# Wide-Area Landslide Deformation Mapping with Multi-Path ALOS PALSAR Data Stacks: A Case Study of Three Gorges Area, China

^{1}

^{2}

^{3}

^{*}

## Abstract

**:**

^{2}were identified to be landslides in active deformation and should be kept under routine surveillance. Analyses of time series displacement measurements revealed that most landslides in the mountainous area far away from Yangtze River suffered from linear deformation, whereas landslides located on the river bank were destabilized predominantly by the influences of reservoir water level fluctuation and rainfall.

## 1. Introduction

## 2. Study Area and Test Datasets

#### 2.1. Three Gorges Area

**Figure 1.**Geographic coverage of the Three Gorges area, with red rectangles indicating our test areas.

**Figure 2.**Water levels of upstream Yangtze River and weekly cumulative rainfall in Fengjie from 2007 to 2011.

#### 2.2. Datasets

**Figure 3.**Interferograms used for small baselines analysis (

**a**) path 462, (

**b**) path 463 and (

**c**) path 464. The circles represent the images and solid lines represent the interferograms.

## 3. Methodology

#### 3.1. Small Baselines Subset InSAR Analysis

_{d}, φ

_{T}, φ

_{a}, φ

_{o}and φ

_{n}are the phase components due, respectively, to surface displacements, topographic error, atmospheric disturbance, inaccurate orbit information and noise. In the StaMPS SBAS analysis, these different components were estimated by iterative filtering with consideration of their identifying characteristics in spatial-temporal domains.

_{i}(i= 0, 1,..., 5) are the coefficients used in orbital error phase estimation; x and y are the coordinates in azimuth and range direction on a SDFP pixel. Then phase ramps were estimated over all interferograms using the SDFP pixels. Typically, the deformation signal will leak into the orbital errors when there are displacements distributed in large areas, as in the case of earthquakes. If this occurs, these areas with displacements should be masked out before performing orbital error estimation.

_{s}, φ

_{a_r}represent the phase delays introduced by the stratified APS and residual, respectively; b is the coefficient used to represent the relationship between elevation and phase delays caused by stratified APS; and h is the elevation. A hybrid description model of the atmospheric phase screen (APS) was incorporated into StaMPS SBAS analysis to improve APS estimation from time series interferograms. The phase delays introduced by stratified APS were estimated by a least squares procedure using all the unwrapped SDFP pixels. Then the atmospheric phase residuals were estimated with temporally high-pass and spatially low-pass filters. Afterwards, time series deformation can be inverted using singular value decomposition (SVD) [7,8].

#### 3.2. Integration of Multi-Path Displacement Measurements

## 4. Experimental Results and Analyses

#### 4.1. Mean Displacement Rate Map

^{2}from Fengjie County to Zigui County along the Yangtze River. Approximately 96% of the points show displacements rates between −10 mm/year and 10 mm/year, which indicated the overall stability of the study area. About 30 slopes with total areas of 48 km

^{2}were identified as being in active deformation.

**Figure 4.**Mean displacement rate map of Three Gorges area generated from three ALOS PALSAR data stacks. Three selected areas are highlighted by dashed rectangles.

**Figure 5.**Mean displacement rate map measured at Fengjie. P1, P2, P3, P4 are points used for time series analysis shown in later sections.

**Figure 7.**Mean displacement rate map covering areas around Badong and Zigui. P5 and P6 are points used in time series analysis shown in later sections.

#### 4.2. Measurement Consistency Evaluation

**Figure 8.**The distribution of displacement rate difference for the overlapping areas between (

**a**) path 464 and path 463 datasets; (

**b**) path 463 and path 462 datasets.

**Figure 9.**Time series displacement of point P5 along the slope direction located at the Huangtupo landslide.

#### 4.3. Effect of Seasonal Rainfall on APS Variation

**Figure 10.**(

**a**) Estimated atmospheric signal on P1 and impact factors: water level (unit: m) and rainfall (unit: mm), the dashed line represents the temporal location of the master image. (

**b**) Time series displacements on P1 with and without stratified APS correction.

#### 4.4. Impact Factors for Landslide Activities

**Figure 11.**Relationship between impact factors and displacements on (

**a**) P2; (

**b**) P3; (

**c**) P4; (

**d**) P6. The measurement units are meter for water level and millimeter for rainfall separately.

## 5. Conclusions

^{2}in total were identified to be active with slopes ranging from 15 to 30 degrees. Through time series analysis, active landslides far away from the Yangtze River exhibit a linear displacement trend. Rainfall plays a key role in the change of the displacement trend. For those active landslides located near the river, rapid water level decline and consecutive rainfall are potentially two key factors to increase slope instability.

## Acknowledgments

## Author Contributions

## Conflicts of Interest

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**MDPI and ACS Style**

Shi, X.; Liao, M.; Li, M.; Zhang, L.; Cunningham, C. Wide-Area Landslide Deformation Mapping with Multi-Path ALOS PALSAR Data Stacks: A Case Study of Three Gorges Area, China. *Remote Sens.* **2016**, *8*, 136.
https://doi.org/10.3390/rs8020136

**AMA Style**

Shi X, Liao M, Li M, Zhang L, Cunningham C. Wide-Area Landslide Deformation Mapping with Multi-Path ALOS PALSAR Data Stacks: A Case Study of Three Gorges Area, China. *Remote Sensing*. 2016; 8(2):136.
https://doi.org/10.3390/rs8020136

**Chicago/Turabian Style**

Shi, Xuguo, Mingsheng Liao, Menghua Li, Lu Zhang, and Cory Cunningham. 2016. "Wide-Area Landslide Deformation Mapping with Multi-Path ALOS PALSAR Data Stacks: A Case Study of Three Gorges Area, China" *Remote Sensing* 8, no. 2: 136.
https://doi.org/10.3390/rs8020136