Innovative landslide susceptibility mapping supported by geomorphon and geographical detector methods

Luo, Wei; Liu, Cheng Chien

doi:10.1007/s10346-017-0893-9

Cited by 98 publications

(52 citation statements)

References 43 publications

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“…In general, the relief and precipitation are the key drivers of landslides. In mountainous areas, under the background of heavy relief and precipitation, most studies consider that changes in land use may be direct drivers of landslides [7,8,[34][35][36][37]. Cropland is the largest land use type of human landscape [38].…”

Section: Introductionmentioning

confidence: 99%

Landslides and Cropland Abandonment in China’s Mountainous Areas: Spatial Distribution, Empirical Analysis and Policy Implications

Deng

Zeng

et al. 2018

Sustainability

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Cropland, as the largest land use type in the human landscape, contributes to not only biodiversity but also global food security. However, cropland abandonment not only is harmful to agricultural cultural landscapes but also threatens food security. Prior studies have suggested that changes in the social environment drive farmers to abandon cropland. In contrast, this study reveals that factors of the natural environment (e.g., landslides) have steadily and significantly affected cropland abandonment after controlling the factors of the social environment. More specifically, based on the survey data of a large sample of 4850 mountainous households in 24 provinces of China and following the theoretical framework of “environment → land use”, this study quantitatively identified the impacts of landslides on cropland abandonment in mountainous areas using the Probit and Tobit models. The results show that: (1) There is a similar spatial agglomeration trend between landslides and cropland abandonment. Namely, an area that has a high incidence of landslides also has a high incidence of cropland abandonment. (2) There is a significant and positive correlation between landslides and cropland abandonment. Namely, compared with peasants who have not suffered from landslides, the probability that peasants suffering from landslides will abandon cropland and the area abandoned increase by 6.8% and 0.064 mu, respectively. (3) Elderly farmers (over 64 years old) and the development of urbanization help curb cropland abandonment in the mountains. The results of this study may provide reference for the government to implement effective policies for managing landslides and revitalizing unused cropland resources.

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Section: Introductionmentioning

confidence: 99%

Landslides and Cropland Abandonment in China’s Mountainous Areas: Spatial Distribution, Empirical Analysis and Policy Implications

Deng

Zeng

et al. 2018

Sustainability

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“…The Geodetector Frequency-Ratio Index was calculated as a weighted geometric mean [37] using the relative weight of significant predictor variables and their frequency ratio values in each interval given by the formula below:…”

Section: Geodetector Frequency Ratio Indexmentioning

confidence: 99%

“…The interval with higher FR is more susceptible to the incidence. We assigned the weights to the predictor variables based on the Geodetector results and assigned the rating based on the FR method to compute the Nitrate Susceptibility Index (NSI) using the geometric mean [37].…”

Section: Introductionmentioning

confidence: 99%

Assessment of Groundwater Nitrate Pollution Potential in Central Valley Aquifer Using Geodetector-Based Frequency Ratio (GFR) and Optimized-DRASTIC Methods

Shrestha

Luo

2018

IJGI

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Groundwater nitrate contamination in the Central Valley (CV) aquifer of California is widespread throughout the valley because of excess nitrogen fertilizer leaching down into the aquifer. The percolation of nitrate depends on several hydrogeological conditions of the valley. Groundwater contamination vulnerability mapping uses hydrogeologic conditions to predict vulnerable areas. This paper presents a new Geodetector-based Frequency Ratio (GFR) method and an optimized-DRASTIC method to generate nitrate vulnerability index values for the CV. The optimized-DRASTIC method combined the individual weights and rating values for Depth to water, Recharge rate, Aquifer media, Soil media, Topography, Impact of vadose zone, and Hydraulic conductivity. The GFR method incorporated the Frequency-Ratio (FR) method to derive rating values and the Geodetector method to derive relative Power of Determinant (PD) values as weights to generate nitrate susceptibility index map. The optimized-DRASTIC method generated very-high to high index values in the eastern part of the CV. The GFR method showed very-high index values in most part of the San Joaquin and Tulare basin. The quantitatively derived rating values and weights in the GFR method improved the vulnerability index and showed better consistency with the observed nitrate contamination pattern than optimized-DRASTIC index, suggesting that GFR is a better method for groundwater contamination vulnerability mapping in the CV aquifer.

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“…A standard LSM based on the geometric mean of multivariables, including a newly introduced region-based preparatory TF factor, was developed to map the landslide susceptibility in I-Lan [25,26]. This LSM can be used to predict landslides by weighting various preparatory factors pf [27] according to their contributions, and to compute a landslide susceptibility index (LSI) using the geometric mean model [28,29].…”

Section: Landslide Susceptibility Modelmentioning

confidence: 99%

“…Although a more advanced model based on weighted geometric mean of variables selected by the geographical detector and on slope units derived from the geomorphon method [26] was also developed for simplicity and to focus on the issue of shadows, the standard model as expressed in Equation (5) is employed here to illustrate and evaluate the possible errors incurred by neglecting the shadow inventory. Note that the geomorphon method is an innovative pattern recognition approach for identifying landform elements based on the line of sight concept, and it is adapted to delineate ridge lines and valley lines to form slope units at self-adjusted spatial scale suitable for LSM [26].…”

Section: Landslide Susceptibility Modelmentioning

confidence: 99%

Influences of the Shadow Inventory on a Landslide Susceptibility Model

Liu

Luo

Chung

et al. 2018

IJGI

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A landslide inventory serves as the basis for assessing landslide susceptibility, hazard, and risk. It is generally prepared from optical imagery acquired from spaceborne or airborne platforms, in which shadows are inevitably found in mountainous areas. The influences of shadow inventory on a landslide susceptibility model (LSM), however, have not been investigated systematically. This paper employs both the shadow and landslide inventories prepared from eleven Formosat-2 annual images from the I-Lan area in Taiwan acquired from 2005 to 2016, using a semiautomatic expert system. A standard LSM based on the geometric mean of multivariables was used to evaluate the possible errors incurred by neglecting the shadow inventory. The results show that the LSM performance was significantly improved by 49.21% for the top 1% of the most highly susceptible area and that the performance decreased gradually by 15.25% for the top 10% most highly susceptible areas and 9.71% for the top 20% most highly susceptible areas. Excluding the shadow inventory from the calculation of landslide susceptibility index reveals the real contribution of each factor. They are crucial in optimizing the coefficients of a nondeterministic geometric mean LSM, as well as in deriving the threshold of a landslide hazard early warning system.

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Innovative landslide susceptibility mapping supported by geomorphon and geographical detector methods

Cited by 98 publications

References 43 publications

Landslides and Cropland Abandonment in China’s Mountainous Areas: Spatial Distribution, Empirical Analysis and Policy Implications

Landslides and Cropland Abandonment in China’s Mountainous Areas: Spatial Distribution, Empirical Analysis and Policy Implications

Assessment of Groundwater Nitrate Pollution Potential in Central Valley Aquifer Using Geodetector-Based Frequency Ratio (GFR) and Optimized-DRASTIC Methods

Influences of the Shadow Inventory on a Landslide Susceptibility Model

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