检索结果-南通市图书馆

Effects of raster resolution on landslide susceptibility mapping:A case study of Shenzhen

在线全文

学校读者我要写书评

暂无评论

Science China(Technological Sciences) 2008年第S2期51卷 188-198页

作者： TIAN Yuan,XIAO ChenChao,LIU Yu & WU Lun Institute of RS and GIS,Peking University,Beijing 100871,China Institute of RS and GIS Peking University Beijing China

Resolution has been playing a significant role in landslide susceptibility mapping and hazard assessment.Based on geographical information system(GIS) and information model,the effects of raster resolution on landslide susceptibility mapping are studied in a central area of Shenzhen,China.Eight factors are selected to calculate landslide susceptibility with eleven groups of different resolutions(5 to 190 m).It has been found that a finer resolution does not necessarily lead to a higher accuracy of landslide susceptibility mappings,while the result of 90 m-resolution has the best accuracy and the 150 m-resolution has the worst one.The accuracy curve is in a shape of "W" along with resolution decreasing:1) The accuracy decreases from 5 to 70 m;2) and then the best accuracy appears at 90 m,which is almost the same as the mean size of landslides in study area;3) the accuracy decreases again from 110 to 150 m;4) and finally the accuracy increases from 150 to 190 m.The sensitivity analysis indicates that the effects of raster resolution are mainly caused by the resolution impact on landform parameter derivation,while factors like geology and human activity are very insensitive to resolutions.A further study shows that in flat,ridge,and slope foot terrains,the susceptibility mapping result is sensitive to resolution,but in the sloping surface area the sensitivity is much less sensitive to resolution.At last,by choosing study areas with different sizes,it has also been found that the optimal resolutions are variable due to size of study area.But the study area is larger than a threshold,which is 135 km2 in this study,and the optimal resolution is almost fixed.

关键词： resolution sensitivity landslide susceptibility mapping digital elevation model(DEM) information model

Evaluating effectiveness of frequency ratio, fuzzy logic and logistic regression models in assessing landslide susceptibility: a case from Rudraprayag district, India

在线全文

学校读者我要写书评

暂无评论

Journal of Mountain Science 2017年第11期14卷 2150-2167页

作者： Mehebub SAHANA Haroon SAJJAD Department of Geography Faculty of Natural Sciences Jamia Millia Islamia

Rudraprayag in Garhwal Himalayan division is one of the most vulnerable districts to landslides in India. Heavy rainfall, steep slope and developmental activities are important factors for the occurrence of landslides in the district. Therefore, specific assessment of landslide susceptibility and its accuracy at regional level is essential for disaster management and proper land use planning. The article evaluates effectiveness of frequency ratio, fuzzy logic and logistic regression models for assessing landslide susceptibility in Rudraprayag district of Uttarakhand state, India. A landslide inventory map was prepared and verified by field data. Fourteen landslide parameters and generated inventory map were utilized to prepare landslide susceptibility maps through frequency ratio, fuzzy logic and logistic regression models. Landslide susceptibility maps generated through these models were classified into very high, high, medium, low and very low categories using natural breaks classification. Receiver operating characteristics(ROC) curve, spatially agreed area approach and seed cell area index(SCAI) method were used to validate the landslide models. Validation results revealed that fuzzy logic model was found to be more effective in assessing landslide susceptibility in the study area. The landslide susceptibility map generated through fuzzy logic model can be best utilized for landslide disaster management and effective land use planning.

关键词： Landslide susceptibility Frequency ratio Logistic regression Natural breaks classification Remote sensing Geographic information system

GIS-based landslide susceptibility mapping using numerical risk factor bivariate model and its ensemble with linear multivariate regression and boosted regression tree algorithms

在线全文

学校读者我要写书评

暂无评论

Journal of Mountain Science 2019年第3期16卷 595-618页

作者： Alireza ARABAMERI Biswajeet PRADHAN Khalil REZAE Masoud SOHRABI Zahra KALANTARI Department of Geomorphology Tarbiat Modares University Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS) Faculty of Engineering and ITUniversity of Technology Sydney Department of Energy and Mineral Resources Engineering Choongmu-gwanSejong University Faculty of Earth Sciences Kharazmi University Department of Civil Engineering- geotechnics Islamic Azad university of Urmia Stockholm University Department of Physical Geography and Bolin Centre for Climate Research

In this study, a novel approach of the landslide numerical risk factor(LNRF) bivariate model was used in ensemble with linear multivariate regression(LMR) and boosted regression tree(BRT) models, coupled with radar remote sensing data and geographic information system(GIS), for landslide susceptibility mapping(LSM) in the Gorganroud watershed, Iran. Fifteen topographic, hydrological, geological and environmental conditioning factors and a landslide inventory(70%, or 298 landslides) were used in mapping. Phased array-type L-band synthetic aperture radar data were used to extract topographic parameters. Coefficients of tolerance and variance inflation factor were used to determine the coherence among conditioning factors. Data for the landslide inventory map were obtained from various resources, such as Iranian Landslide Working Party(ILWP), Forestry, Rangeland and Watershed Organisation(FRWO), extensive field surveys, interpretation of aerial photos and satellite images, and radar data. Of the total data, 30% were used to validate LSMs, using area under the curve(AUC), frequency ratio(FR) and seed cell area index(SCAI).Normalised difference vegetation index, land use/land cover and slope degree in BRT model elevation, rainfall and distance from stream were found to be important factors and were given the highest weightage in modelling. Validation results using AUC showed that the ensemble LNRF-BRT and LNRFLMR models(AUC = 0.912(91.2%) and 0.907(90.7%), respectively) had high predictive accuracy than the LNRF model alone(AUC = 0.855(85.5%)). The FR and SCAI analyses showed that all models divided the parameter classes with high precision. Overall, our novel approach of combining multivariate and machine learning methods with bivariate models, radar remote sensing data and GIS proved to be a powerful tool for landslide susceptibility mapping.

关键词： Landslide susceptibility GIS Remote sensing Bivariate model Multivariate model Machine learning model

A signature for biological heterogeneity in susceptibility to HIV infection?

在线全文

学校读者我要写书评

暂无评论

Infectious Disease Modelling 2018年第1期3卷 139-144页

作者： Nico Nagelkerke Laith JAbu-Raddad Susanne FAwad Vivian Black Brian Williams Department of Public Health Erasmus Medical CenterRotterdamThe Netherlands Infectious Disease Epidemiology Group Weill Cornell Medical College-QatarCornell UniversityQatar Foundation-Education CityDohaQatar Department of Healthcare Policy and Research Weill Cornell Medical CollegeCornell UniversityNew YorkUSA Population Health Research Institute St George'sUniversity of LondonLondonUK Clinical Microbiology and Infectious Diseases Faculty of Health SciencesUniversity of the WitwatersrandSouth Africa Wits Reproductive Health and HIV Institute University of WitwatersrandJohannesburgSouth Africa South African Centre for Epidemiological Modeling and Analysis(SACEMA) StellenboschSouth Africa

Data on female sex workers and sero-discordant couples indicate a pattern of waning of the risk of HIV infection with longer duration of exposure to infected partners.Understanding risk of HIV acquisition and transmission is critical to understanding HIV epidemiology and informing prevention interventions.Informed by empirical data,we aimed to develop a statistical model to explain these observations.In our proposed model,the time to infection for each individual is exponentially distributed,but the marginal(population averaged)distribution of time to infection follows a Weibull distribution with shape parameter of about 0.5,and with the Levy distribution being the mixing distribution.Simulations based on this model demonstrated how HIV epidemics are destined to emerge rapidly,because of the rapid sero-conversion upon exposure,but also simultaneously destined to saturate and decline rapidly after emergence,just as observed for the HIV epidemics in sub-Saharan Africa.These results imply considerable individual variability in infection risk,probably because of biological heterogeneity in the susceptibility to HIV infection.Factoring this variability in mathematical models,through the methodology provided here,could be critical for valid estimations of impact of HIV interventions and assessments of cost-effectiveness.

关键词： HIV Mathematical modeling susceptibility Infection risk Heterogeneity in transmission

Integrating the Analytical Hierarchy Process(AHP) and the Frequency Ratio(FR) Model in Landslide susceptibility Mapping of Shiv-khola Watershed,Darjeeling Himalaya

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

International Journal of Disaster Risk Science 2013年第4期4卷 200-212页

作者： Sujit Mondal Ramkrishna Maiti Department of Geography Raja N.L.Khan Women’s CollegePaschim MedinipurWest Bengal721102India Department of Geography and Environment Management Vidyasagar UniversityPaschim MedinipurWest Bengal721102India

To prepare a landslide susceptibility map of Shivkhola watershed,one of the landslide prone parts of Darjeeling Himalaya,remote sensing and GIS tools were used to integrate 10 landslide triggering parameters:lithology,slope angle,slope aspect,slope curvature,drainage density,upslope contributing area(UCA),lineament,settlement density,road contributing area(RCA),and land use and land cover(LULC).The Analytical Hierarchy Process(AHP) was applied to derive factor weights using MATLAB with reasonable consistency ratio(CR).The frequency ratio(FR) model was used to derive class frequency ratio or class weights that indicate the relative importance of individual classes for each factor.The weighted linear combination(WLC) method was used to determine the landslide susceptibility index value(LSIV) on a GIS platform,by incorporating both factor weights and class weights.The Shiv-khola watershed is classified into five landslide susceptibility zones.The overall classification accuracy is 99.22 and Kappa Statistics is 0.894.

关键词： weights susceptibility watershed

Climatic periodicities recorded in lake sediment magnetic susceptibility data:Further evidence for solar forcing on Indian summer monsoon

在线全文

学校读者我要写书评

暂无评论

Geoscience Frontiers 2017年第6期8卷 1349-1355页

作者： Anish Kumar Warrier Kizhur Sandeep Rajasekharaiah Shankar Department of Marine Geology Mangalore UniversityMangalagangotri 574199KarnatakaIndia Department of Civil Engineering Manipal Institute of TechnologyManipal UniversityManipal 576104KarnatakaIndia Department of Geology School of Earth Science SystemsCentral University of KeralaTejaswini HillsPeriye(P.O.)KasaragodKerala 671 123India

The Indian summer monsoon exhibits considerable spatio-temporal variability.It is therefore important to understand its dynamics and the inherent periodicities.In this study,we have performed spectral and wavelet analyses of magnetic susceptibility data for sediments from Thimmannanayakanakere(TK)-a small lake in southern India.The main objective of this investigation is to identify and explain the possible origin of the prominent periodicities present in the magnetic susceptibility data.Significant periodicities in the TK χ_(lf)data are centered at 906,232,147,128,96,61,54 and 44 years,which might have a solar origin.The wavelet power spectrum of the raw and detrended χ_(lf)data confirms the findings of spectral analysis and also provides temporal variations of the significant cyclicities during the past3700 cal.years B.P.Positive correlation is documented between sunspot activity and TK xif data;crossspectral analysis of the reconstructed sunspot data and TK xif data suggest that there is a strong coherence between the two datasets as significant periodicities are documented in both.There is a good match between the TK xif and the reconstructed total solar irradiance data for the past 1200 years.However,an out-of-phase relationship is documented at certain time-intervals,which may be attributed to uncertainties in the age-depth model.The results obtained from this study show that solar variations are the main controlling factor of the southwest monsoon and,like other archives from different regions in India,the TK lake sediments have also recorded these solar signatures.

关键词： Spectral analysis Periodicity Paleorainfall Lake sediments Magnetic susceptibility Southern India

Two pedogenic models for paleoclimatic records of magnetic susceptibility from Chinese and Siberian loess

在线全文

学校读者我要写书评

暂无评论

Science China Earth Sciences 2008年第2期51卷 284-293页

作者： Paul HESSE Jiri CHLACHULA Department of Physical Geography Macquarie University NSW 2109 Australia Key Laboratory of Desert and Desertification Institute of Cold and Arid Regions Environmental and Engineering Chinese Academy of Sciences Lanzhou 730000 China

The magnetic susceptibility (MS) of Chinese loess showing a general proportional relationship to pedogenic grade has been widely recognized and used for reconstruction of paleoclimate by Quaternary scientists. The in-situ pedogenic enhancement of ferrimagnetic content is normally believed to be the main reason for the increase of susceptibility in soil units. However, this pattern of high magnetic susceptibility in palaeosols, and low values in loess, are not replicated in some loess deposits. Siberian loess deposits display a completely opposite susceptibility behavior: high values in loess and low values in palaeosols. This inverse relationship has been explained by the idea that magnetic susceptibility is reflecting the magnitude of an aeolian ferrimagnetic component of consistent mineralogy, the grain size of which is related to average wind velocity. Our magnetic study of Siberian samples in this paper suggests that there are notable differences in magnetic properties between Siberian loess and developed palaeosols, not only in magnetic grain-size and concentration but also in magnetic mineralogy. This evidence is difficult to explain fully through variation in wind strength alone, but implies that the low magnetic susceptibility values in the Siberian paleosol units are a reflection, at least in part, of the alteration of the ferrimagnetic content by post-depositional processes. The Loess Plateau is a very arid area where potential evaporation is always higher than precipitation; pedogenesis occurs under dry oxidising conditions. The Siberian Kurtak region is located on the edge of the tundra where it is always wet and saturation during interglacials will lead to a reducing pedogenic environment. Ferrimagnetic minerals under this condition will be destroyed, resulting in lower magnetic susceptibility. Therefore, great care should be taken when using susceptibility values for paleoclimatic reconstruction.

关键词： Siberian loess Chinese loess paleoclimate magnetic susceptibility magnetic mineralogy environmental magnetism

Effectiveness analysis of the prediction of regional debris flow susceptibility in post-earthquake and drought site

在线全文

学校读者我要写书评

暂无评论

Journal of Mountain Science 2020年第2期17卷 329-339页

作者： CHEN Ning-sheng ZHANG Yong TIAN Shu-feng DENG Ming-feng WANG Tao LIU Li-hong LIU Mei HU Gui-sheng Key of Mountain Hazards and Surface Process Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610041China University of Chinese Academy of Sciences Beijing 100049China

Debris-flow disasters occurred frequently after the Mw 8.0 Wenchuan earthquake on 12 May 2008 in Sichuan Province, China. Based on historical accounts of debris-flow disaster events, it found that debris flow occurrence is closely related to the impact of earthquakes and droughts, because earthquakedrought activities can increase the loose solid materials, which can transform into debris flows under the effect of rainstorms. Based on the analysis of historical earthquake activity(frequency, magnitude and location), drought indexes and the trend of climate change(amount of rainfall), a prediction method was established, and the regional debris flow susceptibility was predicted. Furthermore, in a debris flow-susceptible site, effective warning and monitoring are essential not only from an economicpoint of view but are also considered as a frontline approach to alleviate hazards. The advantages of the prediction and early monitoring include(1) the acquired results being sent to the central government for policy making;(2) lives and property in mountainous areas can be protected, such as the 570 residents in the Aizi valley, who evacuated successfully before debris flows in 2012;(3) guiding the government to identify the areas of disasters and the preparation for disaster prevention and mitigation, such as predicting disasters in high-risk areas in the period 2012-2017, helping the government to recognize the development trend of disasters;(4) the quantitative prediction of regional debris-flow susceptibility, such as after the Wenchuan earthquake, can promote scientific and sustainable development and socioeconomic planning in earthquake-struck areas.

关键词： Regional debris flow susceptibility Prediction model Wenchuan earthquake Drought Southwest China

Landslide integrated characteristics and susceptibility assessment in Rongxian county of Guangxi,China

在线全文

学校读者我要写书评

暂无评论

Journal of Mountain Science 2019年第3期16卷 657-676页

作者： LIAO Li-ping ZHU Ying-yan ZHAO Yan-lin WEN Hai-tao YANG Yun-chuan CHEN Li-hua MA Shao-kun XU Ying-zi College of Civil Engineering and Architecture Guangxi University Key Laboratory of Disaster Prevention and Structural Safety of Ministry of Education Guangxi University Guangxi Key Laboratory of Disaster Prevention and Engineering Safety Guangxi University Key Laboratory of Mountain Hazards and Surface Processes Institute of Mountain Hazards and EnvironmentChinese Academy of Sciences Guangxi Zhuang Autonomous Region Geological Environmental Monitoring Station

Landslides distribute extensively in Rongxian county, the southeast of Guangxi province, China and pose great threats to this county. At present, hazard management strategy is facing an unprecedented challenge due to lack of a landslide susceptibility map. Therefore, the purpose of this paper was to construct a landslide susceptibility map by adopting three widely used models based on an integrated understanding of landslide’s characteristics.These models include a semi-quantitative method(SQM), information value model(IVM) and logistical regression model(LRM).The primary results show that(1) the county is classified into four susceptive regions, named as very low, low, moderate and high, which covered an area of 13.43%, 32.40%, 31.19% and 22.99% in SQM, 0.86%, 26.82%, 44.11%, and 28.21% in IVM, 9.88%, 17.73%, 46.36% and 26.03% in LRM;(2) landslides are likely to occur within the areas characterized by following obvious aspects: high intensity of human activities, slope angles of 25°～35°, the thickness of weathered soil is larger than 15 m; the lithology is granite, shale and mud rock;(3) the area under the curve of SQM, IVM and LRM is 0.7151, 0.7688 and 0.7362 respectively, and the corresponding success rate is 71.51%, 76.88% and 73.62%. It is concluded that these three models are acceptable because they have an effective capability of susceptibility assessment and can achieve an expected accuracy. In addition, the susceptibility outcome obtained from IVM provides a slightly higher quality than that from SQM, LRM.

关键词： Landslide characteristic susceptibility zonation Prevention regionalization Rongxian county