GIS based landslide susceptibility mapping and assessment using weighted overlay method in Wayanad: A part of Western Ghats, Kerala

Arumugam, Thangavelu; Kinattinkara, Sapna; Velusamy, Sampathkumar; Shanmugamoorthy, Manoj; Murugan, Sakthivel

doi:10.1016/j.uclim.2023.101508

Cited by 11 publications

(2 citation statements)

References 47 publications

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“…The SMCE method using ArcGIS software can be performed using Weighted Overlay Analysis. Each conditioning factor for weighted overlays is adjusted based on its interaction with the causes and the frequencies of specific disasters (Arumugam et al, 2023). The SMCE formula is expressed as Equation 1.…”

Section: Hazard Assessmentmentioning

confidence: 99%

Multi-Hazard Analysis in Gunungkidul Regency Using Spatial Multi-Criteria Evaluation

Mustikaningrum,

Widhatama,

Widantara

et al. 2023

For. Geo.

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This study has two aims: to determine the spatial distribution of multi-hazard levels and to discover the interactions, interdependencies, and effects that cascade among hazards in Gunungkidul Regency, Special Region of Yogyakarta. A multi-hazard map was created with a scale of 1:250,000 and modelled using SMCE (Spatial Multi-Criteria Evaluation). The conditioning factors used included slope, rainfall, historical data, river distance, geomorphology, land cover, lithology, and fault distance. The selected conditioning factors for each hazard were then weighted using weighted overlay analysis. The results showed that the area of Gunungkidul can be included in the high-risk category for floods, since the probability of flooding is 56.72%, the probability of landslides is 9.14%, that of drought is 48.86%, and that of seismic disturbance is 20.83%. (Multi-hazard maps are created by overlaying flood, landslide, seismic, and drought hazard maps.) After these risk factors were calculated, the regions on the multi-hazard map were re-categorized into five hazard classes. All areas in Gunungkidul Regency have multiple hazards, with risk factors of different magnitudes. The interaction between hazards can generate new hazards that are called cascading hazards. The cascading hazards in the study area are most likely to occur in the north of Gunungkidul Regency with its very high seismic and landslide hazard risk factors, due to the geological and geomorphological conditions of the Baturagung Structural Hills.

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Section: Hazard Assessmentmentioning

confidence: 99%

Multi-Hazard Analysis in Gunungkidul Regency Using Spatial Multi-Criteria Evaluation

Mustikaningrum,

Widhatama,

Widantara

et al. 2023

For. Geo.

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“…This information is valuable for identifying hotspots of high SOC stocks and areas with lower SOC content, which can inform land management decisions and targeted conservation efforts. ArcGIS weighted overlay tool is handy for analyzing, mapping, and assessing spatial variability in different applications of the environment [63]. In this case, it has been used to determine soil organic carbon (SOC) by integrating multiple factors and providing a local understanding of the spatial distribution of SOC in the high Andean ecosystem of Puno-Peru.…”

Section: Geostatistical Analysismentioning

confidence: 99%

Spatial Distribution of Soil Organic Carbon in Relation to Land Use, Based on the Weighted Overlay Technique in the High Andean Ecosystem of Puno—Peru

Canaza,

Calizaya,

Chambi

et al. 2023

Sustainability

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Soil organic carbon (SOC) is a crucial component of the planet and is essential for agriculture development. Our region is known for its livestock and agricultural activities. Hence, understanding the spatial distribution of SOC is crucial for sustainable land management of soils in the mountain ecosystems in the Andes. The methodology consisted of obtaining 53 soil samples from depths of 0 to 105 cm, which were analyzed to obtain SOC (Kg/m2) and organic matter (OM) (%). Ordinary kriging, a geostatistical method, was used to determine SOC. Pearson’s statistical method was applied to determine the association between SOC and precipitation, temperature, altitude, and organic matter and gave acceptable correlations of 0.38, −0.32, 0.40, and 0.59. These results were used to apply weighting criteria for climatological and environmental variables. The weighted overlay tool was used for modeling and mapping the spatial variability of SOC. The estimated spatial distribution of SOC in the micro-watershed reveals an increasing trend from south to north, specifically within the 0–20 cm depth profile. The study confirmed through the spatial analysis that regions with intensive agriculture have low reserves (<3 Kg/m2) of SOC, and areas without agricultural activity but with grazing have average resources of 3 Kg/m2 to 5 Kg/m2 of SOC. Finally, in the upper micro-watersheds where there is no agricultural activity, the reserves are high (5 Kg/m2 to 6.8 Kg/m2). Accordingly, we can promote sustainable and responsible land use practices that support long-term productivity, environmental protection, and societal well-being by prioritizing efficient land utilization, soil conservation, biodiversity conservation, land restoration, and informed land use planning in the high Andean ecosystem of Puno–Peru.

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A predictive model incorporating geomorphic factors for assessing the longevity of landslide-dammed lakes

Wu,

Chan,

Lin

2023

Landslides

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GIS based landslide susceptibility mapping and assessment using weighted overlay method in Wayanad: A part of Western Ghats, Kerala

Cited by 11 publications

References 47 publications

Multi-Hazard Analysis in Gunungkidul Regency Using Spatial Multi-Criteria Evaluation

Multi-Hazard Analysis in Gunungkidul Regency Using Spatial Multi-Criteria Evaluation

Spatial Distribution of Soil Organic Carbon in Relation to Land Use, Based on the Weighted Overlay Technique in the High Andean Ecosystem of Puno—Peru

A predictive model incorporating geomorphic factors for assessing the longevity of landslide-dammed lakes

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