the UAV position error. Therefore, the DEM was obtained with geometric error less than 30 cm. The height of generated DEM by UAV was compared with the levelled elevation by RTK-GPS and TanDEM-X radar satellite DEM. From this study, we could confirm that accurate DEM of the tidal flat can be generated using UAV and these detailed spatial information about tidal flat will be widely used for tidal flat management.

Sand dune movements represent a critical global environment challenge. While previous studies have mainly focused on horizontal deformation, this study applies the bistatic InSAR technique to reconstruct high-precision digital elevation models (DEMs) of the desert terrain, enabling quantitative assessment of the height change in sand dunes by the DEM differential method. Although InSAR has been widely applied to monitor the surface deformation over the urban, mining, and landslide areas, its application in the desert area is still rare. In this study, the northwestern Kubuqi desert, where sand dunes are clearly distributed, was selected as the study area. Using the TanDEM-X bistatic InSAR data acquired on 26 December 2012 and 25 January 2018, we generated high-resolution DEMs with an estimated accuracy of RMSE ≈ 0.9 m in non-dune areas, as validated against ICESat-2 reference data. The high-precision DEM is attributed to the application of a parameterized modeling method, which also facilitates the effective implementation of the DEM differential method. Then, the t-test (i.e., a statistical hypothesis method) was used to estimate a minimum detectable height change (i.e., LoD) of approximately ±0.50 m and confirm the significance of observed elevation changes. Based on this, this reveals a net mean dune height decrease of 1.04 m during the study period. In addition, quantitative investigations on the vegetation coverage and the wind conditions provided further evidence supporting the observed reduction in dune height, suggesting that vegetation stabilization has likely inhibited sediment transport. This study demonstrates the potential of bistatic InSAR for monitoring desert geomorphological processes and provides scientific support for designing effective desertification control strategies.

To accurately assess landslide susceptibility and model debris flow paths, acquisition of high-resolution elevation data is essential. These data enable precise topographical analysis, considering factors like slope and curvature. But most of the time such high-resolution data will have inaccuracies due to vegetation, especially in tropical region. This study proposes a comprehensive approach that integrates field data and Structure from Motion (SfM) technology to rectify such DEM inaccuracies caused by dense vegetation. The goal is to enhance the accuracy of landslide simulations and volumetric analysis for effective post-disaster management. The Western Ghats, running parallel to India's western coast, has experienced a surge in rainfall-induced landslides, resulting in significant casualties in recent years. Notably, the Pettimudi village landslide in 2020 caused 70 deaths. The unique geomorphological features of the Western Ghats, such as concave curvature, colluvium deposits, and evidence of paleo landslides, contribute to the area's susceptibility. The study emphasizes the need for detailed assessment and mitigation strategies. The proposed method aims to improve the post-event high-resolution DEM accuracy by integrating field-collected elevation values and utilizing Agisoft Metashape software with the SfM algorithm. The rectification process involves combining elevation differences measured during a field study with photogrammetric elevation data. The field-collected elevation differences are crucial for rectifying these points, and enhancing the Digital Elevation Model (DEM) accuracy. The inaccessible source region is improved using a SfM-created DEM from drone footage, resulting in a more accurate post-event DEM. Correcting the 1 m DEM using an SfM-generated DEM proves challenging but significantly improves detail and accuracy, especially over the landslide source area. The impact of the rectification on accuracy is assessed by comparing volumes calculated from the initial DEM and the newly corrected DEM. The difference in volumes of debris depletion and accumulation, computed using initial and corrected DEMs, highlights variations, with depleted volumes being significantly larger due to the extensive depth increase over the landslide source region. These volumes are then utilized in Rapid Mass Movement Simulation (RAMMS) to validate the rectification process and enhance landslide impact predictions. Debris flow simulations in RAMMS, utilizing the rectified 1 m DEM, show specific outcomes at the landslide source region and toe of the landslide. The study emphasizes the importance of integrating SfM technology with field data to improve DEM accuracy, acknowledging the significance of additional field data for further refinement. The potential adoption of highly precise aerial imagery from Unmanned Aerial Vehicle (UAV) surveys is suggested to further enhance the SfM DEM. Debris flow modeling with RAMMS serves as a vital step in validating the accuracy and reliability of the rectified elevation model. Keywords: Landslides, Western Ghats, Pettimudi, Digital elevation model (DEM), Structure-from-Motion (SfM) technology, Rapid Mass Movement Simulation (RAMMS)

Accurate measurements of glacier surface topography and their changes play an essential role in various glaciological studies related to glacier dynamics and mass balance. The focus of this study is on mapping glacier digital elevation model (DEM) and elevation changes in the western Qilian Mountains, northern Tibetan Plateau, by synergistically using the TanDEM-X (TDX) bistatic Interferometric Synthetic Aperture Radar (InSAR) data in 2013 and Shuttle Radar Topography Mission (SRTM) DEM in 2000. The first high-resolution and high-precision glacier DEM is derived in this region by a TDX InSAR procedure with a nonlocal (NL) filter. Validated against the Ice, Cloud, and land Elevation Satellite (ICESat) height references, the absolute height error of the TanDEM-X DEM derived with the NL filter and the Goldstein filter with the parameters investigated is, respectively, 1.493 ± 0.747 and 1.857 ± 1.709 m. Further, four combinations of differential phase method (DiffPha) and DEM differencing method (DiffDem) with Goldstein filter and NL filter are applied to estimate glacier elevation changes between 2000 and 2013. The synergistic use of the DiffPha method and the NL filter is superior to other three combinations in terms of uncertainty and noise reduction. Generally, a clear surface thinning can be found in most glacier tongue regions, the maximum value of elevation lowering up to approximately −40 m, whereas a slight thickening is detected in accumulation areas, which are in agreement with the height difference results between GPS measurements and SRTM DEM over Laohugou Glacier No.12. This study demonstrates the potential of the TanDEM-X bistatic InSAR in mapping surface topography and elevation changes of valley glaciers in the Tibetan Plateau.

The TerraSAR-X add-on for Digital Elevation Measurements (TanDEM-X) bistatic system provides high-resolution and high-quality interferometric data for global topographic measurement. Since the twin TanDEM-X satellites fly in a close helix formation, they can acquire approximately simultaneous synthetic aperture radar (SAR) images, so that temporal decorrelation and atmospheric delay can be ignored. Consequently, the orbital error becomes the most significant error limiting high-resolution SAR interferometry (InSAR) applications, such as the high-precision digital elevation model (DEM) reconstruction, subway and highway deformation monitoring, landslide monitoring and sub-canopy topography inversion. For rugged mountainous areas, in particular, it is difficult to estimate and correct the orbital phase error in TanDEM-X bistatic InSAR. Based on the rigorous InSAR geometric relationship, the orbital phase error can be attributed to the baseline errors (BEs) after fixing the positions of the master SAR sensor and the targets on the ground surface. For the constraint of the targets at a study scene, the freely released TanDEM-X DEM can be used, due to its consistency with the TanDEM-X bistatic InSAR-measured height. As a result, a parameterized model for the orbital phase error estimation is proposed in this paper. In high-resolution and high-precision TanDEM-X bistatic InSAR processing, due to the limited precision of the navigation systems and the uneven baseline changes caused by the helix formation, the BEs are time-varying in most cases. The parameterized model is thus built and estimated along each range line. To validate the proposed method, two mountainous test sites located in China (i.e., Fuping in Shanxi province and Hetang in Hunan province) were selected. The obtained results show that the orbital phase errors of the bistatic interferograms over the two test sites are well estimated. Compared with the widely applied polynomial model, the residual phase corrected by the proposed method contains little undesirable topography-dependent phase error, and avoids unexpected height errors ranging about from −6 m to 3 m for the Fuping test site and from −10 m to 8 m for the Hetang test site. Furthermore, some fine details, such as ridges and valleys, can be clearly identified after the correction. In addition, the two components of the orbital phase error, i.e., the residual flat-earth phase error and the topographic phase error caused by orbital error, are separated and quantified based on the parameterized expression. These demonstrate that the proposed method can be used to accurately estimate and mitigate the orbital phase error in TanDEM-X bistatic InSAR data, which increases the feasibility of reconstructing high-resolution and high-precision DEM. The rigorous geometric constraint, the refinement of the initial baseline parameters, and the assessment for height errors based on the estimated BEs are investigated in the discussion section of this paper.

Technological developments in the field of photography, especially in the manufacture of 3D models from a collection of aerial photographs can be quickly and effectively with Unmanned Aerial Vehicle (UAV). This research was conducted in CI Durian River as the target object of 3D modeling. The study area located in Bogor regency, West Java province has a morphology of hills to low hills with winding rivers and composed by the Bojongmanik formation (Tmb). The dominant rock units in the study area are sandstone and claystone. The process of data retrieval using Unmanned Aerial Vehicle (UAV) can be used to perform mapping quickly and accurately at a more affordable cost. This research uses descriptive and interpretive methods. Primary Data in the study is all the data acquired through drones. Secondary Data are data such as slope maps and topographic maps. Primary Data and secondary data can be a reference in detecting landslides in the study area. The tool used in this study is to use unmanned Aerial Vehicle (UAV) technology in the form of drones by utilizing aerial photography data which is then processed into Digital Elevation Model (DEM) data. The use of Ground Control Point (GCP) can certainly add accuracy to the creation of DEM data. The Data is a reference in the interpretation of the threat of landslides that occurred in the study area. Primary data in the form of slope can validate secondary data in the form of slope maps. The dominant factors that influence the threat of landslides in the study area include: topographic factors and steep slopes. Topography and slope factors are very steep slopes are the main factors of high landslide threat in the study area.

Combined with the structure from motion (SfM) technique, unmanned aerial vehicles (UAVs) are powerful tools for generating high-resolution digital elevation models (DEMs) for application in hazard assessments. During our field observations in October 2015 at Langtang Village, which was destroyed by the Gorkha earthquake in April 2015, three different UAVs with mounted cameras were operated to evaluate the volume of the avalanche deposit covering the village. This study evaluated the performance of DEMs created from the different cameras on board those UAVs. Multiple DEMs for the different cameras, including Sony-α7R (PA7), Ricoh-GR (XGR), and Canon-IXUS (EIX), were created using SfM software. All DEMs were compared with a base DEM created from differential global positioning system survey data, which was obtained simultaneously with the UAV campaigns. The results show that the elevation difference of PA7-, XGR-, and EIX-DEMs are within ±0.14 m; the standard deviations of elevation difference range from 0.33 to 0.40 m. Although there were slightly larger differences in elevation on the southwest-to-west sides of the XGR- and EIX-DEMs, which can be attributed mainly to the flight paths and ground control point network, our DEMs are still of high enough quality to be used in hazard assessments.

The past few years have seen the raise of unmanned aerial vehicles (UAV) in geosciences for generating highly accurate digital elevation models (DEM) at low costs, which promises to be an interesting alternative to satellite data for small river basins. The reliability of UAV-derived topography as input to hydraulic modelling is still under investigation: here, we analyse potentialities and highlight challenges of employing UAV-derived topography in hydraulic modelling in a tropical environment, where weather conditions and remoteness of the study area might affect the quality of the retrieved data. We focused on a stretch of the Limpopo River in Mozambique, where detailed ground survey and airborne data were available. First, we tested and compared topographic data derived by UAV (25 cm), RTK-GPS (50 cm DEM), LiDAR (1 m DEM) and SRTM (30 m DEM); then, we used each DEM as input data to a hydraulic model and compared the performance of each DEM-based model against the LiDAR based model, currently used as benchmark by practitioners in the area. Despite the challenges experienced during the field campaign—and described here—, the degree of accuracy in terrain modelling produced errors in water depth calculations within the tolerances adopted in this typology of studies and comparable in magnitude to the ones obtained from high-precision topography models. This suggests that UAV is a promising source of geometric data even in natural environments with extreme weather conditions.