Light Detection And Ranging Survey Research Articles

RS-BASED WATER RESOURCES INVENTORY OF THE PHILIPPINES: CAPACITY BUILDING EFFORTS FOR NATIONWIDE IMPLEMENTATION

Abstract. Considering that the Philippines is archipelagic in nature and is exposed to disasters accentuated by climate change, water resource monitoring and management has been an important concern in the country. The design and implementation of an effective management scheme relies heavily on accurate, complete, and updated water resource inventories, usually in the form of maps and geodatabases. With the aim of developing a detailed and comprehensive database of all water resources in the Philippines, a 3-year project entitled “Development of the Philippine Hydrologic Dataset (PHD) for Watersheds from LiDAR Surveys”, has been initiated by the University of the Philippines Diliman (UPD) and the Department of Science and Technology (DOST). Various workflows has been developed to extract inland hydrologic features in the Philippines using accurate Light Detection and Ranging (LiDAR) Digital Terrain Models (DTMs) and LiDAR point cloud data obtained through other government-funded programs, supplemented with other remotely-sensed imageries and ancillary information. Since the project covers national-scale mapping and inventory, the implementation was structured to be a collaborative effort between fifteen (15) State Universities/Colleges (SUCs) and Higher Education Institutes (HEIs), along with multiple National Government Agencies (NGAs) and Local Government Units (LGUs). This paper presents the project’s general structure, focusing mainly on its attempts and accomplishments in strengthening individual capacities of all involved SUCs, HEIs, and stakeholders utilizing hydrologic data for different applications.

Automated feature extraction for prospection and analysis of monumental earthworks from aerial LiDAR in the Kingdom of Tonga

Recent LiDAR (Light Detection and Ranging) survey in Tonga has documented a dense and complex archaeological landscape, particularly on the principal island of Tongatapu. Among the features revealed by the LiDAR are a profusion of earthen mounds, most of which are associated with residence, sporting, or burial in the period 1000–1850 CE. For identification and mapping of the mounds we use and evaluate two automated feature extraction (AFE) techniques, object-based image analysis and an inverted pit-filling algorithm (“iMound”). Accuracy of these methods was measured using an F1-score (harmonic mean of precision and recall). Variable AFE results indicate that continual and iterative fine-tuning is required. Successful mapping of some 10,000 mounds on Tongatapu reveals a distinct spatial structure that relates to traditional land division and tenure.

Numerical Simulation of the Topographical Change in Korea Mountain Area by Intense Rainfall and Consequential Debris Flow

The objectives of this study are to simulate the topographical changes associated with rainfall and the consequential debris flow using terrestrial LiDAR (Light Detection And Ranging). Three rainfall events between July 9 and July 14, 2009, triggered a number of debris flows at Jecheon County in Korea. Rain fell at a rate of 64 mm/h, producing 400 mm of total accumulation during this period. Tank simulation model for SWI (Soil Water Index) estimated the water stored beneath the ground and debris flow occurrence in study area. For the LiDAR (Light Detection and Ranging) survey, the terrestrial laser scanning system RIEGL LMS-Z390i consists of an accurate and fast 3D scanner, associated RTK GPS system. The DEM derived from LiDAR enabled the debris flow to be mapped and analyzed in great detail. The estimated affected area and erosion/deposition volumes by debris flow were compared with two-dimensional numerical simulation. The simulation results were sufficiently in good agreement with the debris flow track, and a success rate of over 90% was achieved with a simulation time of 300 s. A comparison of the simulated and surveyed results based on deposition volume yields a success rate of over 97% with 350 s of simulation time.

Terrestrial LiDAR Survey and Morphological Analysis to Identify Infiltration Properties in the Tamala Limestone, Western Australia

Caves are an ideal observatory of infiltration water in karstified limestone, and the application of remote sensing techniques can bring new insights toward flow patterns and processes. We present an exhaustive characterization of Golgotha Cave in SW Western Australia, based on a light detection and ranging (LiDAR) measurement campaign. The cave is developed in Quaternary age aeolianite (dune limestone) and its infiltration waters form speleothems. We collect ground-based LiDAR scans of the cave ceiling at three sites within the cave system. The resulting point-clouds are analyzed using mathematical morphology to determine statistical information on stalactite widths, lengths, and spatial distributions. We establish a relationship between stalactite diameter and length that is in agreement with the platonic ideal of stalactite shape. We relate stalactite density variation with topography of the cave ceiling and variations in hydraulic gradient. From this analysis, it appears that longer stalactites tend to occur in comparatively lower ceiling elevation, which, we hypothesize, represents greater mass of water in the limestone above the roof of the cave. We also investigate the relationship between stalactite distribution and ceiling features such as fractures. We apply this to identify different types of possible flow patterns such as matrix flow and fracture flow. This analysis demonstrates a spatial variability, with one site having linear groups of stalactites and another site mostly dominated by stalactite clusters.

Automated registration of potential locations for solar energy production with Light Detection And Ranging (LiDAR) and small format photogrammetry

Energy production and consumption is a key element in future development which is influenced both by the technical possibilities available and by decision makers. Sustainability issues are closely linked in with energy policy, given the desire to increase the proportion of renewable energy. According to the Horizon 2020 climate and energy package, European Union (EU) member countries have to reduce the amount of greenhouse gases they emit by 20%, to increase the proportion of renewable energy to 20% and to improve energy efficiency by 20% by 2020. In this study we aim to assess the opportunities available to exploit solar radiation on roofs with Light Detection And Ranging (LiDAR) and photogrammetry techniques. The surveyed area was in Debrecen, the second largest city in Hungary. An aerial LiDAR survey was conducted with a density of 12 points/m2, over a 7 × 1.8 km wide band. We extracted the building and roof models of the buildings from the point cloud. Furthermore, we applied a low-cost drone (DJI Phantom with a GoPro camera) in a smaller area of the LiDAR survey and also created a 3D model: buildings and roof planes were identified with multiresolution segmentation of the digital surface models (DSM) and orthophoto coverages. Building heights and building geometry were also extracted and validated in field surveys. 50 buildings were chosen for the geodetic survey and the results of the accuracy assessment were extrapolated to other buildings; in addition to this, 100 building heights were measured. We focused primarily on the roofs, as these surfaces offer possible locations for thermal and photovoltaic equipment. We determined the slope and aspect of roof planes and calculated the incoming solar energy according to roof planes before comparing the results of the point cloud processing of LiDAR data and the segmentation of DSMs. Extracted roof geometries showed varying degrees of accuracy: the research proved that LiDAR-based roof-modelling is the best choice in residential areas, but the results of the drone survey did not differ significantly. Generally, both approaches can be applied, because the solar radiation values calculated were similar. The aerial techniques combined with the multiresolution processing demonstrated can provide a valuable tool to estimate potential solar energy.

Fault‐Slip Distribution of the 1999Mw 7.1 Hector Mine Earthquake, California, Estimated from Postearthquake Airborne LiDAR Data

The 16 October 1999 Hector Mine earthquake (M_w 7.1) was the first large earthquake for which postearthquake airborne Light Detection and Ranging (LiDAR) data were collected to image the fault surface rupture. In this work, we present measurements of both vertical and horizontal slip along the entire surface rupture of this earthquake based on airborne LiDAR data acquired in April 2000. We examine the details of the along‐fault slip distribution of this earthquake based on 255 horizontal and 85 vertical displacements using a 0.5 m digital elevation model derived from the LiDAR imagery. The slip measurements based on the LiDAR dataset are highest in the epicentral region, and taper in both directions, consistent with earlier findings by other works. The maximum dextral displacement measured from LiDAR imagery is 6.60±1.10 m, located about 700 m south of the highest field measurement (5.25±0.85 m). Our results also illustrate the difficulty in resolving displacements smaller than 1 m using LiDAR imagery alone. We analyze slip variation to see if it is affected by rock type and whether variations are statistically significant. This study demonstrates that a postearthquake airborne LiDAR survey can produce an along‐fault horizontal and vertical offset distribution plot of a quality comparable to a reconnaissance field survey. Although LiDAR data can provide a higher sampling density and enable rapid data analysis for documenting slip distributions, we find that, relative to field methods, it has a limited ability to resolve slip that is distributed over several fault strands across a zone. We recommend a combined approach that merges field observation with LiDAR analysis, so that the best attributes of both quantitative topographic and geological insight are utilized in concert to make best estimates of offsets and their uncertainties.

Evaluation of Internal Structure, Volume and Mass of Glacial Bodies by Integrated LiDAR and Ground Penetrating Radar Surveys: The Case Study of Canin Eastern Glacieret (Julian Alps, Italy)

We propose an integrated methodology to image the internal structure, evaluate the volume and estimate the densities of different units within ice bodies, useful for more precise mass estimation of very small glaciers. The procedure encompasses light detection and ranging (LiDAR) and ground penetrating radar (GPR) common offset data. The case study is the Canin Eastern Glacieret (CEG), a very small and maritime glacier in the Eastern Alps, and one of the lowermost glaciers of the European Alps. We calculate both volumetric and mass variations of the analysed ice body by integrating GPR measurements with LiDAR surveys acquired in different years (2006 and 2011). Between 2006 and 2011, the area of the glacieret increased from 8,510 to 17,530 m2 with a gain of 9,016 m2. The observed volume increase has been estimated in 96,350 m3 (+97 %), which corresponds to a positive mass balance of 3.89 m w.e.. This quite unusual finding in the present global warming behaviour is mainly due to the above-average winter accumulation (cw) in the considered period. Moreover, the winter season 2008–2009 represented an exceptional event with a cw equal to 13.38 m, the highest of the available record. Thanks to density estimation, we infer the total mass of the CEG at the time of the geophysical surveys, comparing such results with the ones obtained with available empirical equations, observing an important mass gain in the 5 years considered.

Developing sub 5-m LiDAR DEMs for forested sections of the Alpine and Hope faults, South Island, New Zealand: Implications for structural interpretations

Kilometre-wide airborne light detection and ranging (LiDAR) surveys were collected along portions of the Alpine and Hope faults in New Zealand to assess the potential for generating sub 5-m bare earth digital elevation models (DEMs) from ground return data in areas of dense rainforest (bush) cover as an aid to mapping these faults. The 34-km long Franz-Whataroa LiDAR survey was flown along the densely-vegetated central-most portion of the transpressive Alpine Fault. Six closely spaced flight lines (200 m apart) yielded survey coverage with double overlap of swath collection, which was considered necessary due to the low density of ground returns (0.16 m−2 or a point every 6 m2) under mature West Coast podocarp-broadleaf rainforest. This average point spacing (∼2.5 m) allowed for the generation of a robust, high quality 3-m bare earth DEM. The DEM confirmed the zigzagged form of the surface trace of the Alpine Fault in this area, originally recognised by Norris and Cooper (1995, 1997) and highlights that the surface strike variations are more variant than previously mapped. The 29-km long Hurunui-Hope LiDAR survey was flown east of the Main Divide of the Southern Alps along the dextral-slip Hope Fault, where the terrain is characterised by lower rainfall and more open beech forest. Flight line spacings of ∼275 m were used to generate a DEM from the ground return data. The average ground return values under beech forest were 0.27 m−2 and yielded an estimated cell size suitable for a 2-m DEM. In both cases the LiDAR revealed unprecedented views of the surface geomorphology of these active faults. Lessons learned from our survey methodologies can be employed to plan cost-effective, high-gain airborne surveys to yield bare earth DEMs underneath vegetated terrain and multi-storeyed canopies from densely forested environments across New Zealand and worldwide.

Impact of cement repointing on rates of sandstone decay in medieval churches of the French Massif Central

Abstract Three Romanesque churches of the Bourbonnais region in the French Massif Central have been investigated. These date back to the twelfth century, and are mainly built of red and white sandstones. Their ashlar blocks were extensively repointed in the mid-twentieth century with cement-rich mortar. In order to quantitatively assess the impact of repointing on the decay rates of the sandstones, the following methods have been used: dating of reference surfaces (‘zero datum levels’) based on stone-dressing marks, stone-by-stone and terrestrial LiDAR (Light Detection And Ranging) surveys, and petrographical analyses including on-site non-destructive tests. This study reveals that, between the twelfth century and the mid-twentieth century, intrinsic geological factors have been a key control on weathering rates. Stone surface recession has proceeded, on average, 500 times faster in the poorly cemented soft white sandstone compared to the iron-cemented red sandstone (4 mm/century v. 0.008 mm/century). Since the mid-twentieth century, the replacement of the original lime mortar with a cement-rich mortar has resulted in a marked increase in weathering rates and resulting surface recession of the poorly cemented white sandstone: this increase is fivefold where cement-lime mortar (‘bastard mortar’) has been used and 10-fold where harder cement-rich mortar has been applied. By contrast, the application of cement-lime mortar between the ashlars composed of iron-cemented red sandstone had no deleterious effects. This study confirms that the use of cement-based mortar should be avoided on soft and porous masonries. It also stresses the fact that accelerated stone surface recession rates are systematically associated with heritage sites that are subject to significant anthropogenic effects caused by inappropriate interventions or excessive pressure on the monuments or their environment.

Evaluation of short-term geomorphic changes along the Tagliamento river using LiDAR and terrestrial laser scanner surveys

In the recent years a change in the predominant morphology of several river environments has taken place, consisting in a reduction of the braided pattern in favor to wandering or straight configurations. This evolution seems to be due, according to the scientific community, to anthropic causes and, in particular, to the alteration of flow regimes as well as the reduction of sediment transport. Braided rivers are characterized by two or more active channels, separated by bars and fluvial islands and normally feature a high morphological dynamism. This dynamism is the result of the interaction among different elements as sediment supply, flow regime and in-channel and perifluvial vegetation. These factors have a fundamental role in the erosion and deposition processes which are the basis of the morphological changes. The aims of this study are the assessment of the short period geomorphic and volumetric changes occurred along a reach of the Tagliamento River and the comparison between the results obtained from LiDAR (Light Detection and Ranging) and TLS (Terrestrial Laser Scanner) data. The Tagliamento river is a natural gravel-bed river located in the NE of Italy, characterized by a relatively low degree of human disturbances. The analyses were carried out considering two different scales (a reach of about 430 ha and a sub-reach of about 25 ha) and were based on two subsequent datasets in order to investigate the shortterm geomorphic changes due to eight significant floods. The surveys were performed using two different datasets derived from LiDAR and TLS technologies and used to analyze the reach and sub-reach respectively. The short-term estimates of geomorphic and volumetric changes were performed using DEMs of Difference (DoD) based on a Fuzzy Inference System. The results have confirmed the high dynamism of the Tagliamento river, estimating a prevalent deposition at reach and a predominant erosion at sub-reach levels. Finally, a comparative qualitative assessment of the output derived from the different data sources was performed, showing little differences between the two survey methods that proved to be both precise and reliable.

Evaluation of short-term geomorphic changes along the Tagliamento river using LiDAR and terrestrial laser scanner surveys

In the recent years a change in the predominant morphology of several river environments has taken place, consisting in a reduction of the braided pattern in favor to wandering or straight configurations. This evolution seems to be due, according to the scientific community, to anthropic causes and, in particular, to the alteration of flow regimes as well as the reduction of sediment transport. Braided rivers are characterized by two or more active channels, separated by bars and fluvial islands and normally feature a high morphological dynamism. This dynamism is the result of the interaction among different elements as sediment supply, flow regime and in-channel and perifluvial vegetation. These factors have a fundamental role in the erosion and deposition processes which are the basis of the morphological changes. The aims of this study are the assessment of the short period geomorphic and volumetric changes occurred along a reach of the Tagliamento River and the comparison between the results obtained from LiDAR (Light Detection and Ranging) and TLS (Terrestrial Laser Scanner) data. The Tagliamento river is a natural gravel-bed river located in the NE of Italy, characterized by a relatively low degree of human disturbances. The analyses were carried out considering two different scales (a reach of about 430 ha and a sub-reach of about 25 ha) and were based on two subsequent datasets in order to investigate the shortterm geomorphic changes due to eight significant floods. The surveys were performed using two different datasets derived from LiDAR and TLS technologies and used to analyze the reach and sub-reach respectively. The short-term estimates of geomorphic and volumetric changes were performed using DEMs of Difference (DoD) based on a Fuzzy Inference System. The results have confirmed the high dynamism of the Tagliamento river, estimating a prevalent deposition at reach and a predominant erosion at sub-reach levels. Finally, a comparative qualitative assessment of the output derived from the different data sources was performed, showing little differences between the two survey methods that proved to be both precise and reliable.

Maps of soil subsidence for Tokyo bay shore areas liquefied in the March 11th, 2011 off the Pacific Coast of Tohoku Earthquake

The March 11th, 2011 Off the Pacific Coast of Tohoku Earthquake, also known as the Great East Japan Earthquake, has shown that a long stretch of landfills along northeastern shorelines of the Tokyo Bay had very high susceptibility to liquefaction, causing concerns about re-liquefactions of the area in the scenario earthquake expected in the capital's metropolitan area. An attempt was made to detect soil subsidence from raster images converted from airborne LiDAR (Light Detection and Ranging) data before and after the earthquake. To eliminate deep-seated tectonic displacements and systematic errors of LiDAR surveys, the template matching technique is used for clusters of pile-supported buildings and bridge piers chosen as templates in source images of the target areas. The obtained subsidence maps describe the spatial distribution of soil subsidence in great detail.

Automated bare earth extraction technique for complex topography in light detection and ranging surveys

Bare earth extraction is an important component to light detection and ranging (LiDAR) data analysis in terms of terrain classification. The challenge in providing accurate digital surface models is augmented when there is diverse topography within the data set or complex combinations of vegetation and built structures. Few existing algorithms can handle substantial terrain diversity without significant editing or user interaction. This effort presents a newly developed methodology that provides a flexible, adaptable tool capable of integrating multiple LiDAR data attributes for an accurate terrain assessment. The terrain extraction and segmentation (TEXAS) approach uses a third-order spatial derivative for each point in the digital surface model to determine the curvature of the terrain rather than rely solely on the slope. The utilization of the curvature has shown to successfully preserve ground points in areas of steep terrain as they typically exhibit low curvature. Within the framework of TEXAS, the contiguous sets of points with low curvatures are grouped into regions using an edge-based segmentation method. The process does not require any user inputs and is completely data driven. This technique was tested on a variety of existing LiDAR surveys, each with varying levels of topographic complexity.

Using airborne LiDAR and USGS DEM data for assessing rock glaciers and glaciers

Varying topographic and geologic conditions affect the location of rock glaciers. Despite being found worldwide, rock glaciers are often confused with glacier counterparts or other periglacial landforms. Light detection and ranging (LiDAR) data, because of its accuracy and resolution, may help the assessment of topographic variables needed to form rock glaciers or help reveal unique characteristics to enhance regional, automatic mapping. The objectives of this paper are to compare the elevation, slope, aspect, hillshade, and curvature for 1m LiDAR and 10m US Geological Survey (USGS) Digital Elevation Models (DEMs) from the Andrews and Taylor Glaciers with the Taylor Rock Glacier in Colorado. The utility of these data sources will be assessed for landform discrimination and to evaluate the uncertainty between the DEMs. According to the LiDAR data, the Taylor Rock Glacier exists at a lower elevation and has a gentler slope compared to the glaciers. Each landform has steep areas from which snow and debris are delivered. The Andrews Glacier has the most northern aspect, which helps maintain it through snow accumulation and reduced insolation. Glaciers exhibit a concave mean curvature, whereas the Taylor Rock Glacier has a convex mean curvature. The fine resolution of the LiDAR data clearly identifies some distinct characteristics. On the Taylor Rock Glacier, ridges, furrows, and a pronounced front slope were easily identifiable on the LiDAR DEM, whereas crevasses, the boundary between snow and debris covered surfaces, and a lateral moraine were detectable near the Andrews Glacier. The accuracy assessment revealed that at a common 10m resolution, the USGS DEM estimated a maximum elevation about 150m greater compared to the LiDAR data in areas of rugged topography surrounding the landforms. A comparison of root mean squared errors (RMSE) between the LiDAR and USGS DEMs showed that the Taylor Rock Glacier has the lowest RMSE for the elevation and the curvature variables. As a result, readily available USGS DEMs may better for analysis to characterize the topographic setting of landforms at the regional scale. At the fine scale, however, the micro-topography of rock glaciers is illuminated much more clearly on the LiDAR data, making it an ideal, yet costly source, for feature extraction.

Using LiDAR to reconstruct the history of a coastal environment influenced by legacy mining

LiDAR (light detection and ranging) data can be used to create fine digital elevation and bathymetric models (DEMs). Here we examine natural coastal erosion in Grand Traverse Bay, Michigan, a part of Keweenaw Bay in Lake Superior, and discuss how a variety of geological features (submersed river bed and channels associated with the Houghton Low; Nipissing dunes) interact with long-term sediment accumulation patterns. The geological features also modify migrating tailings from a legacy mining site. The combination of LiDAR derived images and aerial photographs allowed us to reconstruct the historical movement of tailings along the coastline. A total of 22.8million metric tonnes (Mt) of stamp sand were discharged into the coastal environment off Gay, MI. Over a span of 80years, beaches to the southwest of Gay have progressively received 7.0Mt (30.7%) of the mass eroded from the original pile, whereas 11.1Mt (48.7%) have moved into the bay. The total amount accumulated along the beaches now greatly exceeds the mass remaining on the original tailings pile (3.7Mt; 16.2%). Bathymetric differences between two LiDAR surveys (2008 and 2010) were also used to estimate the mass, and to track the movement of migrating underwater stamp sand bars. These bars are moving southwesterly towards Buffalo Reef, creating a threat to the lake trout and lake whitefish breeding ground.

GNSS-based monitoring and mapping of shoreline position in support of planning and management of Matinhos/PR (Brazil)

Monitoring and mapping variations in shoreline location is an activity that can be undertaken using several different techniques of data collection, e.g., photogrammetric restitution, satellite images, LiDAR (Light Detection and Ranging) or classical topographical surveys to support coastal environmental protection such as identifying flood risk areas. The global navigation satellite system (GNSS) has been employed by the Federal University of Parana (UFPR) as part of their research into the application of geodetic survey methods for shoreline mapping in coastal environments since 1996. The advantages of using GNSS are accuracy and productivity, given that a great number of points can be determined within a short period of time at decimeterlevel accuracy. In this work, GNSS relative kinematic positioning approach was applied to monitor Matinhos coastal district of Brazil. Other important data, such as the highand low-tide marks, all obtained using GNSS, and thematic maps have also been incorporated. Through the reanalysis of historical surveys, it is possible to make some conclusions about the shoreline dynamics and to use this information as material in support of the planning and management of the coastal environment, for example, when planning engineering works that set out to minimize coastal erosion and for urban planning. The results achieved in this work include defining the position of the shoreline for 2008, developing the thematic map of the shoreline, the quantification of the advance and retreat of the shoreline between 2001 and 2008, and a map showing those critical areas where the shoreline position is equal to the high-tide water line. GNSS-based method offers quicker, all-weather, highly accurate and continuously updatable shoreline positional time series relevant for monitoring, thus enabling quicker management decisions to be undertaken, which may be of benefit to coastal engineering applications.

Integrating LiDAR data and conventional mapping of the Fort Center site in south-central Florida: A comparative approach

Publicly available LiDAR (Light Detection and Ranging) data provide a potential windfall for archaeologists, permitting the creation of detailed topographic site maps with little more than an internet-connected computer and appropriate software. The quality of these LiDAR data for site mapping is variable, however, and may need to be supplemented with data obtained from conventional mapping techniques. We share insights from recent mapping of the Fort Center site (8GL13) in southern Florida. Specifically, we suggest a method—based on trial and error—for integrating LiDAR and total station survey data. We compare the results of our work with previous efforts at mapping the site based solely on conventional archaeological survey methods, as well as with results based on LiDAR data alone. We conclude that our combination of LiDAR data, corrected by conventional survey data, produces the most accurate map.

A simple method to recover the latency time of tactical grade IMU systems

This paper investigates the problem of latency estimation between an IMU (Inertial Measurement Unit) and a LiDAR (Light Detection And Ranging). The latency is due to the IMU itself, but also to the acquisition software and hardware configuration, which is generally set-up by survey systems users. We propose a method for latency estimation, and we show that this method meets the accuracy requirements of most LiDAR survey applications. We present test results of our method on various acquisition systems and hardware configuration which demonstrate that it is able to identify very accurately the total IMU–LiDAR latency through a simple procedure. The principle of the method is to put the LiDAR–IMU in rotational motions, thanks to a rotating table. By scanning a spherical target at different angular velocities, we can observe position shifts of the target center from which we derive an estimate the IMU–LiDAR latency. The method we propose works without absolute positioning and is therefore not sensitive to nonmodeled errors coming from GPS geolocated data. We show that in estimating accurately the LiDAR–IMU latency, we can optimize the configuration of a mobile LiDAR survey system in order to enhance its robustness with respect to high motion dynamics of the survey platform.

Influence of cell size on volume calculation using digital terrain models: A case of coastal dune fields

In this work, we analyze how variation in cell size influences the volume calculated from digital terrain models (DTMs) derived from a LiDAR (light detection and ranging) survey in two coastal Late Holocene dune fields in southern Brazil. Cell size varied from 1 to 100m. RMSE (root mean square error) of the resampled DTMs from the original LiDAR (with 0.5m resolution) increases linearly with cell size, while R2 (coefficient of determination) decreases following a second-order trend. The volume does not show simple linear or exponential behavior, but fluctuates with positive and negative deviations from the original DTM. This can be explained by a random factor in the position of the cell with regard to landforms and a relationship between cell and landform size, wherein a small change in cell size can lead to an under- or overestimation of volume. The ASTER GDEM (global digital elevation model) and X-SAR SRTM (Shuttle Radar Topography Mission) 1″ digital elevation models (DEMs) were not considered viable volume sources due to large deviations from the reference data, either as a consequence of noise in the SRTM X-SAR data or lack of bias elevation correction to a common reference base in the GDEM processing chain. Volumes from a 3-arcsec SIR-C SRTM deviated around ±5% from the reference data and are considered suitable input for numerical simulations of Quaternary dune field evolution models because these values should be within the expected range of sediment volume changes over hundreds to millions of years.

Rapid Determination of Near-Fault Earthquake Deformation Using Differential LiDAR

Improved near‐field measurements of earthquake slip and deformation patterns have the potential for expanding our understanding of fault behavior and the relationship of active faulting to topography. Current techniques for obtaining these measurements—including field observation, Global Navigation Satellite Systems displacement estimation, and optical or radar remote sensing—have limitations that can be mitigated by the inclusion of results from differential airborne Light Detection and Ranging (LiDAR) analysis of the rupture zone. The 2005 airborne LiDAR survey of the southern San Andreas, San Jacinto, and Banning faults (the B4 survey) mapped 1100 km of the most seismically active fault systems in southern California for the purpose of providing a baseline for determining slip from a future earthquake. We used the B4 survey to develop a processing algorithm that yields rapid estimates of near‐fault ground deformation using simultaneous cross correlation of both topography and backscatter intensity from pre‐earthquake and simulated postearthquake LiDAR datasets. We show robust recovery of the direction and magnitude of an applied synthetic slip of 5 m in the horizontal and 0.5 m in the vertical within our area of study, with clear discrimination between areas with and without applied slip. We also successfully recovered more complex deformation from a modeled fault stepover in the same study area. Our results indicate that we should be able to recover slip to accuracies of better than 20 cm in the horizontal and 1 cm in the vertical, at a spatial resolution of ≤15 m for LiDAR datasets with sample densities as low as 0.5 points/m2.