Amalgamation in landslide maps
- Inventories of individually delineated landslides are a key to understanding landslide physics and mitigating their impact. They permit assessment of area–frequency distributions and landslide volumes, and testing of statistical correlations between landslides and physical parameters such as topographic gradient or seismic strong motion. Amalgamation, i.e. the mapping of several adjacent landslides as a single polygon, can lead to potentially severe distortion of the statistics of these inventories. This problem can be especially severe in data sets produced by automated mapping. We present five inventories of earthquake-induced landslides mapped with different materials and techniques and affected by varying degrees of amalgamation. Errors on the total landslide volume and power-law exponent of the area–frequency distribution, resulting from amalgamation, may be up to 200 and 50%, respectively. We present an algorithm based on image and digital elevation model (DEM) analysis, for automatic identification of amalgamated polygons. On aInventories of individually delineated landslides are a key to understanding landslide physics and mitigating their impact. They permit assessment of area–frequency distributions and landslide volumes, and testing of statistical correlations between landslides and physical parameters such as topographic gradient or seismic strong motion. Amalgamation, i.e. the mapping of several adjacent landslides as a single polygon, can lead to potentially severe distortion of the statistics of these inventories. This problem can be especially severe in data sets produced by automated mapping. We present five inventories of earthquake-induced landslides mapped with different materials and techniques and affected by varying degrees of amalgamation. Errors on the total landslide volume and power-law exponent of the area–frequency distribution, resulting from amalgamation, may be up to 200 and 50%, respectively. We present an algorithm based on image and digital elevation model (DEM) analysis, for automatic identification of amalgamated polygons. On a set of about 2000 polygons larger than 1000 m2, tracing landslides triggered by the 1994 Northridge earthquake, the algorithm performs well, with only 2.7–3.6% incorrectly amalgamated landslides missed and 3.9–4.8% correct polygons incorrectly identified as amalgams. This algorithm can be used broadly to check landslide inventories and allow faster correction by automating the identification of amalgamation.…
Verfasserangaben: | Odin MarcORCiDGND, Niels HoviusORCiDGND |
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URN: | urn:nbn:de:kobv:517-opus4-408075 |
ISSN: | 1866-8372 |
Titel des übergeordneten Werks (Englisch): | Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe |
Untertitel (Englisch): | effects and automatic detection |
Schriftenreihe (Bandnummer): | Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe (485) |
Publikationstyp: | Postprint |
Sprache: | Englisch |
Datum der Erstveröffentlichung: | 12.12.2018 |
Erscheinungsjahr: | 2015 |
Veröffentlichende Institution: | Universität Potsdam |
Datum der Freischaltung: | 12.12.2018 |
Freies Schlagwort / Tag: | 2008 Wenchuan earthquake; Taiwan; erosion; model; mountain belt; sediment; size distributions |
Ausgabe: | 485 |
Seitenanzahl: | 11 |
Quelle: | Natural Hazards and Earth System Sciences 15 (2015) 4, S. 723–733 DOI: 10.5194/nhess-15-723-2015 |
Organisationseinheiten: | Mathematisch-Naturwissenschaftliche Fakultät |
DDC-Klassifikation: | 9 Geschichte und Geografie / 91 Geografie, Reisen / 910 Geografie, Reisen |
Peer Review: | Referiert |
Publikationsweg: | Open Access |
Fördermittelquelle: | Copernicus |
Lizenz (Deutsch): | CC-BY - Namensnennung 4.0 International |
Externe Anmerkung: | Bibliographieeintrag der Originalveröffentlichung/Quelle |