Loess Landslide Inventory Map Based on GF-1 Satellite Imagery

Wenyi Sun,Yuansheng Tian,Jun Zhai,Xingmin Mu,Peng Gao,Guangju Zhao

doi:10.3390/rs9040314

Abstract

Rainfall-induced landslides are a major threat in the hilly and gully regions of the Loess Plateau. Landslide mapping via field investigations is challenging and impractical in this complex region because of its numerous gullies. In this paper, an algorithm based on an object-oriented method (OOA) has been developed to recognize loess landslides by combining spectral, textural, and morphometric information with auxiliary topographic parameters based on high-resolution multispectral satellite data (GF-1, 2 m) and a high-precision DEM (5 m). The quality percentage (QP) values were all greater than 0.80, and the kappa indices were all higher than 0.85, indicating good landslide detection with the proposed approach. We quantitatively analyze the spectral, textural, morphometric, and topographic properties of loess landslides. The normalized difference vegetation index (NDVI) is useful for discriminating landslides from vegetation cover and water areas. Morphometric parameters, such as elongation and roundness, can potentially improve the recognition capacity and facilitate the identification of roads. The combination of spectral properties in near-infrared regions, the textural variance from a grey level co-occurrence matrix (GLCM), and topographic elevation data can be used to effectively discriminate terraces and buildings. Furthermore, loess flows are separated from landslides based on topographic position data. This approach shows great potential for quickly producing accurate results for loess landslides that are induced by extreme rainfall events in the hilly and gully regions of the Loess Plateau, which will help decision makers improve landslide risk assessment, reduce the risk from landslide hazards and facilitate the application of more reliable disaster management strategies.

Highlights

Landslides represent a major geological hazard and play an important role in the evolution of landscapes [1,2]
In July 2013, prolonged heavy rain fell over an area of approximately 37,000 km2 in Yan’an in the central part of the Loess Plateau, and this rain induced 8135 landslides, destroyed approximately 10,000 cave dwellings, displaced 160,000 residents and killed 45 people according to the local government [7]
We found that loess landslides have a much higher reflectance in the visible channels compared to vegetation cover (Figure 4b–d) and can be discriminated based on their reflectance features

Summary

Introduction

Landslides represent a major geological hazard and play an important role in the evolution of landscapes [1,2]. Landslides can be caused by a variety of natural or human-induced triggers, such as extreme rainfall, earthquakes and engineering activity, and often result in tragic casualties, tremendous economic losses and ecological environment damage [3,4,5]. Numerous landslides occur in the hilly and gully regions of China’s Loess Plateau during the rainy season from July to September [6]. In July 2013, prolonged heavy rain fell over an area of approximately 37,000 km in Yan’an in the central part of the Loess Plateau, and this rain induced 8135 landslides, destroyed approximately 10,000 cave dwellings, displaced 160,000 residents and killed 45 people according to the local government [7].

Objectives

Methods

Results

Discussion

Conclusion