Сurrent state of securing the territory of Рoltava region by points of the national geodesic network

The actual problem of securing the proper functioning of the NGN of Ukraine takinginto account regional peculiarities are studied.The analysis of the state of NGN of Ukraine on the territory of Poltava region by types ofcenters, external geodetic signals, methods of determination of coordinates is carried out in the work.The general problems of functioning of NGN in the territory of Poltava region are established.It is established that in a significant amount of points there are no external geodetic signals.The centers that fix the points of the NGN are represented by more than 40 different types. The centersdiffer in design and size. Some of them are at the same time is references of leveling II category.It is proposed to plan perspectiving measures for the modernization of the NGN on the reasonof the calculation of indicator of regional compliance of the NGN with regulatory requirements forthe density of stations to secure the implementation of topographic surveys. This indicator iscalculated as the ratio of the real amount points in the newly created administrative district to thenormative amount, and is reflected as a percentage. The normative amount is determined on the basisof the area of the respective area and the normative density of stations for the suitable scale of survey.In case of provision of stations at the level of less than 100 % it is necessary to determine theamount of points required to bring the real density in accordance with the normative. Then theexisting NGN needs modernization. Such modernization can be carried out not only in the form of renewal of existing and restoration of lost points, but also through the design and fixation ofadditional points of the calculated number.The analysis of securing of the territory of Poltava region with NGN points for implementationof topographic survey in scales 1:5000, 1:10000, 1:25000 is carried out. Specific proposals toachieve one hundred percent provision of stations in the Poltava region have been developed. Anexample of a possible realization of the respective proposals is illustrated by the design scheme ofadditional stations of the 3 class, developed on the basis of the scheme of the NGN of Ukraine.

Remote Sensing of Landslide-Generated Sediment Plumes, Peace River, British Columbia

Quantifying the contribution of sediment delivered to rivers by landslides is needed to assess a river’s sediment load in regions prone to mass wasting. Monitoring such events, however, remains difficult. This study utilised six years of remotely sensed imagery (PlanetScope and RapidEye, Imagery courtesy of Planet Labs, Inc., San Francisco, CA, USA), topographic surveys, and field observation to examine a hydro-geologically controlled, retrogressive landslide near a tributary to the Peace River, British Columbia. The slide has been active since 2014, delivering large amounts of sediment to the Peace River, visible in a persistent plume. Here, we quantify the landslide’s sediment contribution to the Peace River, assess the hydro-meteorological drivers of plume variability, and test whether plume activity can be directly linked to landslide activity for monitoring purposes. Our results show that the landslide on average delivered 165,000 tonnes of sediment per year, a seven-fold increase of the tributary’s regular load and near half of the Peace River’s load at this location. Due to continuous erosion of landslide material, sediment supply is steady and fuelled by repeated failures. Using thresholding, the identification of ‘high’ plume activity was possible, which positively correlated with the water level in a nearby reservoir, a proxy for the state of groundwater in this region. We reason that ‘high’ plume activity is linked to increased groundwater pressure because landslide activity is groundwater-controlled and failures fuel sediment delivery to the Peace River. Using readily available imagery, it is thus possible to monitor the activity of this recurrent landslide when field data are difficult to obtain.

Practical implementation of the use of GNSS RTK technologies for obtaining topographic and geodetic data

This paper analyzes the use of GNSS equipment when conducting topographic surveys. It was revealed that despite the presence of a large number of modern and high-precision GNSS receivers, nowadays, the regulatory and legal framework has established significant restrictions on the use of GNSS equipment when carrying out topographic and geodetic surveys. According to the current legislation, this equipment cannot accurately determine coordinates and heights on the ground. To prove the opposite, a scientific experiment was carried out, as a result of which it was found that modern GNSS receivers can more accurately determine coordinates and heights on the ground than modern total stations and electronic theodolites. Therefore, it is recommended to use the obtained data of the experiment as a basis for making changes to the regulatory framework.

Mapping Karakorum, the capital of the Mongol Empire

ABSTRACT In the thirteenth century AD, the city of Karakorum was founded as the capital of the Mongol Empire. Relatively little archaeological attention, however, has been directed at the site and the phenomenon of steppe urbanism. The authors report new magnetic and topographic surveys of the walled city and the surrounding landscape. The resulting maps reveal the city in unprecedented detail. Combining the magnetic and topographical data with aerial photographs, pedestrian surveys and documentary sources reveals the extent, layout and organisation of this extensive settlement. Road networks and areas of variable occupation density and types of activities deepen our understanding of this important commercial hub and royal palace, which is conceptualised as a form of ‘implanted’ urbanism.

Reconstruction of the Settlement Levoberezhnoe Plan of the Bronze Age (South Ural, Russia)

In the Southern Urals in 2015–2019 research was conducted on the fortified settlement of the Bronze Age Levoberezhnoe (Sintashta II). An asphalt road was drawn through the settlement, during the construction of which about a third of the monument’s area was destroyed. Excavations of the monument have been carried out since 2015. It has been established that the settlement is multi-layered; it functioned in the Late Bronze Age from the turn of the 3rd–2nd millennium BC until the last quarter of the second millennium BC. Detailed magnetic and topographic surveys were performed on the territory that remaining survived the construction of the road. The location of the external moat was reliably determined by linear positive magnetic anomalies. The base of the outer wall of the settlement had a thickness of about 4 m, the width of the outer moat was 2–2.5 m. It was also possible to accurately localize a number of walls of buildings. The settlement had a rectangular shape, inside there were 26 dwellings. As a result of a comprehensive analysis of the data and aerial photographs of the last century, the layout of the entire settlement was reconstructed.

Improvement of Workflow for Topographic Surveys in Long Highwalls of Open Pit Mines with an Unmanned Aerial Vehicle and Structure from Motion

Conducting topographic surveys in active mines is challenging due ongoing operations and hazards, particularly in highwalls subject to constant and active mass movements (rock and earth falls, slides and flows). These vertical and long surfaces are the core of most mines, as the mineral feeding mining production originates there. They often lack easy and safe access paths. This framework highlights the importance of accomplishing non-contact high-accuracy and detailed topographies to detect instabilities prior to their occurrence. We have conducted drone flights in search of the best settings in terms of altitude mode and camera angle, to produce digital representation of topographies using Structure from Motion. Identification of discontinuities was evaluated, as they are a reliable indicator of potential failure areas. Natural shapes were used as control/check points and were surveyed using a robotic total station with a coaxial camera. The study was conducted in an active kaolin mine near the Alto Tajo Natural Park of East-Central Spain. Here the 140 m highwall is formed by layers of limestone, marls and sands. We demonstrate that for this vertical landscape, a facade drone flight mode combined with a nadir camera angle, and automatically programmed with a computer-based mission planning software, provides the most accurate and detailed topographies, in the shortest time and with increased flight safety. Contrary to previous reports, adding oblique images does not improve accuracy for this configuration. Moreover, neither extra sets of images nor an expert pilot are required. These topographies allowed the detection of 93.5% more discontinuities than the Above Mean Sea Level surveys, the common approach used in mining areas. Our findings improve the present SfM-UAV survey workflows in long highwalls. The versatile topographies are useful for the management and stabilization of highwalls during phases of operation, as well closure-reclamation.

Deep learning for automated river-level monitoring through river-camera images: an approach based on water segmentation and transfer learning

River-level estimation is a critical task required for the understanding of flood events and is often complicated by the scarcity of available data. Recent studies have proposed to take advantage of large networks of river-camera images to estimate river levels but, currently, the utility of this approach remains limited as it requires a large amount of manual intervention (ground topographic surveys and water image annotation). We have developed an approach using an automated water semantic segmentation method to ease the process of river-level estimation from river-camera images. Our method is based on the application of a transfer learning methodology to deep semantic neural networks designed for water segmentation. Using datasets of image series extracted from four river cameras and manually annotated for the observation of a flood event on the rivers Severn and Avon, UK (21 November–5 December 2012), we show that this algorithm is able to automate the annotation process with an accuracy greater than 91 %. Then, we apply our approach to year-long image series from the same cameras observing the rivers Severn and Avon (from 1 June 2019 to 31 May 2020) and compare the results with nearby river-gauge measurements. Given the high correlation (Pearson's correlation coefficient >0.94) between these results and the river-gauge measurements, it is clear that our approach to automation of the water segmentation on river-camera images could allow for straightforward, inexpensive observation of flood events, especially at ungauged locations.

Morphodynamic Evolution of Post-Nourishment Beach Scarps in Low-Energy and Micro-Tidal Environment

Beach scarps are commonly associated with nourishment. Large and persistent beach scarps not only affect the performance of beach nourishment, but also are safety hazards to tourists. In this study, the morphological evolution of beach scarps was examined at a nourished beach in a low-energy and micro-tidal environment. Topographic surveys of nine beach profiles were carried out every 3–6 months after nourishment, lasting for nearly 4.5 years, combined with observed and simulated hydrodynamic data. The results showed that beach scarps were extensively developed after nourishment and migrated landward gradually. The formation of beach scarps was attributed to the higher designed berm, while the migration was possibly initiated by the subsequent higher total water level connected with the irregular tides. However, scarps were completely removed by the first post-nourishment severe storm and had been long absent ever since although two other energetic storms approached. This was different from the result of previous studies, which could be attributed to the much gentler upper beach slope. These results highlighted that the first post-nourishment storm played a key role in the evolution of beach scarps at low-energy and micro-tidal nourished beaches. This study also proposed two methods of determining berm elevation in beach nourishment according to China’s experiences, which would be helpful for other countries’ beach nourishment projects.

Deep learning for the estimation of water-levels using river cameras

River level estimation is a critical task required for the understanding of flood events, and is often complicated by the scarcity of available data. Recent studies have proposed to take advantage of large networks of river camera images to estimate the river levels, but currently, the utility of this approach remains limited as it requires a large amount of manual intervention (ground topographic surveys and water image annotation). We develop an approach using an automated water semantic segmentation method to ease the process of river level estimation from river camera images. Our method is based on the application of a transfer learning methodology to deep semantic neural networks designed for water segmentation. Using datasets of image series extracted from four river cameras and manually annotated for the observation of a flood event on the Severn and Avon rivers, UK (21 November–5 December 2012), we show that our algorithm is able to automate the annotation process with an accuracy greater than 91 %. Then, we apply our approach to year-long image series from the same cameras observing the Severn and Avon (from 1 June 2019 to 31 May 2020) and compare our results with nearby river-gauge measurements. Given the high correlation (Pearson's Correlation Coefficient > 0.94) between our results and the river-gauge measurements, it is clear that our approach to automation of the water segmentation on river camera images could allow for straightforward, inexpensive observation of flood events, especially at ungauged locations.