Landslide susceptibility prediction considering land use change and human activity: A case study under rapid urban expansion and afforestation in China

Xiong, Hanxiang; Ma, Chuanming; Li, Minghong; Tan, Jiayao; Wang, Yuzhou

doi:10.1016/j.scitotenv.2023.161430

Cited by 32 publications

(19 citation statements)

References 103 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The increase in built-up land is mainly distributed around government residences with relatively flat terrain and frequent socio-economic activities. Numerous studies have assessed the impact of LULC changes on landslide susceptibility [18,20,22,25]. However, human activities are carried out by road network [77].…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, this article has updated the list of road networks and LULC. It should be noted that many researchers have explored the application of different landslide inventory in land-use change, such as Xiong et al [22] used LULC and landslide inventories from 2000 and 2020 and Tyagi et al [18] used 218, 243, and 387 landslide events from 2005 to 2010, 2010 to 2015, and 2015 to 2020, respectively. On the contrary, Hao et al [21] only used the 2018 landslide inventory for dynamic research.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Tempo-Spatial Landslide Susceptibility Assessment from the Perspective of Human Engineering Activity

Zeng,

Guo,

Wang

et al. 2023

Remote Sensing

View full text Add to dashboard Cite

The expansion of mountainous urban areas and road networks can influence the terrain, vegetation, and material characteristics, thereby altering the susceptibility of landslides. Understanding the relationship between human engineering activities and landslide occurrence is of great significance for both landslide prevention and land resource management. In this study, an analysis was conducted on the landslide caused by Typhoon Megi in 2016. A representative mountainous area along the eastern coast of China—characterized by urban development, deforestation, and severe road expansion—was used to analyze the spatial distribution of landslides. For this purpose, high-precision Planet optical remote sensing images were used to obtain the landslide inventory related to the Typhoon Megi event. The main innovative features are as follows: (i) the newly developed patch generating land-use simulation (PLUS) model simulated and analyzed the driving factors of land-use land-cover (LULC) from 2010 to 2060; (ii) the innovative stacking strategy combined three strong ensemble models—Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM)—to calculate the distribution of landslide susceptibility; and (iii) distance from road and LULC maps were used as short-term and long-term dynamic factors to examine the impact of human engineering activities on landslide susceptibility. The results show that the maximum expansion area of built-up land from 2010 to 2020 was 13.433 km2, mainly expanding forest land and cropland land, with areas of 8.28 km2 and 5.99 km2, respectively. The predicted LULC map for 2060 shows a growth of 45.88 km2 in the built-up land, mainly distributed around government residences in areas with relatively flat terrain and frequent socio-economic activities. The factor contribution shows that distance from road has a higher impact than LULC. The Stacking RF-XGB-LGBM model obtained the optimal AUC value of 0.915 in the landslide susceptibility analysis in 2016. Furthermore, future road network and urban expansion have intensified the probability of landslides occurring in urban areas in 2015. To our knowledge, this is the first application of the PLUS and Stacking RF-XGB-LGBM models in landslide susceptibility analysis in international literature. The research results can serve as a foundation for developing land management guidelines to reduce the risk of landslide failures.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Tempo-Spatial Landslide Susceptibility Assessment from the Perspective of Human Engineering Activity

Zeng,

Guo,

Wang

et al. 2023

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…High GmD zones are predominantly clustered in and around the terrain with steep slopes, which are also highly vulnerable to landslides (Figures 6, 7b High morphometric variations of the drainage basins, along with the high amplitude of relief and increased anthropogenic activities in the region, have aggravated the potential for geological hazards such as landslides (Arabameri et al, 2020;Bajala et al, 2022;R ożycka & Migo n, 2022;Xiong et al, 2023). The region falls under a high seismic risk zone and has shown potential for topographic amplification (Agrawal & Dixit, 2022b), which may further exacerbate the problem of rock sliding during earthquakes.…”

Section: Discussionmentioning

confidence: 99%

An assessment of the geomorphodiversity and land use/cover change (LUCC) effects associated with landslides in Meghalaya, India

Agrawal,

Dixit

2024

Earth Surf Processes Landf

View full text Add to dashboard Cite

The Shillong Plateau in the Eastern Himalayas is exposed to high seismicity, neo‐tectonic activity and orographic precipitation that aggravated landslides in the region by affecting hillslope processes. Landscape development is influenced by landslide phenomenon and depends upon geomorphic processes and geomorphodiversity (GmD). It is linked intimately with geomorphology, hydrology and soil type. This study uses a remote sensing and GIS‐based approach to assess the spatial linkage between GmD and landslide distribution in Meghalaya (India). GmD index (GmDI) is developed using geological, morphometric and geomorphological parameters and analysed with landslide distribution. The landslide distribution considering land use/cover change (LUCC) is also examined. The result shows that the region with high‐relief, valley and depression zone, mainly along the Dauki fault, have a high to a very high GmDI. About 61% of landslide localities are in zones of high GmDI, concentrated in the central and eastern parts of Meghalaya. Density analysis of the very high class (class 5) of GmD confirms the same. Most of these landslides occur in dense and light‐vegetated landmasses. However, the LUCC analysis reveals a significant increase in the built area on steeper slopes (average expansion ratio of 2.30 for slopes >15°) between 2017 and 2022, indicating a rising threat of landslides in urban areas of Meghalaya. The study presents the importance of GmD in active tectonic regions with particular reference to landslide potential and recent LUCC. It can aid decision‐makers in planning sustainable developments and risk mitigation strategies for landslide hazards and geoconservation.

show abstract

“…Landslide sensitivity assessment is an important component of landslide risk analysis. Landslide susceptibility zoning (LSZ) is the process of determining the probability of a landslide occurring in an area and presenting the landslide risk area spatially in the form of a landslide susceptibility map (LSM) 9 , 10 . Landslide susceptibility areas are usually delineated based on geologic activities, soil structure, topography, hydrologic environment, and human activities as landslide causative factors and combined with GIS techniques 11 .…”

Section: Introductionmentioning

confidence: 99%

“…Heuristic methods are based on a priori knowledge to predict landslides by assuming subjective weights of different factors that may lead to the occurrence of landslides 13 . Physical methods predict landslides through a rigorous mathematical process based on the physical mechanisms by which landslides occur 9 , such as limit equilibrium, finite element, and limit analysis methods. Although physical methods provide a more realistic response to the mechanism and process of landslide occurrence, the use of such methods requires precise mechanical parameters and therefore can only be applied to a certain type of slope stability calculation 14 .…”

Section: Introductionmentioning

confidence: 99%

Landslide susceptibility zonation using the analytical hierarchy process (AHP) in the Great Xi’an Region, China

Liu,

Shao,

Shao

2024

Sci Rep

View full text Add to dashboard Cite

This study aims to delineate landslide susceptibility maps using the Analytical Hierarchy Process (AHP) method for the Great Xi’an Region, China, which is a key planning project for urban construction in Shaanxi Province, China from 2021 to 2035. Multiple data as elevation, slope, aspect, curvature, river density, soil, lithology, and land use have been considered for delineating the landslide susceptibility maps. Spatially thematic layers and distributed maps of all the aforementioned parameters were created in a GIS environment. Determine the relative importance of these thematic layers in the occurrence of landslides in the study area concerning historical landslide data to assign appropriate weights. Landslide sensitivity maps were generated by a weighted combination in a GIS environment after being analyzed by the AHP method. The sensitivity maps were categorized as “very high (11.06%), high (19.41%), moderate (23.03%), low (28.70%), and very low (17.80%)”. Overlay analysis of the test data with the LSM showed that the moderate to very high landslide susceptibility zones were able to contain 82.58% of the historic landslides. The results of the study help determine the landslide-prone areas in the area and provide a reference for subsequent construction. In addition, the analysis of landslide susceptibility in the area contributes to the study of landslides in similar loess sites.

show abstract

Landslide susceptibility prediction considering land use change and human activity: A case study under rapid urban expansion and afforestation in China

Cited by 32 publications

References 103 publications

Tempo-Spatial Landslide Susceptibility Assessment from the Perspective of Human Engineering Activity

Tempo-Spatial Landslide Susceptibility Assessment from the Perspective of Human Engineering Activity

An assessment of the geomorphodiversity and land use/cover change (LUCC) effects associated with landslides in Meghalaya, India

Landslide susceptibility zonation using the analytical hierarchy process (AHP) in the Great Xi’an Region, China

Contact Info

Product

Resources

About