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Geosciences 2016, 6(4), 48; doi:10.3390/geosciences6040048

Identifying Spatio-Temporal Landslide Hotspots on North Island, New Zealand, by Analyzing Historical and Recent Aerial Photography

1
Department of Geoinformatics–Z_GIS, University of Salzburg, Schillerstrasse 30, 5020 Salzburg, Austria
2
Landcare Research, Private Bag 11052, Manawatu Mail Centre, Palmerston North 4442, New Zealand
3
Landcare Research, P.O. Box 69040, Lincoln 7640, New Zealand
*
Author to whom correspondence should be addressed.
Academic Editors: Ruiliang Pu and Jesus Martinez-Frias
Received: 30 June 2016 / Revised: 21 October 2016 / Accepted: 27 October 2016 / Published: 2 November 2016
(This article belongs to the Special Issue Mapping and Assessing Natural Disasters Using Geospatial Technologies)
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Abstract

Accurate mapping of landslides and the reliable identification of areas most affected by landslides are essential for advancing the understanding of landslide erosion processes. Remote sensing data provides a valuable source of information on the spatial distribution and location of landslides. In this paper we present an approach for identifying landslide-prone “hotspots” and their spatio-temporal variability by analyzing historical and recent aerial photography from five different dates, ranging from 1944 to 2011, for a study site near the town of Pahiatua, southeastern North Island, New Zealand. Landslide hotspots are identified from the distribution of semi-automatically detected landslides using object-based image analysis (OBIA), and compared to hotspots derived from manually mapped landslides. When comparing the overlapping areas of the semi-automatically and manually mapped landslides the accuracy values of the OBIA results range between 46% and 61% for the producer’s accuracy and between 44% and 77% for the user’s accuracy. When evaluating whether a manually digitized landslide polygon is only intersected to some extent by any semi-automatically mapped landslide, we observe that for the natural-color images the landslide detection rate is 83% for 2011 and 93% for 2005; for the panchromatic images the values are slightly lower (67% for 1997, 74% for 1979, and 72% for 1944). A comparison of the derived landslide hotspot maps shows that the distribution of the manually identified landslides and those mapped with OBIA is very similar for all periods; though the results also reveal that mapping landslide tails generally requires visual interpretation. Information on the spatio-temporal evolution of landslide hotspots can be useful for the development of location-specific, beneficial intervention measures and for assessing landscape dynamics. View Full-Text
Keywords: landslides; object-based image analysis (OBIA); aerial photography; visual interpretation; remote sensing; spatio-temporal hotspot mapping landslides; object-based image analysis (OBIA); aerial photography; visual interpretation; remote sensing; spatio-temporal hotspot mapping
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Hölbling, D.; Betts, H.; Spiekermann, R.; Phillips, C. Identifying Spatio-Temporal Landslide Hotspots on North Island, New Zealand, by Analyzing Historical and Recent Aerial Photography. Geosciences 2016, 6, 48.

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