Satellite remote sensing for global landslide monitoring

Hong, Yang; Adler, Robert E.; Huffman, George J.

doi:10.1029/2007eo370001

Cited by 41 publications

(8 citation statements)

References 16 publications

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“…Google Earth has high-resolution pictures, 3-D features, zoom, and allow drawing polygons on the area under study, which simplifies the analysis and mapping of slopes besides landslide studies [70][71][72]. These images can be stored, retrieved, measured, and further treated by a GIS package.…”

Section: Fusion Of In Situ and Gis Informationmentioning

confidence: 99%

“…Integration calls for the alignment of performance metrics within and through business entities, and functions to integrate bottom line performance measurement through organizations, as well as value chains to notify management while guaranteeing decision-making, clarity, and external reporting. Integration and change administration are critical achievement factors for the progress of strategic sustainability initiatives [70][71][72]. A holistic methodology has to be thought that takes into consideration:…”

Section: Economic Indicators and Evaluation Tools For Sustainabilitymentioning

confidence: 99%

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Emergency Response Cyber-Physical Framework for Landslide Avoidance with Sustainable Electronics †

et al. 2018

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An Emergency Response (ER) Cyber-Physical System (CPS) to avoid landslides and survey areas located on or near slopes is introduced that handles two problems: electronic waste disposal, and environmental disasters. Uncomplicated detection circuits using salvaged components can pinpoint floods in impoverished regions. CPSs simplify hazard prediction and mitigation in disaster supervision. Nonetheless, few green practices and efforts have been accomplished in this regard. Recent technical advances help landslides studies and the evaluation of suitable risk alleviation measures. This work addresses in situ meters, and cameras to observe ground movements more accurately. The ER-CPS identifies and can help mitigate landslides using techniques based on motion detection that can productively predict and monitor the zone conditions to classify it, and the landslide-related data can be transmitted to inspecting stations to lessen the erosion/sedimentation likelihood while increasing security.

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Section: Fusion Of In Situ and Gis Informationmentioning

confidence: 99%

Section: Economic Indicators and Evaluation Tools For Sustainabilitymentioning

confidence: 99%

Emergency Response Cyber-Physical Framework for Landslide Avoidance with Sustainable Electronics †

et al. 2018

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“…Landslides are among the most devastating natural disasters. Worldwide, they cause billions of dollars in property damage and thousands of deaths every year (Hong et al 2007). Nearly 15% of the Indian land area is prone to landslide hazard (GSI, http://www.portal.gsi.gov.in).…”

Section: Introductionmentioning

confidence: 99%

Selection of weightages for causative factors used in preparation of landslide susceptibility zonation (LSZ)

Gupta

Shukla

Thakur

2018

Geomatics, Natural Hazards and Risk

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Most of the models for landslide susceptibility zonation (LSZ) except machine learning needs manual selection of weights or ratings, which are given by expertise knowledge, leading to subjectivity and specificity. Hence, selection of ratings is very important in the preparation of LSZ maps. Here, seven layers/factors viz. aspect, elevation, geology, slope, soil, distance from stream, distance from thrusts are considered for LSZ mapping in Mandakini River basin, Uttarakhand containing 1,805,636 pixels. The weights were calculated using information value (InfoVal) method. The occurrences of landslides (2009 pixels) until 2008 were considered for training of model. Thus for giving rating to each thematic layer, 7! = 5040 permutations (ratings) are possible. Hence, 5040 LSZ maps were prepared and out of them, the best rating was identified using fisher discriminant analysis (FDA) and binary logistic regression (LR). FDA and LR gave similar ratings and the correlation (r 2 ) between their weights was 0.9226. Thematic layers were then multiplied by the corresponding ratings and added to prepare the final LSZ map. The results were validated on the landslide data until 2011, which were not used for training. Out of 223 occurrences of landslides, 39% (87) falls in high susceptible zone followed by 35% (79) in very high susceptible zone according to FDA and similar for LR. The accuracy of the prediction was assessed by Heidke-Skill-Score, which gave score of 0.89 to FDA and 0.90 to LR for 0.5 as threshold of landslide susceptibility index.

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“…thousands of squared kilometres), the computational load required and the difficulty in assessing the spatial organization of geotechnical parameters prevent the application of physically based models (Baum et al, 2010;Agostini et al, 2014;Rossi et al, 2013). As a consequence, when the area of study is a large district or region, the approach used is frequently based on statistical landslide models relying on rainfall exceedance (Larsen and Simon, 1993;Farahmand and AghaKouchak, 2013;Hong et al, 2006Hong et al, , 2007Bovolo and Bathurst, 2012;Segoni et al, 2014a). In particular, empirical rainfall thresholds are frequently used in operational warning systems (Brunsden, 1973;Aleotti, 2004;Hong et al, 2005;Tiranti and Rabuffetti, 2010;Cannon et al, 2011;Martelloni et al, 2012;.…”

Section: Introductionmentioning

confidence: 99%

Analysing the relationship between rainfalls and landslides to define a mosaic of triggering thresholds for regional-scale warning systems

Segoni

Rosi

Rossi

et al. 2014

Nat. Hazards Earth Syst. Sci.

102

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Abstract.We propose an original approach to develop rainfall thresholds to be used in civil protection warning systems for the occurrence of landslides at regional scale (i.e. tens of thousands of kilometres), and we apply it to Tuscany, Italy (23 000 km 2 ).Purpose-developed software is used to define statistical intensity-duration rainfall thresholds by means of an automated and standardized analysis of rainfall data. The automation and standardization of the analysis brings several advantages that in turn have a positive impact on the applicability of the thresholds to operational warning systems. Moreover, the possibility of defining a threshold in very short times compared to traditional analyses allowed us to subdivide the study area into several alert zones to be analysed independently, with the aim of setting up a specific threshold for each of them. As a consequence, a mosaic of several local rainfall thresholds is set up in place of a single regional threshold. Even if pertaining to the same region, the local thresholds vary substantially and can have very different equations. We subsequently analysed how the physical features of the test area influence the parameters and the equations of the local thresholds, and found that some threshold parameters can be put in relation with the prevailing lithology. In addition, we investigated the possible relations between effectiveness of the threshold and number of landslides used for the calibration.A validation procedure and a quantitative comparison with some literature thresholds showed that the performance of a threshold can be increased if the areal extent of its test area is reduced, as long as a statistically significant landslide sample is present. In particular, we demonstrated that the effectiveness of a warning system can be significantly enhanced if a mosaic of site-specific thresholds is used instead of a single regional threshold.

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Satellite remote sensing for global landslide monitoring

Cited by 41 publications

References 16 publications

Emergency Response Cyber-Physical Framework for Landslide Avoidance with Sustainable Electronics †

Emergency Response Cyber-Physical Framework for Landslide Avoidance with Sustainable Electronics †

Selection of weightages for causative factors used in preparation of landslide susceptibility zonation (LSZ)

Analysing the relationship between rainfalls and landslides to define a mosaic of triggering thresholds for regional-scale warning systems

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