Landslide susceptibility mapping using machine learning algorithms and comparison of their performance at Abha Basin,Asir Region,Saudi Arabia     

Ahmed Mohamed Youssef  Hamid Reza Pourghasemi 《地学前缘(英文版)》2021,12(2):639-655

The current study aimed at evaluating the capabilities of seven advanced machine learning techniques(MLTs),including,Support Vector Machine(SVM),Random Forest(RF),Multivariate Adaptive Regression Spline(MARS),Artificial Neural Network(ANN),Quadratic Discriminant Analysis(QDA),Linear Discriminant Analysis(LDA),and Naive Bayes(NB),for landslide susceptibility modeling and comparison of their performances.Coupling machine learning algorithms with spatial data types for landslide susceptibility mapping is a vitally important issue.This study was carried out using GIS and R open source software at Abha Basin,Asir Region,Saudi Arabia.First,a total of 243 landslide locations were identified at Abha Basin to prepare the landslide inventory map using different data sources.All the landslide areas were randomly separated into two groups with a ratio of 70%for training and 30%for validating purposes.Twelve landslide-variables were generated for landslide susceptibility modeling,which include altitude,lithology,distance to faults,normalized difference vegetation index(NDVI),landuse/landcover(LULC),distance to roads,slope angle,distance to streams,profile curvature,plan curvature,slope length(LS),and slope-aspect.The area under curve(AUC-ROC)approach has been applied to evaluate,validate,and compare the MLTs performance.The results indicated that AUC values for seven MLTs range from 89.0%for QDA to 95.1%for RF.Our findings showed that the RF(AUC=95.1%)and LDA(AUC=941.7%)have produced the best performances in comparison to other MLTs.The outcome of this study and the landslide susceptibility maps would be useful for environmental protection.  相似文献   

Using high-resolution satellite imagery to provide a relief priority map after earthquake     

Hamid Reza Ranjbar  Alireza A. Ardalan  Hamid Dehghani  Mohammad Reza Saradjian 《Natural Hazards》2018,90(3):1087-1113

After the earthquake occurrence, collecting correct information about the extent of damage is essential for managing critical conditions and allocating limited resources. The prepared building damage maps sometimes bring about waste of time required for rescuing individuals under the rubble by wrongly conducting rescue teams toward regions with a lower rescue priority. In this research, an algorithm based on using a proposed standard at database level was developed to prioritize damaged buildings by considering five key elements of land use type, the degree of damage to buildings, the land use differentiation index, time of the highest population density in each land use, and time of disaster’s incidence. The steps of the proposed method which was implemented in the MATLAB environment include: detecting buildings on the pre- and post-event imagery, implementing texture features for each candidate building, choosing the optimal features by genetic algorithm, determining the degree of building damage in three classes of negligible damage, substantial damage, and heavy damage by using the difference between chosen features as inputs of the designed neurofuzzy inference system. Data collected from field observations were compared to the output obtained from the proposed algorithm. This comparison presented a general accuracy of 88% and Kappa coefficient of 79% in the classification of buildings into three damage classes. The proposed standard then was used for classifying damaged buildings into relief priorities of high, medium, and low. Findings revealed that the relief priority map could be a basis for correct guidance of relief and rescue teams during crucial times following earthquakes.  相似文献   

Pressuremeter Modulus and Limit Pressure of Clayey Soils Using <Emphasis Type="Italic">GMDH</Emphasis>-Type Neural Network and Genetic Algorithms     

Reza Ziaie Moayed  Afshin Kordnaeij  Hossein Mola-Abasi 《Geotechnical and Geological Engineering》2018,36(1):165-178

Pressuremeter modulus (\(E_{M}\)) and limit pressure (\(P_{L}\)) are used for the calculation of the settlement and bearing capacity of foundation respectively. As the determination of these parameters from pressuremeter test (PMT) is relatively time-consuming and expensive, various empirical correlations have been proposed to correlate the \(E_{M}\) and \(P_{L}\) to other soil parameters. For the existing equations are incapable of estimating these PMT parameters well, in present research group method of data handling type neural network is used to estimate the \(E_{M}\) and \(P_{L}\) of clayey soils. The \(E_{M}\) and \(P_{L}\) were modeled as a function of three variables including the moisture content (\(\omega\)), plasticity index and corrected SPT blow counts (\(N_{60}\)). A database containing 51 data sets have been used for training and testing of the models. The performances of proposed models are compared with those of existing empirical equations. The results demonstrate that appreciable improvement with respect to the other correlations has been achieved. At the end, sensitivity analysis of the obtained models has been performed to study the influence of input parameters on model outputs and shows that the \(N_{60}\) is the most influential parameter on the PMT parameters.  相似文献   

A hybrid clustering-fusion methodology for land subsidence estimation     

Taravatrooy  Narges  Nikoo  Mohammad Reza  Sadegh  Mojtaba  Parvinnia  Mohammad 《Natural Hazards》2018,93(2):905-920

In many parts of Canada, limited data are available for hydrodynamic model inputs, and the ability to generate quality flood grids through 1D, 2D or 3D methods is nonviable. In this paper, the capability of simplified flood models, which rely solely on digital terrain models (DTMs), was explored to assess the quality and speed of their results. Results were validated against historic floods in two locations. Three non-physics-based simplified conceptual flood models were tested: (1) planar method, (2) inclined plane and (3) height above nearest drainage network (HAND) model. The accuracy and performance were evaluated using three criteria: inundation extent, water depth and computation time. Findings show that the HAND model is the best predictor of inundation extent, with Probability of Detection and Critical Success Index being higher than 0.90 in both study areas. Though the preprocessing time for the HAND model is lengthy, once completed, the time to simulate flooding at a variety of water levels is rapid, making this model the most suitable choice for web-based, on-demand flood inundation mapping. Knowledge of the fit of these flood models and associated uncertainty can be helpful to emergency managers such that they can better understand exposure and vulnerability while preparing flood response plans.  相似文献   

Assessing Lateral Continuity within the Yammama Reservoir in the Foroozan Oilfield, Offshore Iran: An Integrated Study     

Payam HASSANZADEH  Ahmad Reza RABBANI  Ardeshir HEZARKHANI  Saeed KHAJOOIE 《《地质学报》英文版》2018,92(6):2405-2415

Located in Iranian sector of the Persian Gulf, Foroozan Oilfield has been producing hydrocarbons via seven different reservoirs since the 1970s. However, understanding fluid interactions and horizontal continuity within each reservoir has proved complicated in this field. This study aims to determine the degree of intra-reservoir compartmentalization using gas geochemistry, light hydrocarbon components, and petroleum bulk properties, comparing the results with those obtained from reservoir engineering indicators. For this purpose, a total of 11 samples of oil and associated gas taken from different producing wells in from the Yammama Reservoir were selected. Clear distinctions, in terms of gas isotopic signature and composition, between the wells located in northern and southern parts of the reservoir (i.e. lighter δ13C1, lower methane concentration, and negative sulfur isotope in the southern part) and light hydrocarbon ratios (e.g. nC7/toluene, 2,6-dmC7/1,1,3-tmcyC5 and m-xylene/4-mC8) in different oil samples indicated two separate compartments. Gradual variations in a number of petroleum bulk properties (API gravity, V/Ni ratios and asphaltene concentration) provided additional evidence on the reservoir-filling direction, signifying that a horizontal equilibrium between reservoir fluids across the Yammama Reservoir is yet to be achieved. Finally, differences in water-oil contacts and reservoir types further confirmed the compartmentalization of the reservoir into two separate compartments.  相似文献   

Paleoseismological investigations along Joggers Park Fault,Port Blair,South Andaman: Implications towards delineation of blind thrusting and related crustal deformation through ground penetrating radar (GPR) and electrical resistivity techniques (ERT and VES)     

Gulam Rasool Bhat  S. Balaji  Bikram S. Bali  Vazeem Iqbal  Balakrishna  Hamid Hussain 《Journal of the Geological Society of India》2018,91(1):81-90

A comprehensive paleoseismological investigations was carried out along Joggers Park Fault (striking NW-SE) reveals pervasive traces of active compressional tectonics (blind thrusting) and shallow-surface recent tectonic signatures along the fault. The geometry and trends in the tectonic deformation of the blind zone (shallow-subsurface stratigraphy) were examined with GPR and electrical resistivity tomography (ERT) and vertical electrical sounding (VES), strongly demonstrates severe tectonic deformation (persistent tectonic style) from Quaternary to Holocene times in a compressive stress regime. The surface manifestation of deformation (topographic expression) along the fault can be marked as hanging wall uplift and can be visually observed in the exposed sections at nearly half kilometer distance from the table land of Joggers Park in the form of a well-defined disconnected high angle thrust fault scarp (reverse fault). The reverse fault kinematically and intimately linked with underlying fault geometry provides adduced evidence to evaluate strike displacement profiles (displacement length relationship) along the fault. In addition, deformed stacked colluvial wedge below the scarp represents a powerful basis to calibrate recent and long term slip rates of the underlying fault.  相似文献   

Analytical solution of polymer slug injection with viscous fingering     

S. A. Abdul Hamid  A. H. Muggeridge 《Computational Geosciences》2018,22(3):711-723

We present an analytical solution to estimate the minimum polymer slug size needed to ensure that viscous fingering of chase water does not cause its breakdown during secondary oil recovery. Polymer flooding is typically used to improve oil recovery from more viscous oil reservoirs. The polymer is injected as a slug followed by chase water to reduce costs; however, the water is less viscous than the oil. This can result in miscible viscous fingering of the water into the polymer, breaking down the slug and reducing recovery. The solution assumes that the average effect of fingering can be represented by the empirical Todd and Longstaff model. The analytical calculation of minimum slug size is compared against numerical solutions using the Todd and Longstaff model as well as high resolution first contact miscible simulation of the fingering. The ability to rapidly determine the minimum polymer slug size is potentially very useful during enhanced oil recovery (EOR) screening studies.  相似文献   

A tectono-stratigraphic record of an extensional basin: the Lower Jurassic Ab-Haji Formation of east-central Iran     

Mohammad Ali Salehi  Reza Moussavi-Harami  Asadollah Mahboubi  Franz Theodor Fürsich  Markus Wilmsen  Christoph Heubeck 《Swiss Journal of Geoscience》2018,111(1-2):51-78

The Lower Jurassic Ab-Haji Formation consists of siliciclastic strata which are widespread and superbly exposed across the Tabas and Lut blocks of east-central Iran. The formation records the geodynamic history of central Iran during the Early Jurassic in the aftermath of the main Cimmerian event (near the Triassic–Jurassic boundary) through its sedimentary facies and stratigraphic architecture and allows palaeogeographic and palaeoenvironmental reconstructions. We measured and studied three well-exposed outcrop sections and identified lithofacies and facies associations (fluvial plain, delta plain, delta front, prodelta, and shallow-marine siliciclastic shelf). The integration of all geological, stratigraphic, and sedimentological data shows a west-to-east continental-to-marine gradient within the Ab-Haji Formation. Based on thickness variations, lateral facies changes, palaeocurrent patterns, and changes in the nature of the basal contact of the Ab-Haji Formation on the Tabas and Lut blocks, we locate the fault-bounded Yazd Block in the west and the Shotori Swell at the eastern edge of the Tabas Block as provenance regions. The pattern of thickness variations, rapid east–west facies changes, and provenance is best explained by a tectonic model invoking large tilted fault blocks in an extensional basin. The basal unit shows distinct increase in grain size at the base of the Ab-Haji Formation, similar to the Shemshak Group of the Alborz Mountains (the base of the Alasht Formation) and the non-marine time-equivalent succession of the Binalud Mountains of northeastern Iran. This grain size pattern may have been caused by rapid source area uplift due to slab break-off of the subducted Iran plate in the course of the Cimmerian collision in east-central Iran.  相似文献   

Spatial prediction of soil erosion susceptibility: an evaluation of the maximum entropy model   总被引：1，自引：0，他引：1  

Maryam Pournader  Hasan Ahmadi  Sadat Feiznia  Haji Karimi  Hamid Reza Peirovan 《Earth Science Informatics》2018,11(3):389-401

Soil erosion is considered as the most widespread form of soil degradation which causes serious environmental problems. This study investigates the performance of the maximum entropy (ME) in mapping rill erosion susceptibility in the Golgol watershed, Ilam province, Iran. To this end, ten rill erosion conditioning factors were selected to be employed in the modelling process based on an investigation of the literature. These layers are: elevation, slope percent, aspect, stream power index, topographic wetness index, distance from streams, plan curvature, lithology, land use, and soil. Then, a training dataset of rill erosion locations was used for modelling this phenomenon. The area under receiver operating characteristics curve was used for evaluating the performance of the ME model. In addition, Modified Pacific South-West Inter Agency Committee (MPSIAC) framework was applied and sediment yield was determined for different hydrological units in the study area. At last, Jackknife test was implemented to show the contribution of the factors in the modelling process. The results depicted that area under ROC curve for training and validation datasets were 0.867, and 0.794, respectively. Therefore, this conclusion can be achieved that ME worked well and could be a good tool for generating rill erosion susceptibility maps and its output could be employed for soil conservation in similar areas.  相似文献   

GIS-based gully erosion susceptibility mapping: a comparison among three data-driven models and AHP knowledge-based technique     

Alireza Arabameri  Khalil Rezaei  Hamid Reza Pourghasemi  Saro Lee  Mojtaba Yamani 《Environmental Earth Sciences》2018,77(17):628

Toroud Watershed in Semnan Province, Iran is a prone area to gully erosion that causes to soil loss and land degradation. To consider the gully erosion, a comprehensive map of gully erosion susceptibility is required as useful tool for decreasing losses of soil. The purpose of this research is to generate a reliable gully erosion susceptibility map (GESM) using GIS-based models including frequency ratio (FR), weights-of-evidence (WofE), index of entropy (IOE), and their comparison to an expert knowledge-based technique, namely, Analytic Hierarchy Process (AHP). At first, 80 gully locations were identified by extensive field surveys and Google Earth images. Then, 56 (70%) gully locations were randomly selected for modeling process, and the remaining 26 (30%) gully locations were used for validation of four models. For considering geo-environmental factors, VIF and tolerance indices are used and among 18 factors, 13 factors including elevation, slope degree, slope aspect, plan curvature, distance from river, drainage density, distance from road, lithology, land use/land cover, topography wetness index (TWI), stream power index (SPI), normalized difference vegetation index (NDVI), and slope–length (LS) were selected for modeling aims. After preparing GESMs through the mentioned models, final maps divided into five classes including very low, low, moderate, high, and very high susceptibility. The receiver operating characteristic (ROC) curve and the seed cell area index (SCAI) as two validation techniques applied for assessment of the built models. The results showed that the AUC (area under the curve) in training data are 0.973 (97.3%), 0.912 (91.2%), 0.939 (93.9%), and 0.926 (92.6%) for AHP, FR, IOE, and WofE models, respectively. In contrast, the prediction rates (validating data) were 0.954 (95.4%), 0.917 (91.7), 0.925 (92.5%), and 0.921 (92.1%) for above models, respectively. Results of AUC indicated that four model have excellent accuracy in prediction of prone areas to gully erosion. In addition, the SCAI values showed that the produced maps are generally reasonable, because the high and very high susceptibility classes had very low SCAI values. The results of this research can be used in soil conservation plans in the study area.  相似文献