Please use this identifier to cite or link to this item:
https://doi.org/10.21256/zhaw-30133Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Scherelis, Victoria | - |
| dc.contributor.author | Laube, Patrick | - |
| dc.contributor.author | Doering, Michael | - |
| dc.date.accessioned | 2024-03-09T09:35:22Z | - |
| dc.date.available | 2024-03-09T09:35:22Z | - |
| dc.date.issued | 2023-09-07 | - |
| dc.identifier.other | urn:nbn:de:0030-drops-189604 | de_CH |
| dc.identifier.uri | https://digitalcollection.zhaw.ch/handle/11475/30133 | - |
| dc.description.abstract | Change detection is a well-established process of detaining spatial and temporal changes of entities between two or more timesteps. Current advancements in digital map processing offer vast new sources of multitemporal geodata. As the temporal aspect gains complexity, the dismantling of detected changes on a pixel-based scale becomes a costly undertaking. In efforts to establish and preserve the evolution of detected changes in long time series, this paper presents a method that allows the decomposition of pixel evolution vectors into three dimensions of change, described as directed change, change variability, and change magnitude. The three dimensions of change compile to complex change analytics per individual pixels and offer a multi-faceted analysis of landscape changes on an ordinal scale. Finally, the integration of class confidence from learned uncertainty estimates illustrates the avenue to include uncertainty into the here presented change analytics, and the three dimensions of change are visualized in complex change maps. | de_CH |
| dc.language.iso | en | de_CH |
| dc.publisher | Schloss Dagstuhl - Leibniz-Zentrum für Informatik | de_CH |
| dc.relation.ispartofseries | Leibniz International Proceedings in Informatics (LIPIcs) | de_CH |
| dc.rights | http://creativecommons.org/licenses/by/4.0/ | de_CH |
| dc.subject | Digital map processing | de_CH |
| dc.subject | Spatio-temporal modelling | de_CH |
| dc.subject | Land-use change | de_CH |
| dc.subject.ddc | 551: Geologie und Hydrologie | de_CH |
| dc.subject.ddc | 577: Ökologie | de_CH |
| dc.title | From change detection to change analytics : decomposing multi-temporal pixel evolution vectors | de_CH |
| dc.type | Konferenz: Paper | de_CH |
| dcterms.type | Text | de_CH |
| zhaw.departement | Life Sciences und Facility Management | de_CH |
| zhaw.organisationalunit | Institut für Umwelt und Natürliche Ressourcen (IUNR) | de_CH |
| dc.identifier.doi | 10.4230/LIPIcs.GIScience.2023.65 | de_CH |
| dc.identifier.doi | 10.21256/zhaw-30133 | - |
| zhaw.conference.details | 12th International Conference on Geographic Information Science (GIScience), Leeds, United Kingdom, 12-15 September 2023 | de_CH |
| zhaw.funding.eu | No | de_CH |
| zhaw.originated.zhaw | Yes | de_CH |
| zhaw.pages.end | 65:6 | de_CH |
| zhaw.pages.start | 65:1 | de_CH |
| zhaw.publication.status | publishedVersion | de_CH |
| zhaw.series.number | 277 | de_CH |
| zhaw.publication.review | Peer review (Publikation) | de_CH |
| zhaw.title.proceedings | 12th International Conference on Geographic Information Science (GIScience 2023) | de_CH |
| zhaw.funding.snf | 188692 | de_CH |
| zhaw.webfeed | Geoinformatik | de_CH |
| zhaw.webfeed | Ökohydrologie | de_CH |
| zhaw.funding.zhaw | HistoRiCH: Historical river change – Planning for the future by exploring the mapped past | de_CH |
| zhaw.author.additional | No | de_CH |
| zhaw.display.portrait | Yes | de_CH |
| Appears in collections: | Publikationen Life Sciences und Facility Management | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2023_Scherelis-etal_From-change-detection-to-change-analytics.pdf | 18.78 MB | Adobe PDF |  View/Open |
Show simple item record
Scherelis, V., Laube, P., & Doering, M. (2023). From change detection to change analytics : decomposing multi-temporal pixel evolution vectors [Conference paper]. 12th International Conference on Geographic Information Science (GIScience 2023), 65:1–65:6. https://doi.org/10.4230/LIPIcs.GIScience.2023.65
Scherelis, V., Laube, P. and Doering, M. (2023) ‘From change detection to change analytics : decomposing multi-temporal pixel evolution vectors’, in 12th International Conference on Geographic Information Science (GIScience 2023). Schloss Dagstuhl - Leibniz-Zentrum für Informatik, pp. 65:1–65:6. Available at: https://doi.org/10.4230/LIPIcs.GIScience.2023.65.
V. Scherelis, P. Laube, and M. Doering, “From change detection to change analytics : decomposing multi-temporal pixel evolution vectors,” in 12th International Conference on Geographic Information Science (GIScience 2023), Sep. 2023, pp. 65:1–65:6. doi: 10.4230/LIPIcs.GIScience.2023.65.
SCHERELIS, Victoria, Patrick LAUBE und Michael DOERING, 2023. From change detection to change analytics : decomposing multi-temporal pixel evolution vectors. In: 12th International Conference on Geographic Information Science (GIScience 2023). Conference paper. Schloss Dagstuhl - Leibniz-Zentrum für Informatik. 7 September 2023. S. 65:1–65:6
Scherelis, Victoria, Patrick Laube, and Michael Doering. 2023. “From Change Detection to Change Analytics : Decomposing Multi-Temporal Pixel Evolution Vectors.” Conference paper. In 12th International Conference on Geographic Information Science (GIScience 2023), 65:1–65:6. Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.GIScience.2023.65.
Scherelis, Victoria, et al. “From Change Detection to Change Analytics : Decomposing Multi-Temporal Pixel Evolution Vectors.” 12th International Conference on Geographic Information Science (GIScience 2023), Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023, pp. 65:1–:6, https://doi.org/10.4230/LIPIcs.GIScience.2023.65.
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