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.
Highlights
Landslide erosion is a serious land management problem in many parts of the world, and especially in New Zealand where a combination of steep erodible hill country, a maritime climate featuring frequent and intense rainstorms, and recent forest clearance for pastoral farming have led to extensive landslide erosion on many parts of the country’s hill country farmland
A comparison of the derived landslide hotspot maps shows that the distribution of the manually identified landslides and those mapped with object-based image analysis (OBIA) is very similar for all periods; though the results reveal that mapping landslide tails generally requires visual interpretation
Visual mapping identified a total of 2703 landslide scars and 2343 landslide tails over the five layer was mostly used, since landslides usually appear brighter than their immediate surroundings on optical images due to the exposure of bare ground [4,33,40]
Summary
Landslide erosion is a serious land management problem in many parts of the world, and especially in New Zealand where a combination of steep erodible hill country, a maritime climate featuring frequent and intense rainstorms, and recent forest clearance for pastoral farming have led to extensive landslide erosion on many parts of the country’s hill country farmland. In New Zealand, this usually relies on detailed manual mapping from aerial photography [1] and, more recently, spectral classification of regional satellite. For catchment- to farm-scale applications, manual image interpretation and mapping has to date been the most-used method for accurately identifying and mapping landsliding, but it is a very slow and tedious process and is limited to studies of relatively small areas and can be difficult to implement in practice. The quality of the resulting landslide maps depends on the experience of the investigator, the purpose of the mapping, the scale, and the data used [3,4,5,6].
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