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Natural Hazards
Journal Prestige (SJR): 0.767
Citation Impact (citeScore): 2
Number of Followers: 280  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1573-0840 - ISSN (Online) 0921-030X
Published by Springer-Verlag Homepage  [2351 journals]
  • Drought forecasting through statistical models using standardised
           precipitation index: a systematic review and meta-regression analysis
    • Abstract: Quality and reliable drought prediction is essential for mitigation strategies and planning in disaster-stricken regions globally. Prediction models such as empirical or data-driven models play a fundamental role in forecasting drought. However, selecting a suitable prediction model remains a challenge because of the lack of succinct information available on model performance. Therefore, this review evaluated the best model for drought forecasting and determined which differences if any were present in model performance using standardised precipitation index (SPI). In addition, the most effective combination of the SPI with its respective timescale and lead time was investigated. The effectiveness of data-driven models was analysed using meta-regression analysis by applying a linear mixed model to the coefficient of determination and the root mean square error of the validated model results. Wavelet-transformed neural networks had superior performance with the highest correlation and minimum error. Preprocessing data to eliminate non-stationarity performed substantially better than did the regular artificial neural network (ANN) model. Additionally, the best timescale to calculate the SPI was 24 and 12 months and a lead time of 1–3 months provided the most accurate forecasts. Studies from China and Sicily had the most variation based on geographical location as a random effect; while studies from India rendered consistent results overall. Variation in the result can be attributed to geographical differences, seasonal influence, incorporation of climate indices and author bias. Conclusively, this review recommends use of the wavelet-based ANN (WANN) model to forecast drought indices.
      PubDate: 2019-07-16
       
  • Monitoring and analysis of geological hazards in Three Gorges area based
           on load impact change
    • Abstract: Geological hazard monitoring is essential to the prevention and control of geological hazards, yet conventional monitoring is often conducted for local geological hazards, and the relation between monitored results and geological hazards remains poorly understood. In this study, a regional load deformation field model was constructed using data from 26 Continuously Operating Reference Stations (CORS) and 8 gravity stations in the Three Gorges area. The relation between load-induced changes and geological hazards, as the regular characteristics (RCS) in this paper, is obtained by comparing the geological hazards with the impact of the total load change in the whole region of the Three Gorges area and the entire process from 2011 to the beginning of 2015. Geological hazards are more prone to occurring when there are one or more RCS, especially abnormal dynamic environment appears at the same time, such as solid high tide and heavy rainfall. The RCS included the ground geodesy height change rate increasing, the ground gravity change rate decreasing, the ground vertical deviation diverging, the ground geodesy height gradient growing larger and the ground gravity gradient growing larger. Using all of the 18 geological hazards from May to July 2013 to verify the RCS, it was found that the comprehensive observations of CORS and gravity stations can effectively monitor the RCS of the load-induced changes. The results of this study provide more insights associated with the geological hazards monitoring and analysis methods as well as effective support for geological hazard forecasting.
      PubDate: 2019-07-15
       
  • Perceptions of earthquake emergency response and rescue in China: a
           comparison between experts and local practitioners
    • Abstract: By using a questionnaire survey and performing a case study in the Yushu Tibetan Autonomous Prefecture, this study examined the similarities and differences between the perceptions of local practitioners and the perceptions of experts regarding the priority of the factors affecting earthquake emergency response and rescue at the county level in China. The results show that the perceptions of the most and the least important factors are similar between the two groups, except for the factors that affect special abilities. However, one first-level factor, i.e., environmental conditions, and 16 second-level factors, e.g., influence of ethnic cultures, professional rescue teams, GDP level and historical earthquake disaster experience, significantly differed. The local realities of the natural geography, socioeconomic conditions (e.g., economic level, education and ethnic), earthquake experiences and knowledge form the perception of local practitioners, whereas the experts’ perceptions are more consistent with their social role, emergency experiences and knowledge, especially in disaster-prone areas, influencing the differences between the two groups. Suggestions regarding the incorporation local perceptions into the development of local emergency capabilities rather than merely following the perception of experts are discussed.
      PubDate: 2019-07-13
       
  • Damages observed in locations of Oaxaca due to the Tehuantepec Mw8.2
           earthquake, Mexico
    • Abstract: On September 7, 2017, at 23:49 h (local time), a Mw8.2 intermediate-depth normal-fault earthquake occurred in the Gulf of Tehuantepec, 133 km away from Pijijiapan, Chiapas, and about 700 km away from Mexico City. This event caused 95 fatalities and severe damage to different types of structures located close to the epicenter. The main objective of this work is to present observed damages caused in the state of Oaxaca by this earthquake, which were mainly concentrated in self-built houses and historical and ancient buildings. The locations visited by the reconnaissance team of the Institute of Engineering from UNAM in Oaxaca included Salina Cruz, Tehuantepec, Ixtaltepec, Juchitán, Huatulco and La Ventosa.
      PubDate: 2019-07-13
       
  • Torrential rainfall-triggered shallow landslide characteristics and
           susceptibility assessment using ensemble data-driven models in the
           Dongjiang Reservoir Watershed, China
    • Abstract: This study investigated the characteristics of rainfall-triggered landslides during the Typhoon Bilis in the Dongjiang Reservoir Watershed, China. The comparative shallow landslide susceptibility mappings (LSMs) were produced by the ensemble data-driven statistical models in a GIS environment. At first, the landslide inventory for the study area was prepared from the high-resolution QuickBird images, and China–Brazil Earth Resources Satellite images, and field survey. Other necessary data for landslide susceptibility analysis such as the amount of rainfall, geology, and topography were also collected from the respective agencies. Twelve predisposing factors were then prepared using this available dataset. To reduce the subjectivity of models and caution in the selection of predisposing factors, and to avoid the spatial autocorrelation redundancy, certainty factor approach was attempted to optimize these twelve set of parameters. For validating the accuracy of the model, the original landslide data were randomly divided into two parts: 70% (1545 landslides) for training the model and the remaining 30% (662 landslides) for validation. The verified results showed that using the optimized predisposing factors has a higher performance than using all the original twelve factors. The results of ensemble models also showed that LSM maps prepared using binary logistic regression (accuracy is 0.848) model are more accurate than those prepared using bivariate statistical analysis (accuracy is 0.837) model. Additionally, our analysis concludes that the short duration and high-intensity rainfall, drainage density, lithology, and curvature are the major influencing factors for landslide occurrences in this case study area. This research provides an improved understanding of the mechanism of landslides caused by the typhoons for the adjoining watersheds nearby the reservoir. The preliminary understandings and approach could also be applied in similar geological and rainfall-triggered case study sites in the other parts of the world for risk mitigation.
      PubDate: 2019-07-10
       
  • Estimation of ground response and local site effects for Vishakhapatnam,
           India
    • Abstract: Ground motion intensity due to an earthquake changes as it disseminates through the soil media from bedrock to the surface. As the ground motion intensity and damage levels mainly depend upon the local site conditions, it is mandatory to carry out the detailed site-specific hazard studies to assure safety of the structure against seismic risk. In this research paper, an effort has been made to estimate seismic hazard associated with the city of Vishakhapatnam. The city lies in east coast region of southern India and falls under seismic zone II (IS 1893-2016 in Criteria for earthquake-resistant design of structures: part 1—general provisions and buildings, Bureau of Indian Standards, New Delhi, 2016). Seismic activity in the Eastern Ghats mobile belt region has increased due to subduction of Burma plate toward the Bay of Bengal, which resulted in activation of inactive faults and new fault development in the region. Therefore, increasing seismic risk and importance of the study area has motivated the researchers to carry out probabilistic seismic hazard assessment and estimation of local site effects using ground response analysis and microtremor testing. From the results, hazard maps were generated in terms of peak ground acceleration (surface, bedrock level), H/V frequency and H/V amplitude. The seismic hazard parameters, uniform hazard response spectrum and hazards curves from probabilistic seismic hazard assessment are further useful in design and construction of prominent structures. The peak ground acceleration at surface and bedrock, predominant frequency and H/V amplitude indicate the variation in local site conditions and will be of great help in seismic design of structures as well as retrofitting of the existing structures to withstand against seismic hazards. Hazard maps from the study will be helpful in further seismic microzonation studies and also identifying zones of potential seismic risk.
      PubDate: 2019-07-10
       
  • Urban flood vulnerability assessments: the case of Dire Dawa city,
           Ethiopia
    • Abstract: Dire Dawa city is identified as one of the most flood-affected cities in Ethiopia. Classifying village-level flood vulnerability using flood indicators is a new approach to Dire Dawa city. Analysis of different flood vulnerability factors underpins sustainable flood risk management and the application of Flood Vulnerability Index (FVI) approach is the hub of this study. Relevant data were collected from 110 households sampled from purposely selected 10 villages found in Dire Dawa city. The flood vulnerability index was used to compare, classify and rank villages in terms of their flood vulnerability levels. For this purpose, 24 sets of indicators which are strongly affecting the levels of flood vulnerability were assessed from social, economic and physical perspectives. The FVI of each village was computed with unequal method of weighting indicators. The findings of the study revealed that Dire Dawa city villages were experiencing varying levels of flood vulnerability. Accordingly, villages 05, 06, 07 and 09 were identified with high flood vulnerability level while villages 03, 04 and 08 and villages 01, 02 and extension village were identified with medium and low level of vulnerability, respectively. Interestingly, the findings of the study confirmed that social factors contributed much for flood vulnerability in Dire Dawa city. Hence, future urban flood risk planning and management endeavors in the city of Dire Dawa must be underpinned by proper utilization of the flood vulnerability map developed addressing social vulnerability component through both structural and non-structural urban flood risk management measures.
      PubDate: 2019-07-09
       
  • Climate impacts: temperature and electricity consumption
    • Abstract: One of the aspects of climate change is temperature rise. Temperature rise or fluctuations affect human economic activities and electricity consumption. This paper estimates the changes in electricity consumption due to temperature fluctuation at the county scale in rural China. By using the statistics of counties from 2006 to 2015 in a fixed-effect panel model, the results indicate that a one-degree temperature increase in summer days may lead to 0.015% more electricity consumption per capita, and this correlation may be weaker as income increases. Moreover, a one-degree temperature decrease in winter days may lead to 0.002% more electricity consumption. The northern region may consume 0.021% more electricity than the southern region when facing the same temperature drop. Overall, the effect of temperature on electricity consumption is modest, particularly for a drop in temperature, but the usage of other types of energy may increase to adapt to the cold.
      PubDate: 2019-07-08
       
  • Application of 1D and 2D hydrodynamic modeling to study glacial lake
           outburst flood (GLOF) and its impact on a hydropower station in Central
           Himalaya
    • Abstract: The existence of numerous lakes in the higher reaches of the Himalaya makes it a potential natural hazard as it imposes a risk of glacial lake outburst flood (GLOF), which can cause great loss of life and infrastructure in the downstream regions. Hydrodynamic modeling of a natural earth-dam failure and hydraulic routing of the breach hydrograph allow us to characterize the flow behavior of a potential flood along a given flow channel. In the present study, the flow hydraulics of a potential GLOF generated due to the moraine failure of the Satopanth lake located in the Alaknanda basin is analyzed using one-dimensional and two-dimensional hydrodynamic computations. Field measurements and mapping were carried out at the lake site and along the valley using high-resolution DGPS points. The parameters of Manning’s roughness coefficient and terrain elevation were derived using satellite-based raster, the accuracy of which is verified using field data. The volume of the lake is calculated using area-based scaling method. Unsteady flood routing of the dam-break outflow hydrograph is performed along the flow channel to compute hydraulic parameters of peak discharge, water depth, flow velocity, inundation and stream power at a hydropower dam site located 28 km downstream of the lake. Assuming the potential GLOF event occurs contemporaneously with a 100-year return period flood, unsteady hydraulic routing of the combined flood discharge is performed to evaluate its impact on the hydropower dam. The potential GLOF resulted in a peak discharge of ~ 2600 m3s−1 at the dam site which arrived 38 min after the initiation of the moraine-failure event. The temporal characteristics of the flood wave analyzed using 2D unsteady simulations revealed maximum inundation depth and flow velocity of 7.12 m and 7.6 ms−1, respectively, at the dam site. Assuming that the control gates of the dam remain closed, water depth increases at a rate of 4.5 m per minute and overflows the dam approximately 4 min after the flood wave arrival.
      PubDate: 2019-07-06
       
  • Characterizing the spatial distribution of typical natural disaster
           vulnerability in China from 2010 to 2017
    • Abstract: Natural disaster vulnerability can intuitively reflect the susceptibility of an area to environmental changes. Better understanding the spatial distribution of natural disaster vulnerability is a critical process for taking effective adaptation and management. Although significant achievements have been made in disaster vulnerability, few studies are known about natural disaster vulnerability at the national scale, especially from the typical natural disaster events in China. In this study, with normalizing selected indicators and calculating vulnerability index, we analyzed the spatial distribution of natural disasters vulnerability during 2010–2017 using the geospatial techniques. The results showed that natural disaster vulnerability has certain spatial differences, but different natural disaster can occur in the same area during the study period. Drought disaster can occur in all regions of China, especially in Inner Mongolia. Flood disaster is mainly concentrated in the middle and lower reaches of the Yangtze River and the Yellow River Basin. The wind and storm disaster is chiefly in the northern regions in China. The freezing disaster is widely distributed in China. Furthermore, the regions with low vulnerability were primarily distributed in the eastern coastal region, indicating that the rapid development of economy and technology can resist or mitigate natural disaster to a certain extent. This study offers a solution to study natural disasters and provides scientific basis for disaster prevention and mitigation actions.
      PubDate: 2019-07-05
       
  • A methodology for urban micro-scale coastal flood vulnerability and risk
           assessment and mapping
    • Abstract: One of the most dangerous challenges to settlements in the UK comes from flooding. Currently, there is extensive map coverage of flood hazards zones in the UK; however, it is increasingly recognised that risk associated with natural hazards cannot be reduced solely by focussing on the hazard. There is also an urgent need for methods of evaluating and mapping flood vulnerability and risk in detail. Despite its significance, conventional flood risk assessment methodologies often underestimate likely levels of vulnerability in areas prone to hazards, yet it is the degree of vulnerability within a community that determines the consequences of any given hazard. The research presented proposes a general methodology to assess and map Coastal Flood Vulnerability and Risk at a detailed, micro-scale level. This captures aspects that are considered crucial and representative of reality (socio-economic, physical and resilient features). The methodology is then applied to a UK case study (city of Portsmouth). Environment Agency flood hazard data, National Census socio-economic data and Ordnance Survey topographic map data have been used to evaluate and map coastal flood vulnerability, examining neighbourhoods within census wards. This led to a subsequent analysis of Coastal Flood Risk, via the combination of a Coastal Flood Vulnerability Index and a Coastal Flood Hazard Index, for the Portsmouth ward Hilsea. This, consequently, identifies potential weaknesses that could lead to more effective targeting of interventions to improve resilience and reduce vulnerability in the long term and provides a basis for hazard and environmental managers/planners to generate comprehensive national/international vulnerability and risk assessments.
      PubDate: 2019-07-04
       
  • A large wet snow avalanche cycle in West Greenland quantified using remote
           sensing and in situ observations
    • Abstract: On 11 April 2016 we observed high slushflow and wet snow avalanche activity at the environmental monitoring station Kobbefjord in W-Greenland. Snow avalanches released as a result of snow wetting induced by rain-on-snow in combination with a strong rise in air temperature. We exploit high-resolution satellite imagery covering pre- and post-event conditions for avalanche quantification and show that nearly 800 avalanches were triggered during this cycle. The nature of this extraordinary event is put into a longer temporal context by analysing several years of meteorological data and time-lapse imagery. We find that no event of similar size has occurred during the past 10 years of intense environmental monitoring in the study area. Meteorological reanalysis data reveal consistent relevant weather patterns for potential rain-on-snow events in the study area being warm fronts from Southwest with orographic lifting processes that triggered heavy precipitation.
      PubDate: 2019-07-04
       
  • Differentiation and integration: off-site resettlement planning practice
           in New Beichuan after 5.12 Wenchuan Earthquake
    • Abstract: This article explores the spatial differentiation and integration between the post-disaster victims and the indigenous peasants 8 years after a rapid off-site resettlement oriented by governments in New Beichuan. Data were broadly collected from placement documents, questionnaires, interviews and site measurement by empirical research and on-site investigation in 2014. The resettlement plan was introduced and analyzed for housing resettlement, open space systems, public facilities allocation and resettlement policies. Based on statistical analysis of the questionnaire data and observation on the usage of the built environment, problems with the spatial usage and mismatches between the specific spatial requirements and subjective planning intention of integration are analyzed and preliminary findings are shown. The results showed that the excessive pursuit of speed and deficiency in economically self-sustaining efforts might contribute to insufficient attention given to spatial, social and economic aspects and leads to inevitable and long-standing problems, such as housing quality problems, neighborhoods management and security concerns, contradictions between the housing layout and local living habits, different spatial usage preferences between the indigenous peasants and post-disaster migrants, and disequilibrium of public facility allocation.
      PubDate: 2019-07-02
       
  • Tsunami risk perception along the Tyrrhenian coasts of Southern Italy: the
           case of Marsili volcano
    • Abstract: The Marsili volcano is the largest known seamount in Europe, located in the Marsili Basin (Aeolian Arc, Tyrrhenian Sea, Italy). The Marsili seamount shows a high probability to generate a volcanogenic tsunami in the near future, and the coasts of Southern Italy could be affected by this event. We conducted a qualitative risk perception analysis by distributing a questionnaire at the population from three different regions that are surrounded by the Tyrrhenian Sea. Data from questionnaires were analyzed in order to understand the tsunami risk perception of the population. Our data were compared with a probabilistic tsunami scenario due to a Marsili seamount flank collapse. Results underlined the need for a proposed campaign that aimed at informing the Southern Italy population about tsunami risk and the phenomena that can potentially generate a tsunami event.
      PubDate: 2019-07-02
       
  • Land subsidence (2004–2013) in Changzhou in Central Yangtze River
           delta revealed by MT-InSAR
    • Abstract: Land subsidence in Changzhou City in the central Yangtze River Delta of China poses a serious threat to the safety of the environment and infrastructures. Excessive groundwater withdrawal, rapid urbanisation and industrial activities contribute to land subsidence in this area. In this study, we used the multi-temporal InSAR (MT-InSAR) technique to describe the spatiotemporal characteristics of land subsidence in Changzhou. Twenty-five ENVISAT ASAR and 29 TerraSAR-X images acquired from 2004 to 2013 were used to determine the rate and temporal evolution of land subsidence. We used the ERA-Interim model instead of spatiotemporal filtering in traditional MT-InSAR to mitigate the atmospheric phase screen. The InSAR-derived results were evaluated by comparing data from three time series methods and different bands (C and X bands), and accuracy was validated through levelling surveys and GPS measurements. For three regions, a distinct subsidence pattern was observed in major industrial areas with a maximum subsidence rate of up to − 39.9 mm/year. We also characterised the spatiotemporal variations of land subsidence in major industrial areas in Changzhou. The deformation of large-scale man-made linear features, namely high-speed railways, highway networks and a bridge, was analysed. The spatiotemporal characteristics and possible reasons for the observed subsidence were discussed to provide a reference for future urban development planning in Changzhou.
      PubDate: 2019-07-01
       
  • Grey- and rough-set-based seasonal disaster predictions: an analysis of
           flood data in India
    • Abstract: In a globally competitive market, companies attempt to foresee the occurrences of any catastrophe that may cause disruptions in their supply chains. Indian subcontinent is prone to frequent disasters related to floods and cyclones. It is essential for any supply chain operating in India to predict the occurrence of any such disasters. By doing so, the disaster management and the relief teams can prepare for the worst. This research makes use of a grey seasonal disaster prediction model to forecast the possible occurrence of any flood-related disasters in India. Flood data of major flood occurrences for a period of 10 years (2007–2017) have been taken for analysis in this context. We have established a grey model of the first order and with one variable, GM (1, 1), for prediction; from the results, we observe there are high chances of occurrence of a flood-related disaster in India during the early monsoon period (June–August), in both 2018 and 2020. By observing the prediction sequences on fatalities, there is likelihood that the death toll may rise above 100 and the flood can result in disastrous consequences. Also, the results of prediction are compared using an enhanced rough-set-based prediction model. From the results of rough-set-based prediction model, there are chances of a severe flood in mid-2018 in India. The results will be useful for organizations, NGOs and State Governments to carefully plan their supply and logistics network in the event of disasters. Graphic abstract Proposed methodology of grey seasonal disaster prediction for floods.
      PubDate: 2019-06-29
       
  • Satellite-based analysis of the┬áspatial patterns of fire- and
           storm-related forest disturbances in the Ural region, Russia
    • Abstract: Large-scale wildfires and windstorms are the most important disturbance agents for the Russian boreal forests. The paper presents an assessment of fire-related and wind-induced forest losses in the Ural region of Russia for 2000‒2014. The assessment is based on the use of Landsat images, Global Forest Change dataset (Hansen et al. in Science 342:850–853, 2013. https://doi.org/10.1126/science.1244693) and other space imagery data. The total area of stand-replacement fires and windthrows in the Ural’s forests was estimated at 1.637 million ha, which is 1.56% of the total forest-covered area. The contribution of wildfires and windthrows is 96.4% and 3.6%, respectively. The highest frequency of large-scale wildfires was observed behind the Northern Ural ridge, where the fire scars of 2000‒2014 covered 10–14% of the forested area. The storm-related forest damage is significant only on the western part of the Ural. A few catastrophic wildfires and windthrows (with an area > 5000 ha) make up 35% of the entire damaged area. The number of wildfires, windthrows and their damaged area vary significantly from year to year. For 2000–2014, it is impossible to find a statistically significant trend of the fire- and storm-damaged area. The seasonal maximum of large-scale wildfires and windthrows was observed in July. Also, we identified the statistically significant relationships of fire- and wind-related forest damage with environmental variables. The occurrence of large-scale wildfires is related mainly to the species composition of forests, and also to the altitude, the mean annual precipitation and the population density. The spatial distribution of massive windthrows has a strong correlation with the species composition of forests, the mean annual precipitation and partially with the wind effect parameter.
      PubDate: 2019-06-26
       
  • The role of complex terrain in the generation of tornadoes in the west of
           Mexico
    • Abstract: Tornadoes are extreme manifestations of severe storms that occur around the world. In Mexico, the most affected region by the tornado phenomenon is the Trans-Mexican Volcanic Belt (TMVB), a complex topographic region in the central part of the country with a large population density. This research work aims to investigate the role of the complex topography in the generation of instability conditions that favored the formation of two tornadoes almost in the same place (western TMVB) on August 7, 2012, and September 16, 2014. Numerical experiments with the WRF-ARW model were performed in order to obtain knowledge about several important weather conditions preceding each tornado event and to identify the role of the complex terrain in the generation of instability necessary for their formation. Notwithstanding this real complexity, similar patterns in instability parameters and meteorological variables were found for the two tornadoes. The complex terrain seems to be essential in the generation and increase in instability preceding each tornado event. This work is the first approach to understand the meteorological phenomena, in the complex topography of Mexico, which leads to the formation of tornadoes. Understanding natural hazards such as tornadoes represents a first phase in the process of disaster risk reduction.
      PubDate: 2019-06-25
       
  • Nonstationary joint probability analysis of extreme marine variables to
           assess design water levels at the shoreline in a changing climate
    • Abstract: In the present study, a recently developed novel approach (Bender et al. in J Hydrol 514:123–130, 2014) has been further extended to investigate the changes in the joint probabilities of extreme offshore and nearshore marine variables with time and to assess design the total water level (TWL) at the shoreline under the effects of climate change. The nonstationary generalised extreme value (GEV) distribution has been utilised to model the marginal distribution functions of marine variables (wave characteristics and sea levels), within a 40-year moving window. All parameters of the GEV were tested for statistically significant linear and polynomial trends over time, and best-fitted trends have been detected. Different copula functions were fitted at the 40-year moving windows, to model the dependence structure of extreme offshore significant wave heights and peak spectral periods, and of wave-induced sea levels on the shoreline and nearshore sea levels due to storm surges. The most appropriate bivariate models were then selected. Statistically significant polynomial trends were detected in the dependence parameters of the selected copulas, and time-dependent most likely bivariate events were extracted to be used in the estimation of the TWL at the shoreline. The methods of the present work were implemented in three selected Greek coastal areas in the Aegean Sea. The analysis revealed different variations in the most likely estimates of the offshore wave characteristics and nearshore storm surges in the three study areas, as well as in the time-dependent estimates of TWL at the shoreline. The approach combines nonstationarity and bivariate analysis, blends coastal and offshore marine features and finally provides non-trivial alterations in the response of coastal sea level dynamics to climate change signals, compared to former work on the subject. The methodology produces reasonable estimates of design quantities for coastal structures and boundary conditions for the assessment of flood hazard and risk in coastal areas.
      PubDate: 2019-06-24
       
  • An application of InSAR time-series analysis for the assessment of
           mining-induced structural damage in Panji Mine, China
    • Abstract: Underground coal mining activities are likely to cause changes in surface structure, resulting in damage to buildings, which seriously threaten the safety of life and property of the residents within the mining area. In this paper, the synthetic aperture radar time-series analysis method is combined with the building damage level empirical model to conduct a health assessment of the residential buildings in the Panji mining area of Huainan. Through the processing of 50 Sentinel-1A satellite radar images from April 2015 to May 2018, it is indicated that the residential areas in Huainan Panji Mining Area continued to be affected by underground coal mining during this period, and severe settlement occurred. Large areas of buildings in residential areas were damaged. Until May 2018, 202,000 m2 of buildings in the residential area of Panji mining have reached the Class II damage and 41,575 m2 have reached the Class III damage. After field investigation, the actual damage situation of the building is in good agreement with the results of this paper. Therefore, synthetic aperture radar time-series analysis combined with building damage level empirical model can be used as an effective tool for rapid and efficient deformation monitoring and health assessment of buildings. It is of great significance for the identification, early warning and disaster prevention decision making of such disasters.
      PubDate: 2019-06-20
       
 
 
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