Automated Extraction of Heavyweight and Lightweight Models of Urban Features from LiDAR Point Clouds by Specialized Web-Software

Kostrikov, Sergiy; Pudlo, Rostyslav; Bubnov, Dmytro; Vasiliev, V. N.; Fedyay, Yury

doi:10.25046/aj050609

Cited by 4 publications

(6 citation statements)

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“…We only used the 2D visualization of urban green pattern changes to remain within the objective and scope of our research, which is to evaluate changes in the urban stand loss (USL) within an official boundary of a large city for a long period of time as on a yearly basis. The outlined research task can be resolved on the basis of our original multifunctional urban remote sensing (URS) approach (Kostrikov et al, 2020a;Kostrikov et al, 2020b) combined with the strong spatial aspect of a full-format GIS-platform functionality.…”

Section: Methodical Backgroundmentioning

confidence: 99%

Spatiotemporal Analysis of Urban Green Areas Using Change Detection: A Case Study of Kharkiv, Ukraine

Morar

Lukić

Valjarević

et al. 2022

Front. Environ. Sci.

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The contemporary globalized world characterizes the rapid population growth, its significant concentration in cities, and an increase in the urban population. Currently, many socio-cultural, economic, environmental, and other challenges are arising in modern cities, negatively affecting the state of the urban environment, health, and quality of life. There is a need to study these problems in order to solve them. Urban Green Areas (UGAs) are a part of the social space and a vital part of the urban landscape. They act as an environmental framework of the territory and a factor ensuring a more comfortable environment of human life. This study aims at substantiating the importance of the UGAs, identifying the spatiotemporal dynamics of their functioning, and transforming changes in their infrastructure given the expansion of their functions. This research was carried out as a case study of the second city in Ukraine, Kharkiv. The authors developed and used an original integrated approach using urban remote sensing (URS) and GIS for changes detection to evaluate the current state and monitor spatial transformations of the UGAs. We used several GIS platforms and online resources to overcome the lack of digital cadastre of the thematic municipal area of Kharkiv. This resulted in the present original study. The study analyses the dynamics of the spatial and functional organization of the UGAs according to the Master Plans, plans, maps, and functional zoning of the city for the period from 1867 to 2019. The peripheral green areas became important after the large-scale development of the extensive residential areas during the rapid industrial development in remote districts of the city. They provide opportunities for population recreation near living places. Central UGAs are modern, comprehensively developed clusters with multidisciplinary infrastructure, while the peripheral UGAs are currently being developed. The use of URS/GIS tools in the analysis of the satellite images covering 2000–2020 allowed identifying the factors of the UGAs losses in Kharkiv and finding that UGAs were not expanding and partially shrinking during the study period. It is caused by the intensive construction of the residential neighborhoods, primarily peripheral areas, infrastructure development, and expansion of the city transport network. Nonetheless, some sustainable trends of UGA functioning without more or less significant decrease could be proved as existing in a long-term perspective. The authors analyzed and evaluated changes and expansion of the UGAs functions according to modern social demand. The research value of this is the usage of different approaches, scientific sources, URS/GIS tools to determine the UGAs transformation in the second-largest city in Ukraine (Kharkiv), to expand and update the main functions of UGAs and their role in the population’s recreation. The obtained scientific results can be used to update the following strategies, programs, and development plans of Kharkiv.

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Section: Methodical Backgroundmentioning

confidence: 99%

Spatiotemporal Analysis of Urban Green Areas Using Change Detection: A Case Study of Kharkiv, Ukraine

Morar

Lukić

Valjarević

et al. 2022

Front. Environ. Sci.

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“…The fourth goal, which actually has to be achieved as the first one in a temporal perspective, is to simulate by LiDAR data processing the common building types, their formation, and changes as the various set of models: the basic building models (a "box" model), parametrized models, prismatic models, low-polyhedral models (LPM), and high polyhedral models (HPM) [47].…”

Section: Exposition Of the Main Research Material The Performance Of ...mentioning

confidence: 99%

The performance of the digital city projects in urban studies of the megalopolises (the case studies of Kharkiv and Dnipro cities)

Kostrikov,

Kravchenko,

Serohin

et al. 2023

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Introduction of the research problem. Urbanization drives Digital City Projects (DCPs) to create smarter urban environments using advanced technologies. DCPs aim to make cities more connected and responsive, adapting to changing needs. The objective of this paper is to evaluate the performance of DCPs in megalopolises, focusing on Kharkiv and Dnipro in Ukraine. The previous works done. The various literature sources demonstrate the rise of Digital Cities stemming from Smart Cities. Kharkiv and Dnipro in Ukraine exemplify digitalization's role amid Russian aggression. Exposition of the main research material. The performance of the theoretical urbogeosystemic approach and its UOM in the provision of practical Digital City projects. This subsection delves into the practical application of the urbogeosystemic approach and its Urban Ontological Model (UOM) in DCPs. The UOM guides urban studies by defining components and relationships. Implementing DCPs begins with building simulation models using LiDAR data. Case Study First - Kharkiv: A feasible perspective of a full-format DCP implementation. This subsection discusses implementing a DCP in Kharkiv, emphasizing data integration from OpenStreetMap (OSM) and LiDAR. The authors propose that a DCP should serve as a comprehensive model of a real city, encompassing all its structural elements and key objects, going beyond the capabilities of a typical GIS project. Possible user’s scenarios include energy consumption analysis, population estimation, and visibility gradients assessment. The subsection highlights the comprehensive DCP approach with LiDAR data processing software (iQ City CCM) and urban geosituational analysis. Case Study Second - Kharkiv: a perspective of geomarketing within the “Digital Kharkiv” project as a routine GIS one. This subsection delves into the integration of geomarketing into the "Digital Kharkiv" project. Geomarketing plays a pivotal role in mapping socioeconomic elements tied to market interactions. "Digital Kharkiv," primarily sourced from OSM data, is lauded for its versatility in urban studies during peacetime and war. The text urges exploration of geomarketing within "Digital Kharkiv" in the context of post-Russian aggression rehabilitation, particularly in optimizing humanitarian object placements. Changes in geomarketing potential pre- and post-invasion in various city districts have been analyzed, highlighting areas with stagnation and those witnessing growth due to population resettlement. Case Study Third - Dnipro: implementation of a typical GIS-project for analyzing provision of the city population with public transportation infrastructural networks. This subsection discusses the implementation of the "Digital Dnipro" project as part of the DCP framework. The project focuses on analyzing the provision of public transportation networks in the city of Dnipro. It utilizes data from OSM to create a virtual model of the city, which includes attribute information for urban objects. This subsection also highlights the impact of war on urban planning and the need for sustainable updates to adapt to changing conditions. Conclusion. This section summarizes the key findings and takeaways from the research on DCPs in Ukrainian cities like Kharkiv and Dnipro. It highlights the importance of an urbogeosystemic approach in implementing DCPs effectively. The study emphasizes the flexibility and efficiency of the relevant GIS tools in urban research and transformation.

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“…Corresponding functional tools of both ELiT-software platforms, which are set within the HPM frameworks are BE, BEF, CD, and DEM-G tools. The BE/BEF tools extract original building footprints from point clouds while modeling [39,43].…”

Section: Web-based Geoinformation Software For the Urbogeosystem Appr...mentioning

confidence: 99%

“…The relevant functional tool of the LPM approach is the BERA (Building Extraction Rural Area) tool. The BERA instrument employs the third-party building footprints while modeling [39,43]. If the HPM-technique with its heavyweight models is more preferable for simulation of the quasi-vectorized UE (Figure 4), then the LPM-method -for creation of the 3D quasi-vector lightweight models of buildings and other features as elementary functional constituents of a certain urban geographical system (Figure 5).…”

Section: Web-based Geoinformation Software For the Urbogeosystem Appr...mentioning

confidence: 99%

“…In comparison with the HPM pipeline, both planar segmentation and clustering substantially decrease the number of polyhedrons as constituents of a building model extracted. Thus, we attempted to provide an efficient update and an applied realization [43] of the advanced theoretical approach known as segmentation and reconstruction of polyhedral building roofs [18].…”

Section: Web-based Geoinformation Software For the Urbogeosystem Appr...mentioning

confidence: 99%

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Urbogeosystemic Approach to Agglomeration Study within the Urban Remote Sensing Frameworks

Kostrikov¹,

Denis²

2022

Sustainable Development Dimensions and Urban Agglomeration

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The spatial arrangement of human activity within urban areas is normally provided by areal management, and its effective provision is a complicated problem. The current urban development causes a number of problems and urgent challenges, which can be met and resolved exclusively on the basis of innovative scientific and technological advances. The main research objective of this chapter is to represent the authors’ theoretic concept of the urban geographical system combined with the original Urban Remote Sensing approach based on the advanced technique of airborne LiDAR (Light Detection And Ranging) data processing. The authors attempted to prove that the presented concept could contribute to an understanding of the urban agglomeration as an urbanized spatial entity. The chapter explains in what way the urbanistic environment is a quasi-rasterized 3D model of actual city space, and the urbogeosystem (UGS) is a quasi-vector 3D model of the hierarchical formalized aggregate of UGS elementary functional units–buildings, both can efficiently simulate and visualize an urbanized area. Web-based geoinformation software for LiDAR data processing with the objectives of urban studies has been introduced together with its key functionalities. The population estimation use case has been examined in detail within the presented approach frameworks.

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Automated Extraction of Heavyweight and Lightweight Models of Urban Features from LiDAR Point Clouds by Specialized Web-Software

Cited by 4 publications

References 82 publications

Spatiotemporal Analysis of Urban Green Areas Using Change Detection: A Case Study of Kharkiv, Ukraine

Spatiotemporal Analysis of Urban Green Areas Using Change Detection: A Case Study of Kharkiv, Ukraine

The performance of the digital city projects in urban studies of the megalopolises (the case studies of Kharkiv and Dnipro cities)

Urbogeosystemic Approach to Agglomeration Study within the Urban Remote Sensing Frameworks

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