Evaluation of Coherent and Incoherent Landslide Detection Methods Based on Synthetic Aperture Radar for Rapid Response: A Case Study for the 2018 Hokkaido Landslides

Abstract

Damage mapping using Synthetic Aperture Radar (SAR) imagery has been studied in recent decades to support rapid response to natural disasters. Many researches have been developing coherent and incoherent change detection. However, their performances can vary depending on the types of the damages, the characteristics of the scatterers and the corresponding capability of algorithms. In particular, the coherence-based methods have been used as promising detectors over urban areas where high coherences are observed, but their detection accuracies still remain controversial over the area where low coherences are mainly observed such as the 2018 Hokkaido landslides. In order to understand the characteristics of landslide (damage) detectors for low-coherence areas and find an alternative and complementary method, we designed the coherence difference, coherence normalized difference, log-ratio, intensity correlation difference, and normalized differences of the intensity correlation assuming limited availability of dataset, and also developed multi-temporal algorithms using the coherence, intensity, and intensity correlation. They were tested and evaluated using multiple polygons extracted from aerial photos. We were able to observe that the multi-temporal intensity correlation method has the potential to detect the landslides over the low coherence region and all types of land uses.

Leveraging time series analysis of radar coherence and normalized difference vegetation index ratios to characterize pre-failure activity of the Mud Creek landslide, California

“…where * indicates the complex conjugate (Jung et al, 2016). We created a time series of radar coherence ratio (C R ) by calculating the ratio between the mean coherence over the slide (the area that ultimately failed) and the mean coherence over the surrounding slope (termed reference slope; see Fig.…”

Differential SAR Interferometry Using Sentinel-1 Imagery-Limitations in Monitoring Fast Moving Landslides: The Case Study of Cyprus

“…A comparison of pre-event and co-event coherence maps would need to be conducted to study the coherence loss and differentiate between coherence loss due to the landslides and due to the temporal baseline of SAR images. Coherent Change Detection has been widely used for monitoring land use/land cover changes [62][63][64]; agricultural studies [65][66][67]; forestry applications [68][69][70]; and lately earthquake impact assessment [71][72][73][74]. In fact, the Coherent Change Detection methodology has been applied successfully for the detection of the same landslides, determining accurately the extents of the areas affected by the landslides [75].…”

Small Scale Landslide Detection Using Sentinel-1 Interferometric SAR Coherence

“…The performance of the coherence difference and normalized coherence difference indicators was further tested for the specific case study, by the Receiver Operating Characteristic (ROC) analysis. ROC analysis has been widely used for the benchmarking of natural hazard detection methods [42,59,71]. A map of landslide and non-landslide pixels is created and the trade-off between the true positive fraction and the false positive fraction with certain thresholds are calculated.…”

“…The Coherent Change Detection (CCD) technique has been used in several applications such as monitoring land use / land cover changes [44][45][46][47][48] as well as agricultural studies [49][50][51] and forestry applications [52][53][54][55][56], and, lately, in earthquake impact assessment studies [42,43,[57][58][59]. The CCD technique is less efficient in areas with high human activity, or where the underlying geological formations are too hard to record detectable surface modifications.…”

“…Last but not least, the poor resampling can lead to low coherence during InSAR processing [38,40,41,60]. However, the identification of changes in coherence through Interferometric SAR processing can provide useful information for the rapid detection of natural hazards [59,64,65].…”