Automated Spatiotemporal Landslide Mapping over Large Areas Using RapidEye Time Series Data

Robert Behling,Hermann Kaufmann,Birgit Kleinschmit,Sigrid Roessner

doi:10.3390/rs6098026

Abstract

In the past, different approaches for automated landslide identification based on multispectral satellite remote sensing were developed to focus on the analysis of the spatial distribution of landslide occurrences related to distinct triggering events. However, many regions, including southern Kyrgyzstan, experience ongoing process activity requiring continual multi-temporal analysis. For this purpose, an automated object-oriented landslide mapping approach has been developed based on RapidEye time series data complemented by relief information. The approach builds on analyzing temporal NDVI-trajectories for the separation between landslide-related surface changes and other land cover changes. To accommodate the variety of landslide phenomena occurring in the 7500 km2 study area, a combination of pixel-based multiple thresholds and object-oriented analysis has been implemented including the discrimination of uncertainty-related landslide likelihood classes. Applying the approach to the whole study area for the time period between 2009 and 2013 has resulted in the multi-temporal identification of 471 landslide objects. A quantitative accuracy assessment for two independent validation sites has revealed overall high mapping accuracy (Quality Percentage: 80%), proving the suitability of the developed approach for efficient spatiotemporal landslide mapping over large areas, representing an important prerequisite for objective landslide hazard and risk assessment at the regional scale.

Highlights

Landslides are a major natural hazard causing serious damage to buildings and technical infrastructure, as well as severe loss of life in many mountainous regions worldwide [1,2,3]
Spatially explicit representations of the true positive (TP), false negative (FN) and false positive (FP) areas have been obtained for each object comparison (Figure 14)
The ideal spatial overlap between two objects is represented by 100% TP and 0% false positives (FP) indicated by the star in the diagram of Figure 14 depicting the individual objects regarding their percentages of TP and FP

Summary

Introduction

Landslides are a major natural hazard causing serious damage to buildings and technical infrastructure, as well as severe loss of life in many mountainous regions worldwide [1,2,3] Against this background, landslide hazard and risk assessment is of great importance requiring the assessment of past process activity in the form of landslide inventories containing spatiotemporal information about occurrence and characteristics of landslides [4,5,6,7,8]. Landslide hazard and risk assessment is of great importance requiring the assessment of past process activity in the form of landslide inventories containing spatiotemporal information about occurrence and characteristics of landslides [4,5,6,7,8] Since such inventories have to be as complete and precise as possible in time and space, multi-temporal inventories are needed, especially in regions of frequently occurring landslides [6]. For the purpose of post-failure mapping, mainly optical remote sensing data have been used, as most of the landslide processes lead to disturbance of the Earth’s surface resulting in significant changes in the reflectance characteristics of these surfaces [6,13,14,15]

Objectives

Results

Discussion

Conclusion