Features of inventory of green plantings by automated terrestrial laser scanning methods

dc.citation.epage31
dc.citation.issue98
dc.citation.journalTitleГеодезія, картографія і аерофотознімання
dc.citation.spage24
dc.contributor.affiliationНаціональний університет “Львівська політехніка”
dc.contributor.affiliationLviv Polytechnic National University
dc.contributor.authorВаш, Ярослав
dc.contributor.authorVash, Yaroslav
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.date.accessioned2025-03-17T09:36:13Z
dc.date.created2023-02-28
dc.date.issued2023-02-28
dc.description.abstractМета цієї роботи – дослідження процесу отримання необхідної інформації про метричні показники невеликих за площею масивів, лінійно розташованих та поодиноких зелених насаджень на переважно урбанізованих територіях та застосування результатів опрацювання даних при складанні топографічних та спеціальних карт з відповідних матеріалів сканування території. Методика. З цією метою дослідженню підлягають методи наземного лазерного сканування, динамічного лазерного сканування як джерело даних для подеревної зйомки території та як інформаційна база для наповнення відповідних кадастрів. Досліджено можливості використання даних методів для отримання інформації про зелені насадження з використанням сучасних програмних засобів. На основі даних наземного лазерного сканування, виконаного відповідно до вимог нормативних документів з геопросторовою прив’язкою, проведено опрацювання даних наземного лазерного сканування з використанням автоматизованих методів а саме програмного комплексу Terrasolid. Підтверджено необхідність наявності більше 40% покриття стовбура дерева хмарою точок, отриманою з лазерного сканування для усунення можливих помилок при визначенні відповідних показників у зв’язку з неоднорідністю будови різних стовбурів дерев. Попереднє опрацювання матеріалів сканування виконано за допомогою програмного забезпечення FARO Scene 2020. Наукова новизна та практична значущість. Проведено експериментальний аналіз створення планово-висотної основи та інформаційної бази про зелені насадження на обраних об’єктах на території Закарпатської області. Удосконалено технологію отримання даних про зелені насадження, без використання класичних методів топографо-геодезичних робіт, із застосуванням наземного лазерного сканування та частково GNSS вимірювань. В результаті на території досліджуваних об’єктів автоматизованими методами створено таблицю даних зелених насаджень з інформацією про їх розташування у прийнятій системі координат та діаметром стовбура на висоті 1.3 метра.
dc.description.abstractThe aim of this work is to investigate the process of obtaining necessary information about the metric parameters of small-area arrays, linearly arranged and individual green plantings on predominantly urbanized territories, and to apply the results of data processing in the compilation of topographic and special maps from the corresponding scanning materials. Methodology. For this purpose, terrestrial laser scanning methods, dynamic laser scanning as a data source for tree-level mapping of the territory, and as an information base for filling in the respective cadastres are subject to research. The possibilities of using data from these methods to obtain information about green plantings using modern software tools have been explored. Based on terrestrial laser scanning data performed in accordance with the requirements of regulatory spatial reference documents, data processing of terrestrial laser scanning was carried out using automated methods, namely the Terrasolid software suite. The need for more than 40% coverage of the tree trunk with a point cloud obtained from laser scanning to eliminate possible errors in determining the relevant parameters due to the heterogeneity of the structure of different tree trunks has been confirmed. Preliminary processing of scanning materials was carried out using FARO Scene 2020 software. Scientific novelty and practical significance. An experiment was conducted to analyze the creation of both a plan-altitude and an information base regarding green plantings on selected objects within the Zakarpattia region. The process of collecting data on green plantings was improved by using terrestrial laser scanning and partial GNSS measurements, instead of traditional topographic-geodetic methods. A table containing information on green planting data has been created for the studied objects' territory. Automated methods were used to gather this information, including details about their location in the adopted coordinate system and the trunk diameter at a height of 1.3 meters.
dc.format.extent24-31
dc.format.pages8
dc.identifier.citationVash Y. Features of inventory of green plantings by automated terrestrial laser scanning methods / Vash Yaroslav // Geodesy, cartography and aerial photography. — Lviv : Lviv Politechnic Publishing House, 2023. — No 98. — P. 24–31.
dc.identifier.citationenVash Y. Features of inventory of green plantings by automated terrestrial laser scanning methods / Vash Yaroslav // Geodesy, cartography and aerial photography. — Lviv : Lviv Politechnic Publishing House, 2023. — No 98. — P. 24–31.
dc.identifier.doidoi.org/10.23939/istcgcap2023.98.024
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/64174
dc.language.isoen
dc.publisherВидавництво Львівської політехніки
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofГеодезія, картографія і аерофотознімання, 98, 2023
dc.relation.ispartofGeodesy, cartography and aerial photography, 98, 2023
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dc.relation.referencesRitter, T., Schwarz, M., Tockner, A., Leisch, F., & Nothdurft, A. (2017). Automatic mapping of forest stands based on three-dimensional point clouds derived from terrestrial laser-scanning. Forests, 8(8), 265. https://doi.org/10.3390/f8080265
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dc.relation.referencesWang, Y., Pyörälä, J., Liang, X., Lehtomäki, M., Kukko, A., Yu, X., ... & Hyyppä, J. (2019). In situ biomass estimation at tree and plot levels: What did data record and what did algorithms derive from terrestrial and aerial point clouds in boreal forest. Remote Sensing of Environment, 232, 111309. https://doi.org/10.1016/j.rse.2019.111309
dc.relation.referencesWilkes, P., Disney, M., Armston, J., Bartholomeus, H., Bentley, L., Brede, B., ... & Yang, W. (2022). TLS2trees: A scalable tree segmentation pipeline for TLS data. Methods in Ecology and Evolution. https://doi.org/10.1101/2022.12.07.518693
dc.relation.referencesWitzmann, S., Matitz, L., Gollob, C., Ritter, T., Kraßnitzer, R., Tockner, A., ... & Nothdurft, A. (2022). Accuracy and precision of stem cross-section modeling in 3D point clouds from TLS and caliper measurements for basal area estimation. Remote Sensing, 14(8), 1923. https://doi.org/10.3390/rs14081923
dc.relation.referencesYalova, К. (2019). Conceptual propositions of the city’s green plantations monitoring automation. Computerintegrated technologies: education, science, production, (35), 112–116 (in Ukrainian). http://cit-journal.com.ua/index.php/cit/article/view/84
dc.relation.referencesenAbegg, M., Kükenbrink, D., Zell, J., Schaepman, M. E., & Morsdorf, F. (2017). Terrestrial laser scanning for forest inventories – tree diameter distribution and scanner location impact on occlusion. Forests, 8(6), 184, 137–179. https://doi.org/10.3390/f8060184
dc.relation.referencesenFol C. R., Kükenbrink D., Rehush N., Murtiyoso A., Griess V. C. (2023). Evaluating state-of-the-art 3D scaning methods for stem-level biodiversity inventories in forests. International Journal of Applied Earth Observation and Geoinformation, 122, 103396. https://doi.org/10.1016/j.jag.2023.103396
dc.relation.referencesenGollob, C., Ritter, T., Kraßnitzer, R., Tockner, A., & Nothdurft, A. (2021). Measurement of forest inventory parameters with Apple iPad pro and integrated LiDAR technology. Remote Sensing, 13(16), 3129. https://doi.org/10.3390/rs13163129
dc.relation.referencesenKalvoda P., Nosek J, Kuruc M., Volarik T. and Kalvodova P. (2020) Accuracy Evaluation and Comparison of Mobile Laser Scanning and Mobile Photogrammetry Data. 2020. IOP Conference Series: Earth and Environmental Science, Vol. 609. https://doi.org/ 10.1088/1755-1315/609/1/012091
dc.relation.referencesenKuželka K., Surový P. (2021) Mathematically optimized trajectory for terrestrial close-range photogrammetric 3D reconstruction of forest stands. ISPRS Journal of Photogrammetry and Remote Sensing, 178, 259–281. https://doi.org/10.1016/j.isprsjprs.2021.06.013
dc.relation.referencesenLi J., Yang B., Yang Y., Zhao X., Liao Y., Zhu N., Dai W., Liu R., Chen R., Dong Z. (2023). Real-time automated forest field inventory using a compact low-cost helmetbased laser scanning system. Int. J. Appl. Earth Obs. Geoinf., 118, 103299. https://doi.org/10.1016/j.jag.2023.103299
dc.relation.referencesenLiang, X., Hyyppä, J., Kaartinen, H., Lehtomäki, M., Pyörälä, J., Pfeifer, N., ... & Wang, Y. (2018). International benchmarking of terrestrial laser scanning approaches for forest inventories. ISPRS journal of photogrammetry and remote sensing, 144, 137–179. https://doi.org/10.1016/j.isprsjprs.2018.06.021
dc.relation.referencesenLiang, X., Kankare, V., Hyyppä, J., Wang, Y., Kukko, A., Haggrén, H., ... & Vastaranta, M. (2016). Terrestrial laser scanning in forest inventories. ISPRS Journal of Photogrammetry and Remote Sensing, 115, 63–77.
dc.relation.referencesenMaas, H. G., Bienert, A., Scheller, S., & Keane, E. (2008). Automatic forest inventory parameter determination from terrestrial laser scanner data. International journal of remote sensing, 29(5), 1579–1593.
dc.relation.referencesenRitter, T., Schwarz, M., Tockner, A., Leisch, F., & Nothdurft, A. (2017). Automatic mapping of forest stands based on three-dimensional point clouds derived from terrestrial laser-scanning. Forests, 8(8), 265. https://doi.org/10.3390/f8080265
dc.relation.referencesenRogovskyi, S. V., Zhikhareva, K. V., Oleshko, O. G., Strutynska, Yu. V., & Kolotnytska, A. V. (2021). Modern problems of plant inventory in urban plantations and experience in solving them. Scientific Bulletin of the National Forestry University of Ukraine (in Ukrainian) https://rep.btsau.edu.ua/handle/BNAU/7163
dc.relation.referencesenSemko, I. D. (2015). The method of determining the aboveground phytomass of a Scots pine stand based on the materials of aerial lidar surveying (in Ukrainian). https://www.casre.kiev.ua/images/files/paper-semko.pdf
dc.relation.referencesenSerrano, F. L., Rubio, E., Morote, F. G., Abellán, M. A., Córdoba, M. P., Saucedo, F. G., ... & González, J. G. (2022). Artificial intelligence-based software (AIDFOREST) for tree detection: A new framework for fast and accurate forest inventorying using LiDAR point clouds. International Journal of Applied Earth Observation and Geoinformation, 113, 103014. 113.2022. https://doi.org/10.1016/j.jag.2022.103014.
dc.relation.referencesenStoli, S., & Rex, D. (2014). Applications of 3D Laser Scanning in a Production Environment.
dc.relation.referencesenStrzeliński P., Jagodziński A. M., Wencel A., Zawiła Niedźwiecki T. (2008). Szacowanie zasobów węgla w lasach z wykorzystaniem technik geomatycznych. Techniki geomatyczne w inwentaryzacji lasu – potrzeby i możliwości. Warszawa: Wyd. SGGW, 114–125.
dc.relation.referencesenTerraScan User Guide. URL: https://www.terrasolid.com/guides/tscan/crtrees.html
dc.relation.referencesenTockner, A., Gollob, C., Kraßnitzer, R., Ritter, T., & Nothdurft, A. (2022). Automatic tree crown segmentation using dense forest point clouds from Personal
dc.relation.referencesenLaser Scanning (PLS). International Journal of Applied Earth Observation and Geoinformation, 114, 103025. https://doi.org/10.1016/j.jag.2022.103025
dc.relation.referencesenTrochta, J., Krůček, M., Vrška, T., & Král, K. (2017). 3D Forest: An application for descriptions of threedimensional forest structures using terrestrial LiDAR. PloS one, 12(5), e0176871. https://doi.org/10.1371/journal.pone.0176871
dc.relation.referencesenVash, Y., Hubar, Yu. (2022). The method of optimizing measurements with a ground laser scanner of the green plants of T. Masarik park in Uzhgorod. In International Conference of Young Professionals, GeoTerrace 2022, 1, 1–5. European Association of Geoscientists & Engineers. https://doi.org/10.3997/2214-4609.2022590048
dc.relation.referencesenVash, Y., Gubar, Yu, Kalynych, I. & Chetverikov, B. (2022). Inventory of horticultural facilities of T. Masaryk Square in Uzhgorod with the use of TLS (in Ukrainian). https://doi.org/10.33841/1819-1339-2-44-121-129
dc.relation.referencesenVerkhovna Rada of Ukraine (1998). On the approval of the Instructions for topographical surveying at scales of 1: 5000, 1: 2000, 1: 1000 and 1: 500 (DSTU 2.04-02-98).
dc.relation.referencesenUkrgeodeskartography; Order No. 56 of April 9 (in Ukrainian). https://zakon.rada.gov.ua/laws/show/z0393-98
dc.relation.referencesenVerkhovna Rada of Ukraine (2001). On the approval of the Instructions for the inventory of green spaces in populated areas of Ukraine State Committee for Construction, Architecture and Housing Policy of Ukraine Order of December 24, No. 226 (in Ukrainian). https://zakon.rada.gov.ua/laws/show/z0182-02#Text
dc.relation.referencesenVerkhovna Rada of Ukraine (2011). Cabinet of Ministers of Ukraine Decree No. 559 of May 25 on the urban planning cadastre (in Ukrainian). https://zakon.rada.gov.ua/laws/show/559-2011-%D0%BF#Text
dc.relation.referencesenWang, Y., Pyörälä, J., Liang, X., Lehtomäki, M., Kukko, A., Yu, X., ... & Hyyppä, J. (2019). In situ biomass estimation at tree and plot levels: What did data record and what did algorithms derive from terrestrial and aerial point clouds in boreal forest. Remote Sensing of Environment, 232, 111309. https://doi.org/10.1016/j.rse.2019.111309
dc.relation.referencesenWilkes, P., Disney, M., Armston, J., Bartholomeus, H., Bentley, L., Brede, B., ... & Yang, W. (2022). TLS2trees: A scalable tree segmentation pipeline for TLS data. Methods in Ecology and Evolution. https://doi.org/10.1101/2022.12.07.518693
dc.relation.referencesenWitzmann, S., Matitz, L., Gollob, C., Ritter, T., Kraßnitzer, R., Tockner, A., ... & Nothdurft, A. (2022). Accuracy and precision of stem cross-section modeling in 3D point clouds from TLS and caliper measurements for basal area estimation. Remote Sensing, 14(8), 1923. https://doi.org/10.3390/rs14081923
dc.relation.referencesenYalova, K. (2019). Conceptual propositions of the city’s green plantations monitoring automation. Computerintegrated technologies: education, science, production, (35), 112–116 (in Ukrainian). http://cit-journal.com.ua/index.php/cit/article/view/84
dc.relation.urihttps://doi.org/10.3390/f8060184
dc.relation.urihttps://doi.org/10.1016/j.jag.2023.103396
dc.relation.urihttps://doi.org/10.3390/rs13163129
dc.relation.urihttps://doi.org/
dc.relation.urihttps://doi.org/10.1016/j.isprsjprs.2021.06.013
dc.relation.urihttps://doi.org/10.1016/j.jag.2023.103299
dc.relation.urihttps://doi.org/10.1016/j.isprsjprs.2018.06.021
dc.relation.urihttps://doi.org/10.3390/f8080265
dc.relation.urihttps://rep.btsau.edu.ua/handle/BNAU/7163
dc.relation.urihttps://www.casre.kiev.ua/images/files/paper-semko.pdf
dc.relation.urihttps://doi.org/10.1016/j.jag.2022.103014
dc.relation.urihttps://www.terrasolid.com/guides/tscan/crtrees.html
dc.relation.urihttps://doi.org/10.1016/j.jag.2022.103025
dc.relation.urihttps://doi.org/10.1371/journal.pone.0176871
dc.relation.urihttps://doi.org/10.3997/2214-4609.2022590048
dc.relation.urihttps://doi.org/10.33841/1819-1339-2-44-121-129
dc.relation.urihttps://zakon.rada.gov.ua/laws/show/z0393-98
dc.relation.urihttps://zakon.rada.gov.ua/laws/show/z0182-02#Text
dc.relation.urihttps://zakon.rada.gov.ua/laws/show/559-2011-%D0%BF#Text
dc.relation.urihttps://doi.org/10.1016/j.rse.2019.111309
dc.relation.urihttps://doi.org/10.1101/2022.12.07.518693
dc.relation.urihttps://doi.org/10.3390/rs14081923
dc.relation.urihttp://cit-journal.com.ua/index.php/cit/article/view/84
dc.rights.holder© Національний університет “Львівська політехніка”, 2023
dc.subjectназемне лазерне сканування
dc.subjectавтоматизовані методи
dc.subjectстовбур дерева
dc.subjectдіаметр
dc.subjectцифрові моделі поверхні
dc.subjectінвентаризація зелених насаджень
dc.subjectterrestrial laser scanning
dc.subjectautomated methods
dc.subjecttree trunk
dc.subjectdiameter
dc.subjectdigital surface models
dc.subjectinventory of green plantings
dc.subject.udc528.18
dc.subject.udc629.783
dc.titleFeatures of inventory of green plantings by automated terrestrial laser scanning methods
dc.title.alternativeОсобливості інвентаризації зелених насаджень автоматизованими методами наземного лазерного сканування
dc.typeArticle

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