Hazard, Vulnerability and Capacity Mapping for Landslides Risk Analysis using Geographic Information System (GIS)

Sari, Deffi Ayu Puspito; Innaqa, Suci; Safrilah,

doi:10.1088/1757-899x/209/1/012106

Cited by 28 publications

(22 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Women's ability to deal with disasters will be lower because the tendency of women to be physically weaker than men, so that the female population will need the help of male residents [8]. [4], Research by Sari [6], and Research by Bayuaji [9]. Based on all three, modifications and adjustments were made to the research area as in Table 2 and Table 3.…”

Section: Vulnerability Variable and Methodsmentioning

confidence: 99%

“…Unlike vulnerability, community capacity is closely related to efforts to reduce the impact of disasters, which consist of mitigation, disaster preparedness, and the ability to survive. Capacity is a system or a community that is potentially exposed to danger to adapt or change to achieve or maintain acceptable levels of function and structure [6]. Capacity is more directed at the ability of each individual in dealing with and handling disaster.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Community Vulnerability and Capacity to Landslides in South Babakan Madang Subdistrict, Bogor Districts

2019

View full text Add to dashboard Cite

Many countries in the world have various kinds of problems, such as disasters. Indonesia is one of the countries with high area and population affected by landslides, such as in several regions in Indonesia, namely Bogor Districts. The affected population can be caused by the increasing number of residents and built-up areas, as well as the low level of public knowledge about landslides. The high population affected can describe the level of vulnerability and capacity that exists in the community, such as in South Babakan Madang Subdistrict. The density of the population and the built-up area which includes settlements, public facilities and community knowledge related to landslides that are different in 3 Countryside namely Bojong Koneng, Cijayanti, and Karang Tengah make the people in South Babakan Madang Subdistrict vulnerable to landslides. The modified scoring method with reference to Perka BNPB No. 02 of 2012 can be used to determine the level of vulnerability and capacity of the community. The results show that South Babakan Madang Subdistrict is dominated by moderate vulnerability with an index between 0.34 - 0.67. The capacity in the South Babakan Madang Subdistrict tends to be homogeneous in the low capacity class with an index < 0.34.

show abstract

Section: Vulnerability Variable and Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Community Vulnerability and Capacity to Landslides in South Babakan Madang Subdistrict, Bogor Districts

2019

View full text Add to dashboard Cite

show abstract

“…In the technique of one group the data collector or interviewer know that there is only one possibility of the answer for all the attributes that whether the respondent tell truth or lie [11][12][13]. So data privacy is in danger for this type of technique [14][15][16][17][18].…”

Section: Two-group Methodsmentioning

confidence: 99%

Multigroup Classification using Privacy Preserving Data Mining

Erwinsyah,

Chin,

Palalloi

et al. 2019

IJEAT

View full text Add to dashboard Cite

Getting the useful and important data from a huge amount of information is known as data mining. It is a prominent field for search and research of data. To improve the communication between customers and organizations data mining is used. Preserve the private data is very necessary in data mining. It is the issue on which research developed their research in many different ways. For protecting the survey privacy and to avoid the bias answer the randomized response technique was developed. To prevent the data of the survey certain randomness will add with the answers. To improve the privacy level of the preserve data this research use multigroup methods. In this approach all the survey answer divided in multiple groups and then. For different groups data should randomize differently. Based on this multiple groups the decision tree used to classify the data. One group, two group and three group’s techniques used to preserve the data

show abstract

“…Quantitative methods and models that have been proposed for the assessment can be divided into methods of statistical analysis (Sari et al, 2017), mathematical models (Akgun et al, 2012) and machine learning (He and Fu, 2009). However, most of these methods are subjective, such as expert evaluations, analytical hierarchy processes, logistic regressions and fuzzy integration methods, which could affect the accuracy and reasonableness of the evaluation (Fall et al, 2006;Sarkar and Gupta, 2005). This shortcoming can be overcome through the artificial neural network, especially the mature back propagation (BP) neural network that is widely used in function approximation and pattern recognition (Ke and Li, 2014a;Li et al, 2013;Su and Deng, 2003).…”

Section: Introductionmentioning

confidence: 99%

Application of the Levenburg–Marquardt back propagation neural network approach for landslide risk assessments

Xiong

Sun

Zhang

et al. 2019

Nat. Hazards Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. Landslide disasters are one of the main risks involved with the operation of long-distance oil and gas pipelines. Because previously established disaster risk models are too subjective, this paper presents a quantitative model for regional risk assessment through an analysis of the patterns of historical landslide disasters along oil and gas pipelines. Using the Guangyuan section of the Lanzhou–Chengdu–Chongqing (LCC) long-distance multiproduct oil pipeline (82 km) in China as a case study, we successively carried out two independent assessments: a susceptibility assessment and a vulnerability assessment. We used an entropy weight method to establish a system for the vulnerability assessment, whereas a Levenberg–Marquardt back propagation (LM-BP) neural network model was used to conduct the susceptibility assessment. The risk assessment was carried out on the basis of two assessments. The first, the system of the vulnerability assessment, considered the pipeline position and the angle between the pipe and the landslide (pipeline laying environmental factors). We also used an interpolation theory to generate the standard sample matrix of the LM-BP neural network. Accordingly, a landslide susceptibility risk zoning map was obtained based on susceptibility and vulnerability assessment. The results show that about 70 % of the slopes were in high-susceptibility areas with a comparatively high landslide possibility and that the southern section of the oil pipeline in the study area was in danger. These results can be used as a guide for preventing and reducing regional hazards, establishing safe routes for both existing and new pipelines, and safely operating pipelines in the Guangyuan area and other segments of the LCC oil pipeline.

show abstract

Hazard, Vulnerability and Capacity Mapping for Landslides Risk Analysis using Geographic Information System (GIS)

Cited by 28 publications

References 1 publication

Community Vulnerability and Capacity to Landslides in South Babakan Madang Subdistrict, Bogor Districts

Community Vulnerability and Capacity to Landslides in South Babakan Madang Subdistrict, Bogor Districts

Multigroup Classification using Privacy Preserving Data Mining

Application of the Levenburg–Marquardt back propagation neural network approach for landslide risk assessments

Contact Info

Product

Resources

About