Landslide Geoanalytics Using Lidar Derived Digital Elevation Models

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Landslide Geoanalytics Using LiDAR-derived Digital Elevation Models

Author : Saeid Pirasteh
Publisher :
ISBN 13 :
Total Pages : 149 pages
Book Rating : 4.:/5 (13 download)

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Book Synopsis Landslide Geoanalytics Using LiDAR-derived Digital Elevation Models by : Saeid Pirasteh

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.

LANDSLIDE DETECTION AND SUSCEPTIBILITY MAPPING USING LIDAR AND ARTIFICIAL NEURAL NETWORK MODELING

Author : M. Kenneth Brown
Publisher :
ISBN 13 :
Total Pages : 58 pages
Book Rating : 4.:/5 (847 download)

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Book Synopsis LANDSLIDE DETECTION AND SUSCEPTIBILITY MAPPING USING LIDAR AND ARTIFICIAL NEURAL NETWORK MODELING by : M. Kenneth Brown

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.

Landslide Mapping Using Multiscale Lidar Digital Elevation Models

Author : Javed Miandad
Publisher :
ISBN 13 :
Total Pages : 164 pages
Book Rating : 4.:/5 (14 download)

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Book Synopsis Landslide Mapping Using Multiscale Lidar Digital Elevation Models by : Javed Miandad

Download or read book Landslide Mapping Using Multiscale Lidar Digital Elevation Models written by Javed Miandad and published by . This book was released on 2018 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study presents a new methodology to identify landslide and landslide susceptible locations in interior Alaska using only geomorphic properties from light detection and ranging (LiDAR) derivatives (i.e., slope, profile curvature, roughness) and the normalized difference vegetation index (NDVI). The study specifically focused on the effect of different resolutions of LiDAR images in identifying landslide locations. I developed a semi-automated object-oriented image classification approach in ArcGIS 10.5, and prepared a landslide inventory from visual observation of hillshade images. The multistage workflow included combining derivatives from 1m, 2.5m, and 5m resolution LiDAR, image segmentation, image classification using a support vector machine classifier, and image generalization to clean false positives. I assessed the accuracy of the classifications by generating confusion matrix tables. Analysis of the results indicated that the scale of LiDAR images played an important role in the classification, and the use of NDVI generated better results in identifying landslide and landslide susceptible places. Overall, the LiDAR 5m resolution image with NDVI generated the best results with a kappa value of 0.55 and an overall accuracy of 83%. The LiDAR 1m resolution image with NDVI generated the highest producer accuracy of 73% in identifying landslide locations. I produced a combined overlay map by summing the individual classified maps, which was able to delineate landslide objects better than the individual maps. The combined classified map from 1m, 2.5m, and 5m resolution LiDAR with NDVI generated producer accuracies of 60%, 80%, 86%, and user accuracies of 39%, 51%, 98% for landslide, landslide susceptible, and stable locations, respectively, with an overall accuracy of 84% and a kappa value of 0.58. The proposed method can be improved by fine-tuning segmented image generation, incorporating other data sets, and developing a standard accuracy assessment technique for object-oriented image analysis.

A Method for Automatic and Unsupervised Detection of Shallow Landslides from Lidar-derived, High-resolution Digital Elevation Models Using a Wavelet Transform

Download A Method for Automatic and Unsupervised Detection of Shallow Landslides from Lidar-derived, High-resolution Digital Elevation Models Using a Wavelet Transform PDF Online Free

Author : William Jeffery Reeder
Publisher :
ISBN 13 :
Total Pages : 306 pages
Book Rating : 4.:/5 (832 download)

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Book Synopsis A Method for Automatic and Unsupervised Detection of Shallow Landslides from Lidar-derived, High-resolution Digital Elevation Models Using a Wavelet Transform by : William Jeffery Reeder

Download or read book A Method for Automatic and Unsupervised Detection of Shallow Landslides from Lidar-derived, High-resolution Digital Elevation Models Using a Wavelet Transform written by William Jeffery Reeder and published by . This book was released on 2012 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Evaluation of LIDAR for Landslide Mapping

Author : Christopher J. Wills
Publisher :
ISBN 13 :
Total Pages : 72 pages
Book Rating : 4.:/5 (1 download)

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Book Synopsis Evaluation of LIDAR for Landslide Mapping by : Christopher J. Wills

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:

Analysis of Spatial Data from Terrain Models for Landslide Predictive Mapping

Author : Rubini Santha
Publisher :
ISBN 13 :
Total Pages : 214 pages
Book Rating : 4.:/5 (883 download)

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Book Synopsis Analysis of Spatial Data from Terrain Models for Landslide Predictive Mapping by : Rubini Santha

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.

Slope Failure Detection Through Multi-temporal Lidar Data and Geotechnical Soils Analysis of the Deep-Seated Madrone Landslide, Coast Range, Oregon

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Author :
Publisher :
ISBN 13 :
Total Pages : 84 pages
Book Rating : 4.:/5 (963 download)

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Book Synopsis Slope Failure Detection Through Multi-temporal Lidar Data and Geotechnical Soils Analysis of the Deep-Seated Madrone Landslide, Coast Range, Oregon by :

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.

Landslide Inventory Mapping of the Drift Creek Watershed, Lincoln County, Oregon, Using LiDAR Data

Author : Sebastian W. V. Dirringer
Publisher :
ISBN 13 :
Total Pages : 103 pages
Book Rating : 4.:/5 (953 download)

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Book Synopsis Landslide Inventory Mapping of the Drift Creek Watershed, Lincoln County, Oregon, Using LiDAR Data by : Sebastian W. V. Dirringer

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.

Airborne LiDAR-derived Digital Elevation Model for Archaeology

Author : Benjamin Štular
Publisher :
ISBN 13 :
Total Pages : 21 pages
Book Rating : 4.:/5 (128 download)

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Book Synopsis Airborne LiDAR-derived Digital Elevation Model for Archaeology by : Benjamin Štular

Download or read book Airborne LiDAR-derived Digital Elevation Model for Archaeology written by Benjamin Štular and published by . This book was released on 2021 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Analysis of Landslide Kinematics Using Multi-temporal UAV Imagery, La Honda, California

Author : Jordan Alexander Carey
Publisher :
ISBN 13 : 9780355764451
Total Pages : pages
Book Rating : 4.7/5 (644 download)

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Book Synopsis Analysis of Landslide Kinematics Using Multi-temporal UAV Imagery, La Honda, California by : Jordan Alexander Carey

Download or read book Analysis of Landslide Kinematics Using Multi-temporal UAV Imagery, La Honda, California written by Jordan Alexander Carey and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: High-resolution topographic data are vital to studies of earth-surface processes. The combination of unmanned aerial vehicle (UAV) photography and structure-from-motion (SfM) digital photogrammetry provide a quickly deployable and cost-effective method for monitoring geomorphic change and landscape evolution. We acquired imagery of an active landslide in La Honda, California using a GPS-enabled quadcopter UAV with a 12.4 megapixel camera. Deep-seated landslides were previously documented in this region during the winter of 1997-98, with movement recurring and the landslide expanding during the winters of 2004-05 and 2005-06. This study documents the kinematics of a new and separate landslide immediately adjacent to the previous ones, throughout the winter of 2016-17. The Scenic Drive landslide is roughly triangular-shaped, deep-seated failure covering an area of approximately 10,000 m2. The area is underlain by SW-dipping late Miocene to Pliocene sandstones and mudstones. A ~3 m-high head scarp stretches along the northeast portion of the slide along a distance of ~100 m. The direction of movement is towards the southwest, with two prominent NW-SE striking extensional grabens and numerous tension cracks across the landslide body. In this thesis, I calculate displaced landslide volumes, derived from changes in elevation, and surface displacements from multi-temporal UAV surveys. Photogrammetric reconstruction of UAV/SfM-derived point clouds allowed creation of seven digital elevation models (DEMs) with spatial resolutions ranging from ~3 to 10 cm per pixel. I derived displacement magnitude, direction and rate by comparing multiple generations of DEMs and orthophotos and estimated displaced volumes by differencing subsequent DEMs creating DEMs of difference (DoDs). I then correlated displacements with total rainfall and rainfall intensity measurements. Geomorphic mapping of the study area identifies major landslide features, such as the head scarp, normal and thrust scarps, extensional grabens, tension cracks, and associated earthflows, documenting dominant surface processes on the slide. Additionally, I compare the accuracy of the UAV/SfM-derived DEM with a DEM sourced from a synchronous terrestrial lidar survey. Conservative measurements yield 5.4 m of maximum horizontal displacement across the central portion of the slide during the monitoring period. Over the course of the monitoring period, ~3,000 m3 of material was displaced by the landslide. Comparisons between the lidar and SfM DEMs showed that the two are comparable in the horizontal direction within 0.05 m. In the vertical direction lidar and SfM are comparable within 0.20 m in unvegetated areas. This study further demonstrates the ability of the UAV/SfM workflow to map and monitor active mass-wasting processes in regions where landslides pose a threat to the surrounding community. Additionally, this thesis assesses the erosional characteristics of two recently burned areas in northern California: the 2015 Wragg Fire and the 2016 Emerald Fire. For the 2015 Wragg Fire, I compare observed post-fire erosion with USGS post-fire debris-flow models. For the 2016 Emerald Fire, I attempt estimate eroded material through multi-sourced DoDs and compare with field measurements. The aims of this study are to (1) further demonstrate the potential of UAV-SfM techniques in geomorphic studies and hazards management, (2) quantify landslide displacements and volumes by differencing multi-temporal DEMs and (3) document various mass-wasting/erosional processes across northern California. By increasing our understanding the various mass-wasting processes affecting northern California, we can help improve disaster preparation, response and management efforts potentially reducing damages and saving lives.

Discriminating Between Landslide Sites and Potentially Unstable Terrain Using Topographic Indices

Author : Jeremy Appt
Publisher :
ISBN 13 :
Total Pages : 232 pages
Book Rating : 4.:/5 (556 download)

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Book Synopsis Discriminating Between Landslide Sites and Potentially Unstable Terrain Using Topographic Indices by : Jeremy Appt

Download or read book Discriminating Between Landslide Sites and Potentially Unstable Terrain Using Topographic Indices written by Jeremy Appt and published by . This book was released on 2002 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: A landslide inventory, statistical analyses and a Geographic Information System (GIS) are used to analyze landslide sites and potentially unstable terrain in the Oregon Coast Range. The objectives are to evaluate the efficacy of locating landslide sites with topographic variables and discriminate the difference between sites where landslides have and have not occurred. The population of known landslides are characterized as up-slope, non-road related, and associated with 1996 storm events. Topographic variables are derived from a Digital Elevation Model (DEM) for index construction forming six groups; i) slopes, ii) contributing areas, iii) ratios of slope and contributing area, iv) curvature v) infinite slope models, and vi) functions of slope and contributing area based on statistical models. Index groups employ different algorithms. Index performance is measured with landslide and aerial densities. Cumulative landslide occurrence is plotted against cumulative area on a continuous domain of the index to locate a maximum landslide density on equal size areas. Indices are used to generate model definitions of potentially unstable terrain based on similarity to the landslide population. Aerial densities of potentially unstable terrain based on index definitions are determined but no common metric is achieved. Statistical analyses on spatially stratified data suggest a significant ([alpha]

Morphology-based Identification of Surface Features to Support Landslide Hazard Detection Using Airborne LiDAR Data

Author : Omar Ernesto Mora
Publisher :
ISBN 13 :
Total Pages : 223 pages
Book Rating : 4.:/5 (92 download)

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Book Synopsis Morphology-based Identification of Surface Features to Support Landslide Hazard Detection Using Airborne LiDAR Data by : Omar Ernesto Mora

Download or read book Morphology-based Identification of Surface Features to Support Landslide Hazard Detection Using Airborne LiDAR Data written by Omar Ernesto Mora and published by . This book was released on 2015 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reviewing and testing commonly used surface feature extraction techniques, such as point-based, profile-based, shape-based, and change detection techniques, such as nearest neighbor and Digital Elevation Model (DEM) of Difference (DoD), led to a conclusion that no single technique could solve the landslide predisposition for all environments and circumstances. Alternatively, to develop a unified approach, two robust techniques for landslide detection are proposed that are based on a stepwise strategy that focuses on surface geometry. The first method is based on fusing a shape-based surface feature extraction technique and change detection method using multi-temporal surface models, while the second method implements a technique to extract, identify, and map surface features found in landslide morphology using a single surface model. In addition, the impact of spatial resolution on small landslide mapping is demonstrated. Using experimental datasets available at the time of this research, the proposed methods showed that 66% and 84% of the landslides from the reference inventory could be detected by the first and the second method, respectively.

LiDAR-based Landslide Inventory and Susceptibility Mapping, and Differential LiDAR Analysis for the Panther Creek Watershed, Coast Range, Oregon

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Author : Katherine A. Mickelson
Publisher :
ISBN 13 :
Total Pages : 71 pages
Book Rating : 4.:/5 (759 download)

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Book Synopsis LiDAR-based Landslide Inventory and Susceptibility Mapping, and Differential LiDAR Analysis for the Panther Creek Watershed, Coast Range, Oregon by : Katherine A. Mickelson

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.

Global Changes and Natural Disaster Management: Geo-information Technologies

Author : Saied Pirasteh
Publisher : Springer
ISBN 13 : 3319518445
Total Pages : 229 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Global Changes and Natural Disaster Management: Geo-information Technologies by : Saied Pirasteh

Download or read book Global Changes and Natural Disaster Management: Geo-information Technologies written by Saied Pirasteh and published by Springer. This book was released on 2017-03-15 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents ongoing research and ideas related to earth observations and global change, natural hazards and disaster management studies, with respect to geospatial information technology, remote sensing, and global navigation satellite systems. Readers will discover uses of advanced geospatial tools, spatiotemporal models, and earth observation systems. Chapters identify the international aspects of the coupled social, land and climate systems in global change studies, and consider such global challenges as agriculture monitoring, the smart city, and risk assessment. The work presented here has been carefully selected, edited, and peer reviewed in order to advance research and development, as well as to encourage innovative applications of Geomatics technologies in global change studies. The book will appeal not only to academicians, but also to professionals, politicians and decision makers who wish to learn from the very latest and most innovative, quality research in this area of global change and natural disaster management. /divContributions are drawn from revised submissions based on state-of-the-art papers from the 7th GiT4NDM - 5th EOGC, 2015 event.

Geomorphological Mapping

Author : Mike J. Smith
Publisher : Elsevier
ISBN 13 : 0444535365
Total Pages : 635 pages
Book Rating : 4.4/5 (445 download)

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Book Synopsis Geomorphological Mapping by : Mike J. Smith

Download or read book Geomorphological Mapping written by Mike J. Smith and published by Elsevier. This book was released on 2011-10-22 with total page 635 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geomorphological Mapping: a professional handbook of techniques and applications is a new book targeted at academics and practitioners who use, or wish to utilise, geomorphological mapping within their work. Synthesising for the first time an historical perspective to geomorphological mapping, field based and digital tools and techniques for mapping and an extensive array of case studies from academics and professionals active in the area. Those active in geomorphology, engineering geology, reinsurance, Environmental Impact Assessors, and allied areas, will find the text of immense value. Growth of interest in geomorphological mapping and currently no texts comprehensively cover this topic Extensive case studies that will appeal to professionals, academics and students (with extensive use of diagrams, potentially colour plates) Brings together material on digital mapping (GIS and remote sensing), cartography and data sources with a focus on modern technologies (including GIS, remote sensing and digital terrain analysis) Provides readers with summaries of current advances in methodological/technical aspects Accompanied by electronic resources for digital mapping

Applied Spatial Data Analysis with R

Author : Roger S. Bivand
Publisher : Springer Science & Business Media
ISBN 13 : 1461476186
Total Pages : 414 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Applied Spatial Data Analysis with R by : Roger S. Bivand

Download or read book Applied Spatial Data Analysis with R written by Roger S. Bivand and published by Springer Science & Business Media. This book was released on 2013-06-21 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Spatial Data Analysis with R, second edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to access and visualise spatial data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and the open source GRASS GIS and the handling of spatio-temporal data. The second part showcases more specialised kinds of spatial data analysis, including spatial point pattern analysis, interpolation and geostatistics, areal data analysis and disease mapping. The coverage of methods of spatial data analysis ranges from standard techniques to new developments, and the examples used are largely taken from the spatial statistics literature. All the examples can be run using R contributed packages available from the CRAN website, with code and additional data sets from the book's own website. Compared to the first edition, the second edition covers the more systematic approach towards handling spatial data in R, as well as a number of important and widely used CRAN packages that have appeared since the first edition. This book will be of interest to researchers who intend to use R to handle, visualise, and analyse spatial data. It will also be of interest to spatial data analysts who do not use R, but who are interested in practical aspects of implementing software for spatial data analysis. It is a suitable companion book for introductory spatial statistics courses and for applied methods courses in a wide range of subjects using spatial data, including human and physical geography, geographical information science and geoinformatics, the environmental sciences, ecology, public health and disease control, economics, public administration and political science. The book has a website where complete code examples, data sets, and other support material may be found: http://www.asdar-book.org. The authors have taken part in writing and maintaining software for spatial data handling and analysis with R in concert since 2003.

Advances in Remote Sensing and Geo Informatics Applications

Author : Hesham M. El-Askary
Publisher : Springer
ISBN 13 : 3030014401
Total Pages : 329 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Advances in Remote Sensing and Geo Informatics Applications by : Hesham M. El-Askary

Download or read book Advances in Remote Sensing and Geo Informatics Applications written by Hesham M. El-Askary and published by Springer. This book was released on 2018-12-29 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume is based on the best papers accepted for presentation during the 1st Springer Conference of the Arabian Journal of Geosciences (CAJG-1), Tunisia 2018. The book compiles a wide range of topics addressing various issues by experienced researchers mainly from research institutes in the Mediterranean, MENA region, North America and Asia. Remote sensing observations can close gaps in information scarcity by complementing ground-based sparse data. Spatial, spectral, temporal and radiometric characteristics of satellites sensors are most suitable for features identification. The local to global nature and broad spatial scale of remote sensing with the wide range of spectral coverage are essential characteristics, which make satellites an ideal platform for mapping, observation, monitoring, assessing and providing necessary mitigation measures and control for different related Earth's systems processes. Main topics in this book include: Geo-informatics Applications, Land Use / Land Cover Mapping and Change Detection, Emerging Remote Sensing Applications, Rock Formations / Soil Lithology Mapping, Vegetation Mapping Impact and Assessment, Natural Hazards Mapping and Assessment, Ground Water Mapping and Assessment, Coastal Management of Marine Environment and Atmospheric Sensing.