Aerial Photographs Research Articles

Proposal of a flood damage road detection method based on deep learning and elevation data

Identifying an inundation area after a flood event is essential for planning emergency rescue operations. In this study, we propose a method to automatically determine inundated road segments by floods using image recognition technology, a deep learning model, and elevation data. First, we develop a training model using aerial photographs captured during a flood event. Then, the model is applied to aerial photographs captured during another flood event. The model visualizes the inundation status of roads on a 100-m mesh-by-mesh basis using aerial photographs and integrating the information on whether the mesh includes targeted road segments. Our results showed that the F-score was higher, 89%–91%, when we targeted only road segments with 15 m or less. Moreover, visualizing in GIS facilitated the classification of inundated roads, even within the same 100-m mesh, which is a relevant finding that complements deep learning object detection.

The Environmental History of the Navazo Agroecosystem in Late Holocene Sand Bodies Along the Atlantic Coast of Andalusia, Spain

ABSTRACT Since the late Spanish Enlightenment, the agroecosystem of the Atlantic coast of Andalusia, through which coastal dune systems are cultivated via sunken gardens between sand berms, have attracted scholarly attention. The environmental history of these systems, known as Navazo, is the focus of this article. Through analysis of historical aerial photographs, we identify eight areas in which traditional Navazo land use was practiced. By studying landscape diversity and historical documentation we identify key aspects of the emergence and evolution of this agroecosystem. The results of this study indicate that Navazos originated through a combination of the natural properties offered by the region's coastal dune geomorphology, which was cultivated as vineyards since ancient times, as well as external cultural influences. Coinciding with the popularisation of potato consumption in the eighteenth century, earlier vineyards were, in some cases, completely replaced by Navazos. Due to transformations in traditional land use practices, created a contemporary version of the Navazo. The location and physical configuration of the Navazos, meanwhile, display strong similarities with archaeological remains of Plot-and-Berm agroecosystems from the southeastern Mediterranean dating from the Early Islamic period. This study presents evidence to better understand the function, cropping practices and irrigation of these systems. .

Traditional culture of settlements associated with the natural environment: the case of Yi minority Southwest China

ABSTRACT Traditional culture of settlement is an important medium to record the process of balance between human and nature, and it was passed down from generation to generation in different forms (e.g. sacrificial culture, social structure, belief worship). With the intensification of global multicultural integration, the integration relationship between culture and nature has become an important approach for the protection and inheritance of traditional culture. Now, the relationship between artistic creation and ecological environment has been extensively studied. The scientific consensus regarding the influence of ecological environment on artistic creation has gained widespread recognition. Nevertheless, previous research neglects the relationship of traditional culture and natural environment, as well as different spatial characteristics, which are closely related to agricultural production and living. Based on the in-depth investigation of 23 traditional settlements of Yi minority in Southwest China, this paper conducted spatial analysis based on aerial photography, satellite maps and field investigation to analyze the relationship of culture-environment-space. Our results showed that there are significant differences in settlement space (e.g. landscape pattern, landscape space, architectural form) of Yi minority distributed in different areas. Under the same cultural background, the dispersed layout appears in Liangshan with high altitude and cold climate; the mountain foot layout appears in Central Yunnan and Northwest Guizhou with flat terrain and mild climate; the centralized layout appears in Honghe with narrow valleys and hot climate. These results shows that traditional culture comes from the natural environment, and the settlement space built under the guidance of the traditional culture must be in harmony with the natural environment. Therefore, protecting the traditional culture plays an important role in the sustainable development of urban and rural settlements. In addition, our findings may serve to inheritance and protection of traditional culture in other area all over the world.

Research on intelligent monitoring technology for roof damage of traditional Chinese residential buildings based on improved YOLOv8: taking ancient villages in southern Fujian as an example

In the process of preserving historical buildings in southern Fujian, China, it is crucial to provide timely and accurate statistical data to classify the damage of traditional buildings. In this study, a method based on the improved YOLOv8 neural network is proposed to select aerial photographs of six villages in Xiamen and Quanzhou cities in Fujian Province as the dataset, which contains a total of 3124 photographs. Based on the high-resolution orthophotographs obtained from UAV tilt photography, the YOLOv8 model was used to make predictions. The main task in the first stage is to select the buildings with historical value in the area, and the model's mAP (Mean Accuracy Rate) can reach 97.2% in the first stage task. The second stage uses the YOLOv8 model to segment the images selected in the first stage, detecting possible defects on the roofs, including collapses, missing tiles, unsuitable architectural additions, and vegetation encroachment. In the second stage of the segmentation task, the mAP reaches 89.4%, which is a 1.5% improvement in mAP50 (mean accuracy) compared to the original YOLOv8 model, and the number of parameters and GFLOPs are reduced by 22% and 15%, respectively. This method can effectively improve the disease detection efficiency of historical built heritage in southern Fujian under complex terrain and ground conditions.

Retrospective assessment of mine impacts: a case study using palaeoecology, aerial photography and maps from North Stradbroke Island (Minjerribah), Australia

ABSTRACT Mining is an environmentally destructive human activity. Consequently, community expectations and legislation require minimisation of impacts and rehabilitation once mining ceases. Rehabilitation standards now include restoration of structural and functional attributes of pre-disturbed landscapes. However, insufficient baseline data before, and during, mining often makes it difficult to assess impacts and develop rehabilitation objectives. Techniques that retrospectively document the pre-impact condition and environmental history of wetlands affected by mines can provide this information. We demonstrate how this can be achieved using data from palaeoecology and remote sensing, to understand mine impact on Fishermans Wetland, North Stradbroke Island (Minjerribah), by inferring its environmental history from formation to present. Fishermans Wetland is a small, clear, open water, wetland with extensive macrophyte growth. A lack of information about the wetland’s pre-mine condition created uncertainty about the effects of upstream sand mining. Contrary to local community concerns that Fishermans Wetland was ancient and hydrologically modified by mining, it only formed in the 1950s. Moreover, changes to site hydrology predated mining. Consequently, ongoing supplementation of water is unnecessary for maintaining the wetland’s ecological character. Similar techniques could be used elsewhere where mine impacts are poorly understood or contested.

A methodological approach to rock art survey and recording via drone. The application to the Rock Art of the Mediterranean Basin of the Iberian Peninsula assemblage

The significant advancement in drone technology has led to increased usage across different scientific domains. In the field of archaeology, drones became increasingly popular a decade ago, primarily for photogrammetric documentation or aerial photography. Since then, researchers have experimented with new applications, notably utilizing LiDAR imagery to enhance archaeological surveying. In this context, one of the latest applications involves surveying open-air rock art shelters in inaccessible locations to search for prehistoric rock art imagery. The current study involves refining the methodology used for this purpose in the territory of UNESCO’s World Heritage List property Rock Art of the Mediterranean Basin of the Iberian Peninsula, utilizing the DJI Mavic 3 foldable drone, which represents a significant improvement over previous models. On the other hand, it highlights the potential for its utilization in conservation studies and managing human activity in their environments, considering the threats to which these sites are currently exposed.

Sea ice melt pond bathymetry reconstructed from aerial photographs using photogrammetry: a new method applied to MOSAiC data

Abstract. Melt ponds are a core component of the summer sea ice system in the Arctic, increasing the uptake of solar energy and impacting the ice-associated ecosystem. They were thus one of the key topics during the 1-year drift campaign Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) in the Transpolar Drift 2019/2020. Pond depth is a dominating factor in describing the surface meltwater volume; it is necessary to estimate budgets and used in model parameterization to simulate pond coverage evolution. However, observational data on pond depth are spatially and temporally strongly limited to a few in situ measurements. Pond bathymetry, which is pond depth spatially fully resolved, remains unexplored. Here, we present a newly developed method to derive pond bathymetry from aerial images. We determine it from a photogrammetric multi-view reconstruction of the summer ice surface topography. Based on images recorded on dedicated grid flights and facilitated assumptions, we were able to obtain pond depth with a mean deviation of 3.5 cm compared to manual in situ observations. The method is independent of pond color and sky conditions, which is an advantage over recently developed radiometric airborne retrieval methods. It can furthermore be implemented in any typical photogrammetry workflow. We present the retrieval algorithm, including requirements for the data recording and survey planning, and a correction method for refraction at the air–pond interface. In addition, we show how the retrieved surface topography model synergizes with the initial image data to retrieve the water level of individual ponds from the visually determined pond margins. We use the method to give a profound overview of the pond coverage on the MOSAiC floe, on which we found unexpected steady pond coverage and volume. We were able to derive individual pond properties of more than 1600 ponds on the floe, including their size, bathymetry, volume, surface elevation above sea level, and temporal evolution. We present a scaling factor for single in situ depth measurements, discuss the representativeness of in situ pond measurements and the importance of such high-resolution data for new satellite retrievals, and show indications for non-rigid pond bottoms. The study points out the great potential to derive geometric properties of the summer sea ice surface emerging from the increasingly available visual image data recorded from uncrewed aerial vehicles (UAVs) or aircraft, allowing for an integrated understanding and improved formulation of the thermodynamic and hydrological pond system in models.

Analysis of land-use change in Mandrolisai 1860 to 2016: a case study from Sardinia (Italy)

ABSTRACT The focus on rural landscapes, already present in ‘Agenda 2000’, is reconfirmed for the CAP 2023–2027 (Green Deal). The CAP programmes have, however, often turned out to be generic and unsuited to the multifaceted reality of Mediterranean Europe, while FAO-GIAHS and UNESCO World Heritage programmes suit large territories. Both, as well as the CAP, support the conservation or renaturalisation of rural landscapes but cannot apply prescriptions at the planning stage. In Italy, the ‘Code of Cultural Heritage and Landscape’ contains prescriptive measures that the regions must include in their Landscape Plan (RLP); the municipalities must then adopt Urban Plans in accordance with the RLP. In Sardinia, RLP has protected the coastal areas (49.6 per cent of the 24,000 km2 surface area of the island) since 2006 but does not provide detailed guidelines for inland areas. We therefore tested the methodology proposed by the Ministry of Agriculture for recovering Historic Rural Landscapes in a study area of 23.63 km2 located in the heart of the island (in Mandrolisai region), where the two rural villages of Atzara and Sorgono border a system of traditional vineyards. Comparison of the 1860–1880 Land Register data, images from the first (1954) and last air flight (2016) shows that the agro-silvo-pastoral system has not changed structurally. In 2016, 53 per cent of the analysed area retains the same land-use macrocategories as the 1954 aerial photographs. Despite wide fluctuations in some agricultural crops, the most characteristic ones tend to occupy the same places, e.g., 72 per cent of 2016 vineyards compared to 1954. The biggest changes have been the transformation of natural pastures into cork oak wooded pastures, due to the sustained demand for cork.

Shrinking Green Footprint in Future Urbanism: Urban Green Space Analysis and Monitoring Using Remote Sensing Data

The rapid expansion of urbanization globally, has resulted in gradual disappearance of green spaces, threatening the quality of urban life and environmental sustainability. Conventional methods like Field Surveys, Aerial Photography and Satellite Imagery, fail to capture real-time data for effective urban planning and management. This study explores innovative solutions, harnessing remote sensing and GIS technology, to combat the diminishing urban green footprints. Through effective integration of these tools, we aim for precise urban green space assessments, tracking transformations and empowering planners. Thereby, promising substantial green space preservation, to enhance urban resilience. This research connects remote sensing, GIS and architecture/planning, empowering decision-makers with timely insights. This study investigates three cases of diverse urban landscapes - Bangalore, Singapore and Abu Dhabi, to ensure the applicability and versatility of the proposed solution in varied urban contexts. This study concludes with a focus on policy proposals and minor interventions, to facilitate sustainable urban growth.

Detection Based on Semantics and a Detail Infusion Feature Pyramid Network and a Coordinate Adaptive Spatial Feature Fusion Mechanism Remote Sensing Small Object Detector

In response to the challenges of remote sensing imagery, such as unmanned aerial vehicle (UAV) aerial imagery, including differences in target dimensions, the dominance of small targets, and dense clutter and occlusion in complex environments, this paper optimizes the YOLOv8n model and proposes an innovative small-object-detection model called DDSC-YOLO. First, a DualC2f structure is introduced to improve the feature-extraction capabilities of the model. This structure uses dual-convolutions and group convolution techniques to effectively address the issues of cross-channel communication and preserving information in the original input feature mappings. Next, a new attention mechanism, DCNv3LKA, was developed. This mechanism uses adaptive and fine-grained information-extraction methods to simulate receptive fields similar to self-attention, allowing adaptation to a wide range of target size variations. To address the problem of false and missed detection of small targets in aerial photography, we designed a Semantics and Detail Infusion Feature Pyramid Network (SDI-FPN) and added a dedicated detection scale specifically for small targets, effectively mitigating the loss of contextual information in the model. In addition, the coordinate adaptive spatial feature fusion (CASFF) mechanism is used to optimize the original detection head, effectively overcoming multi-scale information conflicts while significantly improving small target localization accuracy and long-range dependency perception. Testing on the VisDrone2019 dataset shows that the DDSC-YOLO model improves the mAP0.5 by 9.3% over YOLOv8n, and its performance on the SSDD and RSOD datasets also confirms its superior generalization capabilities. These results confirm the effectiveness and significant progress of our novel approach to small target detection.

Geological Mapping of Kaso, Tambaksari, Ciamis, West Java Province Using Lidar Images Interpretation

Abstract Remote sensing nowadays is used to quickly and effectively obtain information about an object, area or phenomenon and can be applied to large areas that are sometimes difficult to reach. Satellites with multispectral imagery are commonly used in geological mapping, but have drawbacks when used in tropical areas such as Indonesia, with dense vegetation, fast sedimentation rates and highly weathered that will cover fresh rocks making it difficult to interpret geological condition through aerial photo. Light Detection And Ranging (LiDAR) images using laser beams to produce elevation data (x,y,z) with high spatial resolution and can penetrate the surface of vegetation are expected to be a solution in areas with dense vegetation that are sometimes difficult to reach. The study was conducted by interpreting the morphometric aspects using Digital Terrain Model (DTM) data processed from LiDAR imagery with a spatial resolution of 1 m/pixel to display the topographical surface in detail. The morphometric aspects used include slope, surface roughness, aspect, hillshade, and stream pattern. Field data validation through surface mapping is carried out to correct the lithology interpretation by comparing the results of LiDAR image interpretation. Field data validation results show that interpretation using LiDAR imagery has good results (79%) through overall accuracy percentage, with the lithology units being sandstones, siltstone, breccias, and andesitic igneous rocks. The lineament interpretation of the DTM data indicates the existence of a geological structure in the form of a normal and strike-slip fault in the study area.

Att-Mask R-CNN: an individual tree crown instance segmentation method based on fused attention mechanism

Tree detection and canopy area measurement are important and difficult tasks in forest inventory, which are important for understanding forest stand structure. This study utilized remotely piloted aircraft (RPA) aerial photography technology to collect remote sensing images of forests in Xiong County, China, creating a dataset comprising 1200 images of six tree species. Based on this dataset, the paper proposes an optimized model, Att-Mask R-CNN, for canopy detection and segmentation. Att-Mask R-CNN outperforms the original models (Mask R-CNN and MS R-CNN) by achieving 65.29% mean average precision for detection, 80.44% mean intersection over union for segmentation, and 90.67% overall recognition rate for the six tree species. In addition, a pixel statistics method based on segmentation masks is introduced for estimating the vertical projected area of individual tree crowns, and comparisons between the measured and predicted vertical projected area of the crowns of six tree species (100 trees of each class) show an overall goodness-of-fit R2 of 85% and a relative root-mean-square error rRMSE of 12.81%. By using remote sensing images from RPAs and optimizing existing deep learning models, the detection and segmentation of individual tree canopies can be achieved, resulting in a more accurate understanding of forest structure, which provides scientific support for forest management and resource monitoring.

Integrating Depth Measurements From Gaging Stations With Image Archives for Spectrally Based Remote Sensing of River Bathymetry

AbstractRemote sensing can be an effective tool for mapping river bathymetry, but the need for direct measurements to calibrate image‐derived depth estimates impedes broader application of this approach. One way to circumvent the need for field campaigns dedicated to calibration is to capitalize upon existing data. In this study, we introduce a framework for Bathymetric Mapping using Gage Records and Image Databases (BaMGRID). This workflow involves retrieving depth measurements made during gaging station site visits, downloading archived multispectral images, and then combining these two data sets to establish a relationship between depth and reflectance. We developed a processing chain that involves using application programming interfaces to obtain both depth measurements made during site visits and images centered on the gage and then linking depth to reflectance via an optimal band ratio analysis (OBRA) algorithm modified for small sample sizes. Applying this workflow to selected gages within two river basins indicated that depth retrieval from multispectral satellite images could be highly accurate, but with variable results from one image to the next at a given site. High resolution aerial photography was less conducive to bathymetric mapping in one of the basin considered. Of the four predictors of depth retrieval performance we evaluated (mean and standard deviation of depth, width, and an index of water clarity), only width was consistently significantly correlated with OBRA R2 (p < 0.026). Currently, BaMGRID is best‐suited for site‐by‐site analysis to support practical applications at the reach scale; continuous, basin‐wide mapping of river bathymetry will require additional research.

SEGMENTATION OF PARCEL BOUNDARY INDICATIONS IN VERY HIGH-RESOLUTION ORTHOPHOTO MOSAICS FOR CONTROL POINT IDENTIFICATION

Several Land Parcel Geometry issues in Indonesia's Land Registration Process, such as parcel overlapping, gaps between parcels, and incorrect parcel shapes and sizes, are currently being addressed through a block adjustment approach. One crucial aspect of the block adjustment process is determining control points that tie the parcel geometry to the land coordinate system. Detailed Observations and measurements of parcel points in the field and aerial photographs established these control or tie points. Rectifying land parcels requires many control points, requiring substantial time and effort. The automation phase is critical to expedite the control point identification process. This research uses artificial intelligence techniques to identify control points in very high-resolution orthophoto mosaics. The method employed for control point identification involves the Segment Anything Model (SAM) algorithm to segment parcel boundary indications accurately. Enhance the quality of segmentation results conducted by fine-tuning, followed by centerline extraction and refinement of the extracted data. Based on the segmentation, a SAM model capable of accurately segmenting building objects is attained, After the centerline extraction process and modifications to the existing geometric operations within the GIS Tool, at the edges of buildings, fences, and walls derived points. These points can serve as control point indications in the block adjustment process.

UAV Mapping for Flood Routing in Steep and Densely Vegetated Areas: Insights from the Contok River Basin, Garang Watershed, Indonesia

This research utilizes photogrammetry to assess flood routing dynamics in the Contok river basin, a sub-watershed with a challenging landscape characterized by steep slopes, dense vegetation, and meandering patterns. The objectives are to assess Unmanned Aerial Vehicle (UAV) mapping accuracy, evaluate the river's capacity for design flood volumes, quantify the impact of land cover changes on surface runoff, and provide insights for early warning systems and watershed conservation strategies. The study area, encompassing the Contok River Basin, a sub-watershed of the Garang Watershed, covers 7,413 km² and includes a stream length of 5,274 meters in Semarang City, Central Java, Indonesia. This research employed image processing of aerial photographs and satellite imagery. Aerial photos captured using UAV data were utilized to derive elevation data and cross-sectional profiles of the Contok River, essential for understanding channel morphology and hydraulic characteristics. Concurrently, satellite imagery was used for land cover analysis, identifying vegetation and built-up areas that influence surface runoff dynamics. Hydrological analysis was performed to quantify discharge magnitudes, simulated against river cross-sections to evaluate flood behavior under varying scenarios. Our proposed UAV mapping provides adequate accuracy for small and local areas. Furthermore, it remains reliable for flood routing analysis. We discovered that the capacity of the Contok River channel in the downstream area allows it to convey design flood discharges up to a 50-year return period, contrary to the upstream area, it overflows. Notably, the shift from vegetated to built-up and agricultural areas significantly contributes to the 10.6% increase in surface runoff. This research highlights the role of UAV-based photogrammetry in assessing and mitigating flood hazards amidst evolving land cover patterns. It also enhances the understanding of flood dynamics and thus provides insights that will serve as a reference for flood early warning systems, flood management practices, and watershed conservation.

ANALISIS POLA PERUBAHAN LAHAN SAWAH MENGGUNAKAN SISTEM INFORMASI GEOGRAFIS (STUDI KASUS: KELURAHAN MAKROMAN, SAMARINDA)

Changes in rice fields are an important phenomenon that affects the sustainability of agriculture and the environment. This study aims to analyze the pattern of changes in rice fields in Makroman Village, using a Geographic Information System (GIS) approach. The method used is spatial analysis which involves such as spatial data creation, spatial data conversion, spatial data clustering, and mathematical calculation of spatial data. The spatial data used in this study include Ikonos Satellite Images of Makroman Village in 2011 and UAV Aerial Photos of Makroman Village in 2019. The results showed that the area of rice fields in Makroman Village increased from 96.196 ha to 129.343 ha in 2011-2019. Spatially, the increase occurred due to the presence of new rice fields and existing rice fields that did not decrease in number. Shrubs become land uses that have the potential to be converted in rice field extensification activities. GIS application is a method that can be used to answer the problems in this study to the level of detail, but some things that need to be considered in the application of this method are the quality of spatial data, especially remote sensing data used.

Utilization of the DJI Phantom 3 Advance Quadcopter Type Drone Vehicle for Area Mapping of the Samarinda State Agricultural Polytechnic Campus

This research is motivated by the fact that currently remote sensing technology continues to develop, both in terms of data collection and processing. This is characterized by the existence of data collection techniques using unmanned aerial vehicles for aerial photo mapping. The advantage of using this technology is that it is effective and efficient both in terms of time and human resources for mapping in areas that are not too large. Another advantage is that it can produce clearer photos, because the plane's flying height is below 400 meters above ground level so that during the shooting process there is no cloud interference. The aim of this research is to create an aerial photo map at the Samarinda State Agricultural Polytechnic, validate objects in aerial photos and in the field, and provide information about the area, boundaries and topography of the Samarinda State Agricultural Polytechnic campus area. The implementation of activities and research objects is the Samarinda State Agricultural Polytechnic campus area. This research uses a small format aerial photo mapping method using a Quadcopter, making it easier to determine where to start taking off and landing. With a Quadcopter vehicle, grounding problems are no longer an obstacle. The research results showed that photography carried out with a Quadcopter at a height of 200 m above the ground produced an area of 28.17 Ha and a spatial resolution of 8.40 cm/pixel. The validation results in aerial photos and in the field using drones have a small difference between 0-4 cm with an average of 1.625 cm/photo. From the digitization results of campus objects, there are 30 objects on campus with a total area of 2.67 Ha. As for the topography results in the campus area, the highest point is 107.5 meters above sea level and the lowest point is 60 meters above sea level.

Оценка развития опасных склоновых процессов и явлений в районе проектирования и строительства всесезонного туристско-рекреационного комплекса «Мамисон»

This paper presents the ortho-photomap we created of the territory of the all-season tourist and recreational complex “Mamison” (ATRC “Mamison”) using the example of the Kozy-Don gorge, which was obtained using a DJI Mavic Air 2 unmanned aerial vehicle. The compiled ortho-photomap of the Kozy-Don gorge quite fully displays the terrain, which made it possible to create a DTM (digital terrain model) with a given image scale. Using DTM, areas of development of dangerous slope processes, such as avalanches, mudflows, etc., were identified. The data obtained with the help of UAVs are already being used for the research and development of mountainous areas, and are also taken into account in the design and construction of national economic facilities of the Mamison ATRC. Materials and methods. In this work, the creation of an ortho-photomap of the Mamison territory is shown using the example of the Kozy-Don gorge, where mudflow and avalanche activity is widespread. During the field work, aerial photography of the gorge’s relief was taken for further image processing in the Agisoft Metashape Professional software package. Results. About 1000 photographs were taken, of which 952 were aligned. Based on the aligned photographs, more than 551 thousand tie points were automatically constructed, reflecting relief characteristics. Based on the aligned photographs, more than 551 thousand tie points were constructed, reflecting relief characteristics. A denser cloud of points was built to clarify the characteristics of the relief; as a result of processing, a clearer relief model was obtained. Based on a dense point cloud, a digital model of the study area was built, with the relative heights of the Kozy-Don gorge. Using the resulting DTM, a map of average relief slopes was constructed, which was necessary to determine avalanche danger zones. Also, based on the DTM, an ortho mosaic was built for the territory of the Kozy-Don gorge. Discussion. During the field work, the Kozy-Don gorge was examined on the territory of the All-Russian Technical Complex. Aerial photography of the gorge’s relief was taken for further image processing in the Agisoft Metashape Professional software package. 194 photographs were taken. The photo database was created using the standard shooting equipment of the DJI Mavic Air 2 unmanned aerial vehicle. Based on the results of photo processing using software, an orthomosaic map was constructed for the territory of the Kozy-Don gorge of the Mamison ATRC. Conclusions. The created ortho-photomap of the Kozy-Don if ATRC “Mamison” quite fully reflects the topography of the study area. It allows you to select individual areas in the form of a 3-model with a given image scale. Resume. Based on aerial photography, a digital terrain model with relative heights is built. It allows you to select and form, in the form of a separate file, areas of development of dangerous slope processes – avalanches, mudflows, landslides. Suggestions for practical applications and directions for future research. The research results obtained using an unmanned aerial vehicle can be useful in the exploration and development of mountainous areas, especially where the terrain is difficult to pass and where stationary research is not conducted.

On the Methodology of Analysing Aerial and Satellite Images to Detect Archaeological Sites

Today, the use of remote sensing methods is an integral part of archaeological research. The use of various types of aerial and satellite photography at the level of micro-regions makes it possible to collect data on large areas in a short time. The received data are subject to archaeological deciphering – the process of recognition, detection and interpretation of archaeological information based on photographic images of the Earth’s surface. In the course of deciphering pictures, photographic images of objects are analysed, which have a number of decipherable features, that is, characteristic ones by which archaeological objects can be recognised. Modern processing and recording of these data is carried out in geoinformation systems, taking into account their spatial reference. The analysis of domestic publications showed that this direction is promising for future research in Ukrainian archaeology. However, the researchers do not provide a general, clear methodology for working with aerial photography materials and features of archaeological deciphering. Summarising this information prompts the creation of a consistent description of such work. This description is intended to formalise those research operations, which in one way or another were performed by the above-mentioned authors. The paper is an attempt to create a methodology for the archaeological deciphering of aerial and satellite photos for the remote study of archaeological monuments and the protection of archaeological heritage. It is intended to summarise the previous experience of publishing the methodology of working with remote sensing of the land in the archaeology of Ukraine and to structure it on the basis of our own developments. The proposed scheme is not final or mandatory, but only offers one of the options for the approach to thematic deciphering in archaeology. Undoubtedly, the given algorithm of actions will require improvement and expansion as a result of the accumulation of practical experience and theoretical achievements. It is important to emphasise that this branch of archaeology is closely related to technical sciences and technologies in general and therefore requires thoughtful introspection and competent theorising. To obtain reliable results of deciphering in archaeology, it is necessary to always pay attention to the analysis of the research process and the multi-level process of checking its results. The reliability of the obtained data definitely depends on the clarity and awareness of the sholar’s actions, which in turn has a great impact on various fields of archaeological science, and even national security. The reliability of data depends on the “purity” of research operations, which is extremely important in the process of monitoring archaeological objects. The current state of archaeological monuments in Ukraine in the conditions of martial law, and especially on the territories of hostilities, requires urgent monitoring. With the help of modern aerial and satellite photographs, it is especially relevant and necessary today to investigate the damaged archaeological landscapes, wide application of remote sensing of land, satellite navigation systems and geo-information technologies with decoding, for the collection, processing and analysing the information in combination with the data of specific aerial visual surveys using drones and traditional methods of surveys in those areas where it is possible.

Evolution of flight control systems and aerial photography in unmanned agricultural aircraft

The advancement of UAV technologies has enabled the automated capture of photos and videos, eliminating the need for manual intervention in flight control. (Research purpose) This research aims to conduct a retrospective analysis of the evolution offlight control systems and the development of aerial photography equipment for agricultural land, covering the period from the mid-19th century to present. (Materials and methods) A systematic literature review was conducted using the historical-analytical method. The paper examines original works by both domestic and international authors, including monographs, scientific journals, conference proceedings, museum exhibitions, photographic archives, and open-source software code. (Results and discussion) The paper identifies six distinct phases in the development of aerial photography and flight control systems. The classification is based on key innovations in camera types, control systems, and aircraft designs. Each phase highlights the predominant cameras, control systems, and aircraft utilized for agricultural applications. (Conclusions) Over the past 165 years, notable changes have occurred in aerial photography parameters, including the type of photographic material, image spatial and spectral resolution, camera weight and mounting, shutter types and their mechanisms, inertial control units, integrated GPS/GLONASS receivers, and light sensors. In terms of flight control systems for UAVs, significant developments over the last 106 years include variations in flight control types, the number offlight-stabilizing sensors, obstacle detection systems, size of the flight control units, flight modes, and takeoff/landing techniques, along with interfaces for attachments. It is anticipated that future intellectualization and miniaturization of flight control systems will not only boost UAV performance but also reduce the economic costs associated with the aerial monitoring of agricultural biological assets.