Download or read book LiDAR based Landslide Inventory and Susceptibility Mapping and Differential LiDAR Analysis for the Panther Creek Watershed Coast Range Oregon written by Katherine A. Mickelson and published by . This book was released on 2011 with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: LiDAR (Light Detection and Ranging) elevation data were collected in the Panther Creek Watershed, Yamhill County, Oregon in September and December, 2007, March, 2009 and March, 2010. LiDAR derived images from the March, 2009 dataset were used to map pre-historic, historic, and active landslides. Each mapped landslide was characterized as to type of movement, head scarp height, slope, failure depth, relative age, and direction. A total of 153 landslides were mapped and 81% were field checked in the study area. The majority of the landslide deposits (127 landslides) appear to have had movement in the past 150 years. Failures occur on slopes with a mean estimated pre-failure slope of 27° ± 8°. Depth to failure surfaces for shallow-seated landslides ranged from 0.75 m to 4.3 m, with an average of 2.9 m ± 0.8 m, and depth to failure surfaces for deep-seated landslides ranged from 5 m to 75m, with an average of 18 m ± 14 m. Earth flows are the most common slope process with 110 failures, comprising nearly three quarters (71%) of all mapped deposits. Elevation changes from two of the successive LiDAR data sets (December, 2007 and March, 2009) were examined to locate active landslides that occurred between the collections of the LiDAR imagery. The LiDAR-derived DEMs were subtracted from each other resulting in a differential dataset to examine changes in ground elevation. Areas with significant elevation changes were identified as potentially active landslides. Twenty-six landslides are considered active based upon differential LiDAR and field observations. Different models are used to estimate landslide susceptibility based upon landslide failure depth. Shallow-seated landslides are defined in this study as having a failure depth equal to less than 4.6 m (15 ft). Results of the shallow-seated susceptibility map show that the high susceptibility zone covers 35% and the moderate susceptibility zone covers 49% of the study area. Due to the high number of deep-seated landslides (58 landslides), a deep-seated susceptibility map was also created. Results of the deep-seated susceptibility map show that the high susceptibility zone covers 38% of the study area and the moderate susceptibility zone covers 43%. The results of this study include a detailed landslide inventory including pre-historic, historic, and active landslides and a set of susceptibility maps identifying areas of potential future landslides.

Download or read book Landslide Inventory Mapping of the Drift Creek Watershed Lincoln County Oregon Using LiDAR Data written by Sebastian W. V. Dirringer and published by . This book was released on 2015 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: Light Detection and Ranging (LiDAR) elevation data was collected in 2011 for the Drift Creek watershed, Lincoln County, Oregon. LiDAR derived images were used to map landslide deposits, scarp flanks and head scarps. Landslide features, such as the type of movement, relative age, pre-failure slope angle, head scarp heights, failure depth, and direction, were also characterized. Landslide susceptibility zones for the entire watershed were generated combining a factor of safety approach, which utilizes the infinite slope analysis. Spatial statistics were calculated with respect to landslides and their proximity to roads and streams. A total of 473 landslides have been located in the Drift Creek watershed through applications of the Geographic Information System (GIS). A portion of the total number of landslides mapped using LiDAR data were field checked to ensure mapping accuracy. Rock and soil samples, collected in the field, were used to classify fine and coarse- grained materials that comprise most of the watershed. Effects of timber harvesting practices are profound in the study area, impacting both hydrological and ecological regimes. Most logging roads either cut across the toes of the landslides or apply large live loads to slope crests, thereby promoting landslide- related erosion. This study found that in the Drift Creek watershed, landslides directly impact (intersect) 22% of streams and 14% of roads. All of the streams in the study area flow into the Alsea River, which ultimately discharges into the Pacific Ocean.

Download or read book Landslide Inventory Mapping and Dating Using LiDAR based Imagery and Statistical Comparison Techniques in Milo McIver State Park Clackamas County Oregon written by Serin Duplantis and published by . This book was released on 2011 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: A landslide inventory was conducted for the Redland and Estacada Quadrangles of western Oregon using LiDAR DEMs. Many of these landslides were field verified. In total, 957 landslides were mapped using LiDAR whereas previously, only 228 landslides were believed to exist in the study area based on SLIDO information. In Milo McIver State Park, 41 landslides were mapped using LiDAR. SLIDO indicated only three landslides present within the park. A sequence of seven terraces of the Clackamas River is mapped in Milo McIver State Park. Landslides in the park predominantly occur between these terraces. Soils studied from representative areas within landslide complexes and terrace surfaces help to formulate a soil chronosequence for the study area. The youngest soils, Entisols, develop in less than 1,600 years, Inceptisols between 1,600-10,000 years, and the oldest soils, Alfisols, develop in at least 10,000 years. Classifications of soil profiles netted ten Alfisols (mainly on upper terraces), 49 Inceptisols, and 20 Entisols (reactivated slides in the complexes). The soils are predominantly ML soils and have Loam and Silt Loam textures. Results of spectral analysis, carried out on the LiDAR DEMs, indicate that the spectral character of landslides changes with age. However, applying statistical tools such as the Kolmogorov-Smirnov test (K-S test) and cluster analysis suggest that it is not possible to use spectral analysis to determine the relative age of failed surfaces. The K-S test showed that the spectral character among landslides varies widely. Cluster analysis resulted groupings not based on age or terrain type. The result of the cluster analysis illustrates that it may not be realistic to use a single cutoff, which separates failed terrain from unfailed, in the spectral distributions to analyze an entire region. In all, the results of the spectral analysis were not conclusive. Individual landslides, not complexes, should be used in future studies, since complexes have slides that are continually reactivating. The landslides were also too young to display very much differentiation in age based on soils and spectral analysis. Essentially, a similar study should be conducted using individual landslides with a large age range for more conclusive results.

Download or read book Analysis of Spatial Data from Terrain Models for Landslide Predictive Mapping written by Rubini Santha and published by . This book was released on 2014 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: Landslides are a pervasive hazard that can result in substantial damage to properties and loss of life throughout the world. To understand the nature and scope of the hazard, landslide hazard mapping has been an area of intense research by identifying areas most susceptible to landslides in order to mitigate against these potential losses. Advanced GIS and remote sensing techniques are a fundamental component to both generate landslide inventories of previous landslides and identify landslide prone regions. A Digital Elevation Model (DEM) is one of the most critical data sources used in this GIS analysis to describe the topography. A DEM can be obtained from several remote sensing techniques, including satellite data and Light Detection and Ranging (LiDAR). While a DEM is commonly used for landslide hazard analysis, insufficient research has been completed on the influence of DEM source and resolution on the quality of landslide hazard mapping, particularly for high resolution DEMs such as those obtained by LiDAR. In addition to topography, multiple conditioning factors are often employed in landslide susceptibility mapping; however, the descriptive accuracy and contribution of the data representing these factors to the overall analysis is not fully understood or quantified. In many cases, the data available for these factors may be of insufficient quality, particularly at regional scales. These factors are often integrated into a wide assortment of analysis techniques, which can result in inconsistent mapping and hazard analysis. To this end, the principal objectives of this study are to 1) evaluate the influence of DEM source and spatial resolution in landslide predictive mapping, 2) asses the predictive accuracy of landslide susceptibility mapping produced from fewer critical conditioning factors derived solely from LiDAR data, 3) compare six widely used and representative landslide susceptibility mapping techniques to evaluate their consistency, 4) create a seismically-induced landslide hazard map for landside-prone Western Oregon, and 5) develop automated tools to generate landslide susceptibility maps in a regional scale. In this study, semi-qualitative, quantitative and hybrid mapping techniques were used to produce a series of landslide susceptibility maps using 10 m, 30 m and 50 m resolution datasets obtained from ASTER (Advance Space borne Thermal Emission and Reflection Radiometer), NED (National Elevation Dataset) and LiDAR (Light Detection and Ranging). The results were validated against detailed landslide inventory maps highlighting scarps and deposits derived by geologic experts from LiDAR DEMs. The output map produced from the LiDAR 10 m DEM was identified as the optimum spatial resolution and showed higher predictive accuracy for landslide susceptibility mapping. Higher resolution DEMs from LIDAR data was also investigated; however, they were not significantly improved over the 10 m DEM. Next, a series of landslide susceptibility maps were compared from six widely used statistical techniques using slope, slope roughness, elevation, terrain roughness, stream power index and compound topographic index derived from LiDAR DEM. The output maps were validated using both confusion matrix and area of curve methods. Statistically, the six output maps produced, showed accepTable prediction rate for landslide susceptibility. However, visual effects and limitations were noted that vary based on each technique. This study also showed that a single LiDAR DEM was capable of producing a satisfactory susceptibility map without additional data sources that may be difficult to obtain for large areas. In western Oregon, landslides are widespread and account for major direct and indirect losses on a frequent basis. A variety of factors lead to these landslides, which makes them difficult to analyze at a regional scale where detailed information is not available. For this study, a seismically-induced landslide hazard map was created using a multivariate, ordinary least squares approach. Various data sources, including combinations of topography (slope, aspect), lithology, vegetation indices (NDVI), mean annual precipitation, seismic sources (e.g., PGA, PGV, distance to nearest fault), and land use were rigorously evaluated to determine the relative contributions on each parameter on landslide potential in western Oregon. Results of the analysis showed that slope, PGA, PGV and precipitation were the strongest indicators of landslide susceptibility and other factors had minimal influence on the resulting map. An automated tool kit was a byproduct of this analysis which can be used to simply the hazard mapping process and selection of parameters to include in the analysis.

Download or read book Slope Failure Detection Through Multi temporal Lidar Data and Geotechnical Soils Analysis of the Deep Seated Madrone Landslide Coast Range Oregon written by and published by . This book was released on 2015 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: Landslide hazard assessment of densely forested, remote, and difficult to access areas can be rapidly accomplished with airborne light detection and ranging (lidar) data. An evaluation of geomorphic change by lidar-derived digital elevation models (DEMs) coupled with geotechnical soils analysis, aerial photographs, ground measurements, precipitation data, and numerical modeling can provide valuable insight to the reactivation process of unstable landslides. A landslide was selected based on previous work by Mickleson (2011) and Burns et al. (2010) that identified the Madrone Landslide with significant volumetric changes. This study expands on previous work though an evaluation of the timing and causation of slope failure of the Madrone Landslide. The purpose of this study was to evaluate landslide morphology, precipitation data, historical aerial photographs, ground crack measurements, geotechnical properties of soil, numerical modeling, and elevation data (with multi-temporal lidar data), to determine the conditions associated with failure of the Madrone Landslide. To evaluate the processes involved and timing of slope failure events, a deep seated potentially unstable landslide, situated near the contact of Eocene sedimentary and volcanic rocks, was selected for a detailed analysis. The Madrone Landslide (45.298383/-123.338796) is located in Yamhill County, about 12 kilometers west of Carlton, Oregon. Site elevation ranges from 206 meters (m) North American Vertical Datum (NAVD-88) near the head scarp to 152 m at the toe. The landslide is composed of two parts, an upper more recent rotational slump landslide and a lower much older earth flow landslide. The upper slide has an area of 2,700 m2 with a head scarp of 5-7 m and a volume of 15,700 m3. The lower earth flow has an area of 2300 m2, a head scarp of 15 m, and a volume of 287,500 m3. Analysis of aerial photographs indicates the lower slide probably originated between 1956 and 1963. The landslide is located at a geologic unit contact of Eocene deep marine sedimentary rock and intrusive volcanic rock. The landslide was instrumented with 20 crack monitors established across ground cracks and measured periodically. Field measurements did not detect ground crack displacement over a 15 month period. Soil samples indicate the soil is an MH soil with a unit weight of 12 kN/m3 and residual friction angle of 28 which were both used as input for slope stability modeling. Differential DEMs from lidar data were calculated to generate a DEM of Difference (DoD) raster to identify and quantify elevation changes. Historical aerial photograph review, differential lidar analysis, and precipitation data suggest the upper portion of the landslide failed as a result of the December 2007 storm.

Download or read book Laser Scanning Applications in Landslide Assessment written by Biswajeet Pradhan and published by Springer. This book was released on 2017-05-04 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is related to various applications of laser scanning in landslide assessment. Landslide detection approaches, susceptibility, hazard, vulnerability assessment and various modeling techniques are presented. Optimization of landslide conditioning parameters and use of heuristic, statistical, data mining approaches, their advantages and their relationship with landslide risk assessment are discussed in detail. The book contains scanning data in tropical forests; its indicators, assessment, modeling and implementation. Additionally, debris flow modeling and analysis including source of debris flow identification and rockfall hazard assessment are also presented.

Download or read book Landslide Inventory and Susceptibility in the Salmonberry River Drainage Basin Northern Oregon Coast Range written by Laura M. Burris and published by . This book was released on 1999 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book LANDSLIDE DETECTION AND SUSCEPTIBILITY MAPPING USING LIDAR AND ARTIFICIAL NEURAL NETWORK MODELING written by M. Kenneth Brown and published by . This book was released on 2012 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this study was to detect shallow landslides using hillshade maps derived from Light Detection and Ranging (LiDAR)-based Digital Elevation Model (DEM) and validated by field inventory. The landslide susceptibility mapping used an Artificial Neural Network (ANN) approach and back propagation method that was tested in the northern portion of the Cuyahoga Valley National Park CVNP) located in Northeast Ohio. The relationship between landslides and different predictor attributes extracted from the LiDAR-based-DEM such as slope, profile and plan curvatures, upslope drainage area, annual solar radiation, and wetness index was evaluated using a Geographic Information System (GIS) based investigation. The approach presented in this thesis required a training study area for the development of the susceptibility model and a validation study area to test the model. The results from the validation showed that within the very high susceptibility class, a total of 42 % of known landslides that were associated with 1.6% of total area were correctly predicted. On the other hand, the very low susceptibility class that represented 82 % of the total area was associated with 1 % of correctly predicted landslides. The results suggest that the majority of the known landslides occur within a small portion of the study area, which is consistent with field investigation and other studies. Sample probabilistic maps of landslide susceptibility potential and other products from this approach are summarized and presented for visualization which is intended to help park officials in effective management and planning.

Download or read book Landslide Distribution and Susceptibility Material Properties and Soil Loss Estimates for the Drift Creek Watershed Siletz River Lincoln County Oregon written by David M. Korte and published by . This book was released on 2018 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Drift Creek Watershed is a source of drinking water for the Confederated Tribes of Siletz Indians (CTSI) and Lincoln City and is a reproductive habitat for endangered salmon and trout species. The Watershed has been designated as "Impaired by Unknown Stressors" by the MidCoast Watersheds Council Biological Monitoring Results Survey (2013). The Oregon Department of Geology and Mineral Industries (DOGAMI), the Oregon Department of Environmental Quality (DEQ), and the CTSI suspect that landslides may be causing water quality deterioration. This study maps landslide distribution and landslide susceptibility; determines physical properties of landslide-prone soil and rock; and estimates soil loss resulting from landslide-derived sediment within 30 m of Strahler 3rd order or higher streams in the Drift Creek Watershed. Five hundred and seventy landslides were mapped using light detection and ranging (lidar) imaging, orthophotographs, and field observations. Debris flow and fluvial incision are controlling the relief in the Siletz River Volcanics; while deep seated landslides (landslides through bedrock) are controlling the relief in the Tyee Formation. Logistic regression was used to determine the most significant variables contributing to the probability of landslide occurrence and to create a watershed scale landslide susceptibility map. The susceptibility model can be focused to determine the probability of landslide occurrence for any specific area of interest (near a stream, a road, human related activity such as residential and commercial construction and trails, etc.) in the Watershed. Rock durability ranges from very low to medium high. Siletz River Volcanics and Tyee Formation soils in the Drift Creek Watershed fail in a brittle manner when sheared at natural water content, have a narrow range of plasticity, and have residual friction angles near the pre-failure slope angles for their respective landslide deposits. The soil loss model developed for this study estimates average annual soil loss anywhere in the Watershed, at any distance from the stream network, at any specific landslide deposit, any specific land cover condition, near any road, etc. The model points out the exact landslide deposits and stream channels where the DEQ should focus initial studies of deteriorating water quality resulting from landslide-derived sediment entering stream channels. Estimated average annual soil loss from landslide deposits within 30 m of the 3rd order or higher stream network in the Upper Drift Creek component of the Drift Creek Watershed is more than twice the estimate for the Lower Drift Creek component (65 tons/acre/year vs 29 tons/acre/year respectively). The highest landslide-derived sediment soil loss estimates near stream channels occurred in logging areas. Recent logging activity is almost exclusive to the Upper Drift Creek Watershed. Logging activity, while not an initial concern for this study, was found to substantially affect landslide-derived sediment contribution to the stream channels in the Upper Drift Creek component of the Watershed.

Download or read book Landslide Geoanalytics Using LiDAR derived Digital Elevation Models written by Saeid Pirasteh and published by . This book was released on 2018 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: Landslides are natural hazards that contribute to tremendous economic loss and result in fatalities if there is no well-prepared mitigation and planning. Assessing landslide hazard and optimizing quality to improve susceptibility maps with various contributing factors remain a challenge when working with various geospatial datasets. Also, the system of updating landslide inventories which identify geometry, deformation, and type of landslide with semi-automated computing processes in the Geographic Information System (GIS) can be flawed. This study explores landslide geoanalytics approaches combined with empirical approach and powerful analytics in the Zagros and Alborz Mountains of Iran. Light Detection And Ranging (LiDAR)-derived Digital Elevation Models (DEMs), Unmanned Aerial Vehicle (UAV) images, and Google Earth images are combined with the existing inventory dataset. GIS thematic data in conjunction with field observations are utilized along with geoanalytics approaches to accomplish the results. The purpose of this study is to explore the challenges and techniques of landslide investigations. The study is carried out by studying stream length-gradient (SL) index analysis in order to identify tectonic signatures. A correlation between the stream length-gradient index and the graded Dez River profile with slopes and landslides is investigated. By building on the previous study a quantitative approach for evaluating both spatial and temporal factors contributing to landslides for susceptibility mapping utilizing LiDAR-derived DEMs and the Probability Frequency Ratio (PFR) model is expanded. Furthermore, the purpose of this study is to create an algorithm and a software package in MATLAB for semi-automated geometric analysis to measure and determine the length, width, area, and volume of material displacement and flow direction, as well as the type of landslide. A classification method and taxonomy of landslides are explored in this study. LiDAR-derived DEMs and UAV images help to characterize landslide hazards, revise and update the inventory dataset, and validate the susceptibility model, geometric analysis, and landslide deformation. This study makes the following accomplishments and contributions: 1) Operational use of LiDAR-derived DEMs for landslide hazard assessment is estimated, which is a realistic ambition if we can continue to build on recent achievements; 2) While a steeper gradient could potentially be a signature for landslide identification, this study identifies the geospatial locations of high-gradient indices with potential to landslides; 3) An updated inventory dataset is achieved, this study indicates an improved landslide susceptibility map by implementing the PFR model compared to the existing data and previous studies in the same region. This study shows that the most effective factor is the lithology with 13.7% positive influence; and 4) This study builds a software package in MATLAB that can a) determine the type of landslide, b) calculate the area of a landslide polygon, c) determine and measure the length and width of a landslide, d) calculate the volume of material displacement and determine mass movement (i.e. deformation), and e) identify the flow direction of a landslide material movement. In addition to the contributions listed above, a class taxonomy of landslides is introduced in this study. The relative operating characteristic (ROC) curve method in conjunction with field observations and the inventory dataset are used to validate the accuracy of the PFR model. The validation of the result for susceptibility mapping accuracy is 92.59%. Further, the relative error method is applied to validate the performance of relative percentage of error of the selected landslides computing in the proposed software package. The relative percentage of error of the area, length, width, and volume is 0.16%, 1.67%, 0.30%, and 5.50% respectively, compared to ArcGIS. Marzan Abad and Chalus from Mazandaran Province of Iran and Madaling from Guizhou Province of China are used for validating the proposed algorithm.

Download or read book Landslide Susceptibility Map for Shallow Landslides for the West Hills of Portland Oregon Using GIS and LiDAR written by Marina Claire Drazba and published by . This book was released on 2008 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Protocol for Inventory Mapping of Landslide Deposits from Light Detection and Ranging lidar Imagery written by William John Burns and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Enhancing Landslide Inventorying Hazard Assessment and Asset Management Using Lidar written by Ben A. Leshchinsky and published by . This book was released on 2018 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book High resolution Lidar Mapping and Analysis to Quantify Surface Movement of Swift Creek Landslide Whatcom County WA written by Benjamin R. Ferreira and published by . This book was released on 2014 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Probabilistic Use of LiDAR Data to Detect and Characterize Landslides written by Dorota A. Grejner-Brzezinska and published by . This book was released on 2015 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: Landslide hazard and its consequences in the transportation network are well-understood, yet current methods of identifying and assessing landslide conditions are inefficient, as they are mostly based on labor-intensive field surveys. This research was performed as a feasibility study, where the potential of airborne LiDAR data for landslide detection was investigated. The primary objective of this pilot study was to develop, implement and validate computer models for automatic detection and assessment of landslides using time-series of airborne LiDAR data. Models have been developed using LiDAR data obtained from SR 666 in Muskingum County (District 5) and independently tested on LiDAR data covering southern Ohio. In this research effort, two techniques, one using single and the other based on multi-temporal surface models, obtained by airborne LiDAR, were proposed, implemented and tested for landslide susceptibility and hazard mapping. Based on a single dataset, 84% of the landslides from the reference inventory map of SR 666 were correctly identified, while using two datasets acquired four years apart, the proposed technique was able to identify 66% of the mapped landslides that are experiencing temporal changes susceptible to slides.

Download or read book Evaluation of LIDAR for Landslide Mapping written by Christopher J. Wills and published by . This book was released on 2006 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book LiDAR GIS and Multivariate Statistical Analysis to Assess Landslide Risk Horseshoe Run Watershed West Virginia written by Kory M. Konsoer and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: