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Scientific paper - Chapter in Book
Landslide Detection and Spatial Prediction: Application of Data and Information from Landslide Maps
In: Progress in Landslide Research and Technology, Volume 1, Issue 2 / Alcántara-Ayala, Irasema; Arbanas, Željko (Ed.). Cham: Springer Science and Business Media LLC, 2023. pp. 195-212. https://doi.org/10.1007/978-3-031-18471-0_16
Mihalić Arbanas, Snježana; Bernat Gazibara, Sanja; Krkač, Martin; Sinčić, Marko; Lukačić, Hrvoje; Jagodnik, Petra; Arbanas, Željko

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Mihalić Arbanas, S., Bernat Gazibara, S., Krkač, M., Sinčić, M., Lukačić, H., Jagodnik, P. & Arbanas, Ž. (2023). Landslide Detection and Spatial Prediction: Application of Data and Information from Landslide Maps. In I. Alcántara Ayala, (Ed.), Ž. Arbanas, (Ed.), Progress in Landslide Research and Technology, Volume 1, Issue 2 (pp. 195-212). Cham: Springer Science and Business Media LLC. doi: 10.1007/978-3-031-18471-0_16

Mihalić Arbanas, Snježana, et al. "Landslide Detection and Spatial Prediction: Application of Data and Information from Landslide Maps." Progress in Landslide Research and Technology, Volume 1, Issue 2, edited by Irasema Alcántara Ayala, edited by Željko Arbanas, Springer Science and Business Media LLC, 2023, pp. 195-212. https://urn.nsk.hr/urn:nbn:hr:169:327253

Mihalić Arbanas, Snježana, Sanja Bernat Gazibara, Martin Krkač, Marko Sinčić, Hrvoje Lukačić, Petra Jagodnik and Željko Arbanas. "Landslide Detection and Spatial Prediction: Application of Data and Information from Landslide Maps." In Progress in Landslide Research and Technology, Volume 1, Issue 2, edited by Irasema Alcántara Ayala, edited by Željko Arbanas, 195-212. Cham: Springer Science and Business Media LLC, 2023. https://urn.nsk.hr/urn:nbn:hr:169:327253

Mihalić Arbanas, S., et al. (2023) 'Landslide Detection and Spatial Prediction: Application of Data and Information from Landslide Maps' in Alcántara Ayala, I. (ed.), Arbanas, Ž. (ed.) Progress in Landslide Research and Technology, Volume 1, Issue 2 Cham: Springer Science and Business Media LLC, pp. 195-212. Available at: https://urn.nsk.hr/urn:nbn:hr:169:327253 (Accessed 18 April 2024)

Mihalić Arbanas S, Bernat Gazibara S, Krkač M, Sinčić M, Lukačić H, Jagodnik P, and sur.. Landslide Detection and Spatial Prediction: Application of Data and Information from Landslide Maps. In: I. Alcántara Ayala, ed., Ž. Arbanas, ed. Progress in Landslide Research and Technology, Volume 1, Issue 2. Cham: Springer Science and Business Media LLC; 2023. Pp. 195-212. [cited 2024 April 18] Available at: https://urn.nsk.hr/urn:nbn:hr:169:327253

S. Mihalić Arbanas, et al., "Landslide Detection and Spatial Prediction: Application of Data and Information from Landslide Maps", Progress in Landslide Research and Technology, Volume 1, Issue 2, I. Alcántara Ayala and Ž. Arbanas, Eds. Cham: Springer Science and Business Media LLC, 2023, pp. 195-212. [Online] Available at: https://urn.nsk.hr/urn:nbn:hr:169:327253

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Metadata
Title (english)Landslide Detection and Spatial Prediction: Application of Data and Information from Landslide Maps
AuthorSnježana Mihalić Arbanas
AuthorSanja Bernat Gazibara
AuthorMartin Krkač
AuthorMarko Sinčić
AuthorHrvoje Lukačić
AuthorPetra Jagodnik
AuthorŽeljko Arbanas
EditorIrasema Alcántara-Ayala
EditorŽeljko Arbanas
Author's institutionUniversity of Rijeka
Faculty of Civil Engineering
Author's institutionUniversity of Zagreb
Faculty of Mining, Geology and Petroleum Engineering
(Department of Geology and Geological Engineering)
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Mining, Petroleum and Geology Engineering
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Geology
Abstract (english)
Abstract The need for landslide maps of wider areas has increased with the understanding that proper planning will considerably decrease the construction and maintenance cost of structures. The main objective of the paper is to present types of data and information on landslides that can be derived from landslide inventory and landslide susceptibility maps and their use for spatial and urban planning. Recent examples of landslide zonation maps from Croatia are given to show the possibility of the derivation of data about landslides by using LIDAR (Light Detection and Ranging) DTM (Digital Terrain Model) for the compilation of historical landslide inventory. The application of data about landslide phenomena is compared with the application of information from landslide susceptibility zonation maps. It is concluded that a multi-level and hierarchical approach is necessary to reach the cost-effectiveness of nationwide production of landside maps for land-use planning.
Keywords (english)
Languageenglish
Publication typeScientific paper - Chapter in Book
Publication statusPublished
Peer reviewPeer review - international
Publication versionPublished version
Book titleProgress in Landslide Research and Technology, Volume 1, Issue 2
Series titleProgress in Landslide Research and Technology (PLRT)
Numberingpp. 195-212
ISBN978-3-031-18470-3 (Hardcover)
ISBN978-3-031-18471-0 (eBook)
ISBN978-3-031-18473-4 (Softcover)
p-ISSN2731-3808
DOIhttps://doi.org/10.1007/978-3-031-18471-0_16
URN:NBNurn:nbn:hr:169:327253
Publication2023
ProjectNumber: IP-2019-04-9900
Title (croatian): Razvoj metodologije procjene podložnosti na klizanje za planiranje namjene zemljišta primjenom LiDAR tehnologije
Title (english): Methodology development for landslide susceptibility assessment for land-use planning based on LiDAR technology
Acronym: LandSlidePlan
Leader: Snježana Mihalić Arbanas
Jurisdiction: Croatia
Funding stream: IP
ProjectNumber: KK.05.1.1.02.0020
Title (croatian): Primijenjena istraživanja klizišta za razvoj mjera ublažavanja i prevencije rizika PRI-MJER
Acronym: PRI-MJER
Leader: Snježana Mihalić Arbanas
Jurisdiction: Croatia
Funding stream: EFRR
Document URLhttps://link.springer.com/10.1007/978-3-031-18471-0_16
Type of resourceText
PublisherSpringer Science and Business Media LLC
Publishing placeCham
Access conditionsOpen access
Terms of useLicence Attribution 4.0 International (CC BY 4.0) icon
Created on2024-02-09 09:37:41