# Influences of the Shadow Inventory on a Landslide Susceptibility Model

^{1}

^{2}

^{3}

^{4}

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Study Area and Satellite Images

## 3. Landslide Susceptibility Model

_{pf}

_{(i)}is defined as:

_{pf}

_{(i),}and the total area of the study area is A

_{t}. At each interval, the landslide ratio LR

_{pf}

_{(i)}is therefore defined as the area ratio of

_{pf}

_{(i)}is the landslide area of pf at interval i. L

_{t}is the total landslide area. Because all landslides are delineated on Formosat-2 imagery outside shadowy areas, there is no intersection between the landslide and the shadow inventories. The weight of pf at interval i can be defined as the frequency ratio.

## 4. Influences of Shadows on the LSM

_{pf}

_{(i)}(the shadowy area of pf at interval i) from A

_{pf}

_{(i)}, we redefine $A{R}_{pf(i)}^{*}$ (the shadow-corrected area ratio at each interval i) as:

## 5. Conclusions

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 1.**(

**a**) A standard false color image of I-Lan taken by Formosat-2 on 24 August 2009. Both the landslide inventory and shadow inventory were prepared using a semiautomatic expert system [24] and masked as yellow and white polylines, respectively. (

**b**) The union of all landslide inventories (yellow polygons) and shadow inventories (white polygons) derived from the annual Formosat-2 imagery (2005–2016). The river channel and those regions outside the study area are annotated in blue. The area ratios of landslide inventory and shadow inventory are 3.9% and 34.1%, respectively.

**Figure 2.**Bar charts of (

**a**) $A{R}_{Slope}$ (green bars) vs. $A{R}_{Slope}^{*}$ (red bars), and (

**b**) ${W}_{Slope}$ (green bars) vs. ${W}_{Slope}^{*}$ (red bars).

**Figure 3.**Bar charts of (

**a**) $A{R}_{Aspect}$ (green bars) vs. $A{R}_{Aspect}^{*}$ (red bars), and (

**b**) ${W}_{Aspect}$ (green bars) vs. ${W}_{Aspect}^{*}$ (red bars).

**Figure 4.**Bar charts of (

**a**) $A{R}_{TF}$ (green bars) vs. $A{R}_{TF}^{*}$ (red bars), and (

**b**) ${W}_{TF}$ (green bars) vs. ${W}_{TF}^{*}$ (red bars).

**Figure 5.**Bar charts of (

**a**) $A{R}_{Lithology}$ (green bars) vs. $A{R}_{Lithology}^{*}$ (red bars), and (

**b**) ${W}_{Lithology}$ (green bars) vs. ${W}_{Lithology}^{*}$ (red bars).

**Figure 6.**Maps of (

**a**) LSI (without the correction for shadows) and (

**b**) LSI* (with the correction for shadows) for all cells using Equations (5) and (8), respectively.

**Figure 7.**Cumulative percentage of landslide occurrence (CPOLO) based on LSM* (solid line) and LSM (broken line). The percentage of improvement ρ is plotted as a dotted line.

The Most Highly Susceptible Area | LSM | LSM* |
---|---|---|

top 1% | 5.42% | 8.09% |

top 10% | 33.60% | 38.72% |

top 20% | 53.70% | 58.91% |

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**MDPI and ACS Style**

Liu, C.-C.; Luo, W.; Chung, H.-W.; Yin, H.-Y.; Yan, K.-W.
Influences of the Shadow Inventory on a Landslide Susceptibility Model. *ISPRS Int. J. Geo-Inf.* **2018**, *7*, 374.
https://doi.org/10.3390/ijgi7090374

**AMA Style**

Liu C-C, Luo W, Chung H-W, Yin H-Y, Yan K-W.
Influences of the Shadow Inventory on a Landslide Susceptibility Model. *ISPRS International Journal of Geo-Information*. 2018; 7(9):374.
https://doi.org/10.3390/ijgi7090374

**Chicago/Turabian Style**

Liu, Cheng-Chien, Wei Luo, Hsiao-Wei Chung, Hsiao-Yuan Yin, and Ke-Wei Yan.
2018. "Influences of the Shadow Inventory on a Landslide Susceptibility Model" *ISPRS International Journal of Geo-Information* 7, no. 9: 374.
https://doi.org/10.3390/ijgi7090374