KEYWORDS: Unmanned aerial vehicles, 3D modeling, Point clouds, Remote sensing, Sensors, Classification systems, Sustainability, RGB color model, Vegetation, Systems modeling
According to UN DESA (United Nations Department of Economic and Social Affairs) urban population will become 66 percent of the planet's population by 20501. Unmanned Aerial Vehicles (UAVs) are confirmed as rapid, efficient, lowcost and flexible acquisition systems for remote sensing data with high-resolution and accuracy (sub-meter to few centimeters)2. The urban environment observed at large scale is dynamic and ever changing due to the human activities, which is a real opportunity for UAV and its urban applications such as management of urban infrastructure3 building observation4, urban land cover classification using airborne LiDAR5 and automatic feature extraction for UAV-based cadastral mapping6. A typical photogrammetric UAV workflow consists of flight planning, image acquisition, camera calibration, image orientation and data processing, which can result in Digital Surface Models (DSMs), orthoimages and point clouds7. In this paper, we perform a rapid, multi UAV data acquisition on the territory Bulgarian city of Stara zagora for a single day. 3 fixed-wing UAV, model eBeeX, manufactured by the company AgEagle Aerial Systems, was used in the present survey. The urban mapping area covered by the drones is 31.215 km2. To gather the necessary information, the platform is equipped with a dedicated integrated photogrammetric sensor S.O.D.A with RTK functionality. All the imagery captured by the three drones are postprocessed in Pix4D Mapper v4.8. Highly accurate 3D point cloud, digital surface model (DSM) and high-resolution and accuracy orthophoto map are produced. The results obtained by the drones have a spatial resolution of 5cm per pixel and vertical accuracy between 5 – 10 cm. All the results are exported and published in easy-to-use formats.
In recent years, the planning and management of urban areas has undergone an increasingly profound process of digital transformation. This is directly linked to the concepts of digital geospatial twins and smart cities, which in turn place completely new demands on digital geospatial information, which is one of the main resources driving the digital transformation processes of modern cities. Last but not least, this precise geospatial information is also one of the important elements in dealing with the problems of climate change and the increasingly changing geographical environment in which modern cities are developing. Modern geo-information technologies and tools offer a wide range of opportunities, including those related to the provision of resources for effective urban planning. Nevertheless, the integration of these technological tools and the data they produce pose a number of challenges for both researchers and practitioners. This paper aims to explore the possibilities and analyze the opportunities for the augmentation of data obtained from digital photogrammetry by unmanned aerial systems with one of the most innovative and rapidly developing technologies, namely SLAM-based laser scanning. The integration between these tools has significant potential to provide high spatial resolution data, but also a number of outstanding issues, mostly related to their precise spatial referencing and integration in urban environments. This study presents and investigates a methodology for combining the application of SLAM laser scanning in urban environments georeferenced by control points from orthophotos collected by UAVs. This saves valuable time while providing the ability to quickly establish an efficient basis for the development of digital doubles of the urban environment for planning and land management purposes.
KEYWORDS: Buildings, Reflection, Air quality, Chemical elements, Air contamination, Analytical research, Climatology, Orthophoto maps, Data processing, 3D modeling
This study presents a methodological approach and the results of a geospatial localization analysis of selected residential areas of the Sofia Municipality, which are highly vulnerable in terms of Ambient air Quality (AQ). The objective is a scientifically sound selection of locations for the construction of additional Green Infrastructure (GI) elements. A targeted selection of 13 indicators was carried out on urban morphology, demography, geo-ecological conditions, and an annual average concentration of pollutants. The output data are organized in a spatial grid (250/250 m). A weighted overlay was performed to identify cells with a high need for the construction of GI as additional measures to regulate microclimatic conditions and the associated AQ. Additional prioritization has been carried out for units with largest number of schools, kindergartens, hospitals. They have been surveyed with unmanned aerial systems (E-BeeX SenseFly). A digital surface model in 3D point cloud and an orthophoto map were generated in Pix4D environment. As a result, 401 specific land properties have been identified for the construction of new GI or upgrading of existing GI elements to increase the potential for effective regulation of the urban microclimate and mitigation of the negative effects of air pollution. The study was conducted in 2022 by the National University Center for Geospatial Research and Technology on behalf of Sofia Municipality. The results will be used for the expansion of parks and gardens, the afforestation of inter-block spaces ("mud patches"), the greening of schoolyards and kindergartens, busy transport arteries, or other innovative green solutions.
The aim of this study is to present the possibilities of thermal photogrammetry, carried out by an Unmanned Aerial System (UAS) in determining the Local Climate Zones (LCZ) in the city of Burgas, Bulgaria. This LCZ-based methodological approach has been used as one of the major standards in the research practices of mapping and assessment of the effects of the Urban Heat Island phenomenon (UHI). А complex methodological approach specifically designed for the purpose of the study was applied, which includes the use of a flying wing type UAS and a specialized integrated sensor with a thermal calibrated camera and a photogrammetric one, as well as a developed scheme for the collection, processing, and modeling of the data. As a result, the thermal characteristics of the surface of the individual types of LCZ on the territory of the city of Burgas were determined and specified. The latter was used as an information basis for modeling and mapping the effect of the UHI and determining its intensity. The data were collected according to a predetermined sampling scheme within a two-year period (2021-2022) during the hottest months of the year for the city (July and August) by the National University Center for Geospatial Research and Technology. All in-situ studies were carried out after sunset, in the time interval 20:30 - 22:00, in order to eliminate the effect of direct solar radiation on the recorded temperatures of the different land cover types. Subsequently, the collected and processed data were cataloged and integrated into geographic database of the LCZ, and the potential thermal load of each individual LCZ and individual land cover types was estimated. The results have been discussed with the Municipality of Burgas and will be used in the development of a series of urban planning measures focusing on energy efficiency, human health (regulating ecosystem services from green infrastructure) and the conservation of protected areas (falling immediately within the municipality).
KEYWORDS: Deformation, LIDAR, Remote sensing, Data modeling, Associative arrays, Systems modeling, Laser scanners, 3D modeling, Point clouds, Photography
The aim of the present study is to present an integrated approach based on the use of both classical remote sensing data and data generated by Unmanned Aerial Systems (UAS) for the purpose of precise mapping and assessment of vertical deformations of large-scale landslides structure (160 ha) located in the Eastern Rhodopes region, Bulgaria. The evaluations and the mapping itself were carried out by means of different types of generated Digital Terrain Models (DTMs), reflecting the dynamics in the development of the structure over a long period of time. The DTMSs were generated on the basis of three groups of methods – vectorized data of large-scale topographic maps from the 1980s, photogrammetric data and data from airborne laser scanning (LIDAR) based on an unmanned aerial vehicle platform. The complex geospatial analysis of the different digital terrain models shows that as a result of the landslide, significant vertical deformations occurred in the study area, with their maximum amplitude ranging from -17,2meters to more than +20 meters. The results of the present study demonstrate the enormous possibilities of modern geoinformation technologies to integrate and analyze various data, approaches and methods, which provides the necessary tools for conducting long-term precise monitoring of territories affected by risk processes, including landslides.
This article aims to present the developed and applied methodology for the study, mapping, and evaluation of urban mobility patterns in the city of Sofia. The research is based on the combination and integration of GIS-based spatial analysis techniques and high-resolution data obtained through sensors based on state-of-the-art Unmanned Aerial Vehicle systems (UAVs). The results obtained from this study are adapted to their use for the purpose of supporting urban planning processes in the city and could greatly assist in the establishment of more adequate models for solving some of the most pressing problems of urban mobility in the urban area of Sofia.
This article aims to present the developed, adapted and applied methodology for the study, mapping, and evaluation of the effect and intensity of the urban heat island(UHI) within the urban space of the city of Sofia, while assessing its potential impact on the structure of the city and the prospects for its development and structure. For this purpose, a combination of GIS-based spatial analysis techniques is used, based both on the application of traditional satellite data sources and on the use of state-of-the-art unmanned aerial vehicle systems (UAVs), delivering highresolution information. The results obtained from the study are adapted towards their use for the purpose of supporting urban planning processes in the city and could greatly assist in the establishment of more adequate models of spatial planning in the urban area of Sofia, in the context of global climate change and the expected intensification of the UHI effects in the near future.
Over the last decades, massive forest decline has occurred in many countries because of prolonged periods of drought and anomalous climatic phenomena. Studies show that in most cases this is the result of a combination of unfavourable climatic conditions and impact of harmful biotic factors, mostly insect pests and fungal pathogens. The massiveness of these unfavourable phenomena, as well as the specificities of their occurrence and spatial distribution, including mountainous and difficult to access areas, require the application of flexible, high-tech methods of collecting and processing data and information, and in recent years, modern unmanned aerial platforms and systems. This article presents the used approach, the methodology for complex assessment and the results obtained in integrated application of the potential of modern unmanned aerial platforms and traditional entomological and phytopathological methods for field investigation of sanitary status of two protected areas in West Balkan Range in Bulgaria – Gornata koria Reserve and Chuprene Biosphere Reserve.
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