Tropical Geography ›› 2020, Vol. 40 ›› Issue (3): 478-486.

### Spatio-Temporal Patterns of Landslides in Hani Rice Terraces World Heritage Site Based on Spatial Density Function

Ding Zhiqiang1(), Gao Xuan1, Jiao Yuanmei1(), Li Yuhui1, Guo Rujun2

1. 1.School of Tourism and Geographical Sciences, Yunnan Normal University, Kunming 650500, China
2.School of Earth Sciences, China University of Geosciences, Wuhan 430074, China
• Received:2019-05-15 Revised:2019-09-09 Online:2020-05-31 Published:2020-06-30
• Contact: Jiao Yuanmei E-mail:zhiqiang_ding9303@163.com;ymjiao@sina.com

Abstract:

Landslides are the fourth leading natural hazard that threaten human survival after floods, earthquakes, and drought. The frequency and density of landslides are increasing with the intensification of climate change and human activities. For World Heritage Sites around the world, landslide risk affects their integrity, aesthetic value, and sustainable development. The study of the spatial and temporal distribution patterns of landslides could aid in understanding the factors influencing landslide and provide guidance for disaster prevention and mitigation and heritage conservation. The Honghe Hani Rice Terraces World Heritage is an important cultural landscape located in the mountainous area of Yunnan Province, China, where landslides frequently occur during the annual rainy season. To investigate the spatiotemporal pattern of landslides in the heritage core area, a landslide database was established based on the remote sensing images of Google Earth at a resolution of 0.55 m in 2005, 2009, and 2015, combined with a field survey. The nearest neighbor index, K function, and kernel density function of the landslides are calculated and analyzed with ArcGIS 10.2. The results are as follows: 1) The number of landslides of study area in 2005, 2009, and 2015 are 184, 337, and 285 respectively. The nearest neighbor index indicates that the landslides are spatially clustered, and their aggregation decreased over time. The K-function analysis shows that the most significant spatial scale of landslide aggregation is 1 km. The thresholds from aggregation to discrete distribution are 2.9, 3.9, and 3.6 km in 2005, 2009, and 2015, respectively. 2) In terms of spatial distribution, the analysis of the kernel density function shows that the high-density area of the landslides in the heritage core area contains multiple centers, such as forest areas on the western and eastern sides of the study area; the villages of Duoyishu, Dongpu, Mengpin, and Shuibulong; and terraced fields in the Amengkong and Bimeng river basins. 3) During the period studied, the proportion of high-density landslide areas increased from 2005 to 2015 (2.3%→5.8%→8.3%). The proportion of medium-density areas also increased (15.7%→21.8%→27.9%), while the proportion of low-density areas decreased (82.0%→72.5%→66.8%). On the scale of administrative villages, the proportion of high, medium, and low-density landslides in each village varied over time. The villages with increased high-density areas over time are Dongpu, Shuibulong, Duoyishu, Baoshan, and Xinjie, which need to reduce landslide risks significantly. The detailed analysis of the occurrence mechanism, influencing factors, monitoring, and early warning of landslides is beyond the scope of the present study. In the future, we will explore the potential interactions between geographical conditions and landslides. In particular, we will quantify the contribution of human activities to landslide risks to improve our understanding of the mechanisms of landslide occurrence in similar regions as well as the accuracy of landslide risk prediction. In summary, the spatial pattern of landslides in the study area changed significantly from 2005 to 2015. The risk of landslides has become more unpredictable as human interventions increase on the surface landscapes.

CLC Number:

• P642.22