LiDAR Digital Elevation Model Research Articles

Lidar DEM and Computational Mesh Grid Resolutions Modify Roughness in 2D Hydrodynamic Models

AbstractTopography and the computational mesh grid are fundamental inputs to all two‐dimensional (2D) hydrodynamic models, however their resolutions are often arbitrarily selected based on data availability. With the increasing use of drone technology, the end user can collect topographic data down to centimeter‐scale resolution. With this advancement comes the responsibility of choosing a resolution. In this study, we investigated how the choice of mesh grid and digital elevation model (DEM) resolutions affect 2D hydrodynamic modeling results, specifically water depths, velocities, and inundation extent. We made pairwise comparisons between simulations from a 2D HEC‐RAS model with varying mesh grid resolutions (1 and 2 m) and drone‐based lidar DEM resolutions (0.1, 0.25, 0.5, 1, and 2 m) over a 1.5 km reach of Stroubles Creek in Blacksburg, Virginia. The model was rerun for up to ±4% change in floodplain roughness to determine how the DEM and mesh grid changes relate to an equivalent change in roughness. We found that the modeled differences from resolution change were equivalent to altering floodplain roughness by up to 12% for depths and 44% for velocities. The largest differences in velocity were concentrated at the channel‐floodplain interface, whereas differences in depth occurred laterally throughout the floodplain and were not correlated with lidar ground point density. We also found that the inundation boundary is dependent on the DEM resolution. Our results suggest that modelers should carefully consider what resolution best represents the terrain while also resolving important riparian topographic features.

Age and origin of closed depressions in the Paris Basin: A majority of marl pits dug since the Neolithic period?

Marling (limestone alkaline amendment) agrarian practices have a plurimillennial influence on soil pH and on soil-associated ecosystems. Although the earliest written records in Europe date back to antiquity, the origin of this agrarian practice is not well known. In order to trace the evolution of this practice in the early agrarian societies of Western Europe, we searched for topographic anomalies of ancient limestone quarries that may have been used for marling. Four hundred circular closed topographic depressions (CDs) were identified under two areas of ancient forest in northern France with Lidar digital elevation models (DEMs). Soils, morphology and archaeological context were studied and filling sediments were dated in several dozen CDs.The gaps in the carbonate rocks, soils with calcaric properties (scattered limestone fragments), unstratified fills, the absence of buried paleosols, and dates (OSL, C-14) later than the first local agricultural societies made it possible to recognise the CDs that may have served as limestone quarries. This was the case for most of the 30 CDs studied, leaving a minority of natural origin (suffosion, depressions of thermokarstic origins). Amongst the quarries identified, the preferential excavation of soft (friable) limestone and the location of these quarries in fossil agrarian plots led us to hypothesize that they were used for alkaline amendments of the cultivated fields. The quarries were filled from the Middle Neolithic to Late Antiquity, shortly before the period of afforestation of these former agrarian territories.

Coastal Compound Flood Simulation through Coupled Multidimensional Modeling Framework

Coastal watersheds are prone to compound flooding caused by heavy rainfall, storm surge, and high tide. Accurate prediction and modeling of coastal compound floods (CCF) require precise physical representation in numerical models with appropriate numerical approximation associated with multi-driver physical processes for simulating the flood dynamics. To address this, an integrated and tightly coupled modeling approach is implemented to capture the nonlinear and complex processes involved in CCF and interconnectivity among Multidimensional Hydraulics (pipe and channel), Hydrodynamics (2D overland flow), and distributed Hydrologic (MH3) models are developed. The coupled modeling framework focuses on the development of interconnected meshes of the node-link-basin using the Interconnected Channel and Pond Routing (ICPR) model. This framework effectively incorporates the complex drainage network system of tidal creeks, tidal channels, underground sewer networks, and detention ponds of the Charleston Peninsula of South Carolina (SC). The dynamics of the urbanized floodplain in the peninsula are represented using high-resolution LiDAR-derived Digital Elevation Model (DEM) and Digital Surface Model (DSM). The overland flow is simulated using energy balance, momentum balance, and diffusive wave methods. The performance of the CCF model is tested for the 2015 SC historical flood and a high tide flood event. The momentum balance-based CCF model shows 98.35% accuracy in identifying street-level flooding locations. Furthermore, the model shows that incorporating DSM processing in the current study improves the accuracy of urban flood simulation by approximately 15% to 33% compared to LiDAR DEM. It is revealed that the momentum balance method outperforms to simulate the flood dynamics. Consequently, this study contributes to the modeling of CCF by developing an integrated MH3 system that enhances the physical representation of coastal hydrology at a fine scale.

Shoreline classification maps and ground truth data for the Neuse River Estuary, North Carolina

Estuaries provide essential ecosystem services and economic value but are facing widespread degradation due to changing anthropogenic and climatic factors. In North Carolina, coastal structures, like bulkheads and riprap, are widely used by property owners throughout the Albemarle-Pamlico estuary to stop erosion and reclaim lost land following storm events. While coastal development is tightly governed, limited historical and no up-to-date data report on the spatial distribution of coastal structures throughout the Albemarle-Pamlico estuary. Here we describe the development of a dataset that classifies and catalogues 67 km of shoreline type along the Neuse River Estuary (NRE), a large tributary of the Albemarle-Pamlico. We used available LiDAR digital elevation models (DEMs), aerial imagery, and a ground truthing field campaign to determine shoreline type present along the NRE as of 2020. We validated these results using an intensive manual editing procedure that comparatively examines DEMs, LiDAR derived slope, aerial imagery, and ground truth photography of the shoreline. This dataset is available for public download.

Geomorphology of the upper sector of the Roncovetro active landslide (Emilia-Romagna Region, Italy)

ABSTRACT We present the geomorphological map of the upper sector of the Roncovetro active landslide (Enza Valley, Emilia-Romagna, Italy). The 1:1500 scale map provides an accurate picture of the landslide in October 2014. The map is mainly based on the data collected during an airborne LiDAR survey. The capability of LiDAR to ‘penetrate’ the vegetation cover makes these data the most complete and accurate topographic dataset of this landslide. The map shows that the upper sector of the Roncovetro landslide consists of gravity- and water runoff-related forms. Gravitational features are linked to sliding and flowing movements that characterize the short- and long-term behaviour of the landslide. By comparing the 2014 LiDAR-Digital Elevation Model (DEM) with the 1973 DEM provided by the Emilia-Romagna Region, we calculated that 6.2 ± 0.8 × 105 m3 of material has moved from the top of the Roncovetro landslide in about 40 years.

Bridging the gap between airborne and spaceborne imaging spectroscopy for mountain glacier surface property retrievals

Observations of glacier albedo are sparse, despite being a first-order control on net solar radiation and melt rates. Recent and forthcoming airborne and satellite imaging spectrometer missions increase our ability to record changes in albedo over time and space but will require an understanding of uncertainties, especially in areas of rugged terrain. Some of these uncertainties arise from the timing of acquisition and resolution of digital elevation models (DEM) that are used for topographic correction. We use the fine-resolution data (2 m) from the Airborne Coastal Observatory (ACO), an imaging spectroscopy and lidar remote sensing platform, to quantify the expected error from other airborne and satellite scale platforms. First, we describe our retrieval workflow - the Imaging Spectroscopy Snow and Ice Algorithm (ISSIA) that yields spatial retrievals of broadband albedo (BBA), optical grain size, and radiative forcing by light absorbing particles (RFLAP) using the coincident 2 m lidar DEM over mountain glaciers. We use two acquisitions over Place Glacier, British Columbia, Canada that represent typical spring and summer conditions as a baseline from which synthetic datasets were generated to represent data from coarser-scale imaging spectroscopy platforms. Each synthetic dataset was motivated by specific airborne and satellite platform scenarios and quantifies four sources of error: (1) DEM spatial resolution and elevation accuracy, (2) coincident vs non-coincident DEM collection, (3) imagery spatial resolution, and (4) spectral resolution. Use of a 30 m DEM introduced the most error in steep mountain terrain, which primarily increased error in the BBA and RFLAP retrievals. The timing of DEM acquisition mattered most for high-resolution imagery and in areas surrounding the glacier toe where mass loss occurred more rapidly. Coarse-resolution imagery did not fully capture spatial variability in surface properties and topography, which lowered variance and increased overall errors. Coarsening of spectral resolution from 5 nm to 10 nm had minimal impact on surface property retrieval and associated errors were independent of DEM or imagery resolution. A simple energy analysis showed that surface albedo error, due to topographic correction with coarse and non-coincident DEMs, resulted in melt rate errors ranging from 6 to 20% for airborne and 11–20% for satellite scenarios.

Research on Landslide Trace Recognition by Fusing UAV-Based LiDAR DEM Multi-Feature Information

Landslide traces are crucial geomorphological features of landslides. Through the recognition of landslide traces, a better grasp of the topographical features of landslides can be achieved, thereby aiding in the enhancement of capabilities for the prevention, response, and management of landslides. Aiming at the complex topographic features of landslide traces, only using a single DEM product could provide a complete and comprehensive recognition of landslide traces. A method of landslide tracing recognition based on the fusion of multi-feature information from the Unmanned Aerial Vehicle-based Light Detection and Ranging (UAV-based LiDAR) Digital Elevation Model (DEM) is proposed. First, a high-precision DEM is constructed by using the LiDAR point cloud data. Based on the DEM, four multi-feature images that can enhance the landslide geomorphology are generated: hillshading, slope, positive openness, and sky-view factor. Furtherore, the DEM multi-feature images were fused using the Visualization for Archaeological Topography (VAT) method to obtain the DEM Multi-Feature Fusion Image (DEM-DFFI). Finally, the landslide traces were extracted from the DEM-DFFI based on fractal theory. The method presented in this paper makes full use of DEM multi-feature images and fuses them, which can accurately and clearly show the topographic and geomorphological features of landslides. Based on this, it helps improve landslide trace recognition accuracy.

Human impacts on infilling rates of hollows in landslide‐prone areas of western Japan: Estimation from radiocarbon dates and high‐resolution DEMs

AbstractThe infilling rate of hollows is one of the primary factors affecting the recurrence interval of shallow landslides. Although many studies have focused on colluvium in hollows under various regional settings, few have directly estimated the infilling rates from radiocarbon dating and airborne LIDAR digital elevation models (DEMs) in shallow landslide scars. In this work, we analysed the radiocarbon dates of charcoal in the colluvium in the granitic mountains of Hiroshima and Hofu, where heavy rainfall has caused multiple shallow landslides in recent years. A total of 27 samples were collected from landslide scars in seven hollows, and the infilling rates were inferred from the calibrated radiocarbon ages and pre‐landslide depth of the samples estimated from the DEMs before the landslide event. Topographic parameters including local slope gradient and size of the source area were also measured using the DEMs. Our findings showed that the calibrated radiocarbon ages of colluvium in hollows ranged from about 350 to 1700 cal BP, and the infilling rates ranged from about 0.2 ± 0.2 to 5.4 ± 0.9 mm/y. In the two hollows with limited human impacts, the infilling rates were relatively low, and there is a trend of increase with increasing source‐area size and topographic curvature. In contrast, infilling rates were very high at two hollows with intensive human impacts where active surface erosion occurred from the 17th to the early 20th century. Three hollows located around the ruins of a medieval castle near the drainage divides of the source area also had relatively high infilling rates. For the hollows with intensive human impacts, the infilling rates were not controlled by topographic attributes such as source‐area size and curvature.

Aerial characterization of surface depressions in urban watersheds

Digital elevation models (DEM) are one of the most fundamental inputs for hydrological modeling. It has been a common practice to remove all surface depressions in a DEM as they are assumed to be data errors. The emerging technology of unmanned aircraft systems (UAS) provides an opportunity to re-examine this assumption at the hyperspatial resolution. This study was the first attempt to characterize small surface depressions in urban environments using UAS imagery. Using an urban area in south Texas as the study site, UAS flights were conducted to yield hybrid DEMs at the resolution of 8–14 cm, coupled with comprehensive ground truth collection. Surface depressions identified from the UAS DEMs were first corrected based on the vertical accuracy of DEMs and then validated through field surveys, with comparisons to two existing LiDAR DEMs (1-m and 10-m). The hydrological impacts of different DEM-derived estimates of catchment depression storage were examined using the Curve Number method across different design storms. Results show that the UAS DEMs outperformed the LiDAR DEMs in describing the microtopographic control of urban overland flow and associated hydrological connectivity across built and natural features. The 8-cm UAS DEM revealed 926% more depression storage than the 10-m LiDAR DEM. This demonstrates a compelling correlation between increasing DEM resolution and enhanced quantification of depression volume. Consequently, the increased depression storage reduced surface runoff by 41% under a two-year design storm and 13% under a 200-year design storm. The results suggest a strong relationship between the DEM resolution and the derived depression estimates, aligning with the fractal nature of watershed systems. Also, the results indicate that the centimeter-level UAS DEMs were not immune from problems. They could yield fake depressions caused by factors such as vegetation, temporary street objects, and underground sewer pipes. The findings of this study suggest the need to quantify the relationships between DEM resolution and associated hydrological attributes and develop new digital drainage analysis algorithms that could effectively incorporate UAS data into urban hydrological modeling.

The influence of roads on depressional storage capacity estimates from high-resolution LiDAR DEMs in a Canadian Prairie agricultural basin

The Canadian Prairies are a post-glacial agricultural landscape, where millions of small depressions store surface water, form wetlands and control runoff contributing area. Their management is key to flood and drought hydrology, groundwater recharge, ecological integrity, migratory bird habitat and agricultural productivity. Depression drainage and infilling is common in the region, where it is often used to increase cropped area. The regularly spaced, rural ‘grid-road‘ network also impedes drainage, but associated culvert drainage can mitigate those effects. Management of depressions can be informed by hydrological modelling, but accurate surface water storage capacity estimates are needed to ensure accurate model results. Simple representation of road embankments in digital elevation models (DEMs) neglects the effects of culvert drainage. Here, a raster-based depression-filling algorithm was used to delineate depressions from three LiDAR-derived DEMs: a 10-m DEM with roads intact, a 2-m DEM with roads intact, and a 2-m DEM with roads breached at culvert locations. Road breaching was conducted manually in the 2-m DEM to remove artifact depressions that form alongside roads where culverts exist. Results indicated that increasing DEM resolution from 10-m to 2-m in a 393.5 km2 basin did not significantly change depression area or storage capacity estimates; however, breaching roads in the 2-m DEM decreased depression area by 29% (from 98.5 km2 to 69.8 km2) and estimated storage capacity by 48% (from 47.4 × 106 m3 to 23.8 × 106 m3), compared to leaving roads intact in the 2-m DEM. Depressions delineated from the 2-m roads-breached DEM also covered 48% more area and offered 53% more storage capacity than Canadian Wetland Inventory (CWI) aerial-photograph delineated wetlands, which occupied 47.1 km2 with an estimated storage capacity of 15.5 × 106 m3. The implications of these results for the ability of hydrological models to calculate runoff contributing areas and streamflow are discussed.

Inherited anthropogenic disturbance and decadal sediment dynamics in a mountain fluvial system: The case of the Marecchia River canyon, Northern Apennines

We evaluate decadal coarse sediment dynamics along the Marecchia River of the Northern Apennines, a fluvial system with a history of gravel mining that led to the incision of a 6-km-long canyon. To this purpose, we subdivided the river into 21 reaches, seen as sediment reservoirs, to examine (1) historical variations in active channel width (1955−2019) in conjunction with (2) change in alluvial sediment storage (2009−2019), by differencing two sequential LiDAR digital elevation models (DEMs) within the active channel footprint. Combined examination of lateral (widening or narrowing) and vertical (aggradation or degradation) channel changes allowed the identification of composite styles of reservoir adjustment, as well as the refinement of geomorphic inference solely based on changes in active channel width. In particular, we find that different styles of decadal adjustment (1) are compatible with supply- and transport-limited conditions, as constrained by degree of confinement, stream channel slope, and active channel width; and (2) indicate different stages of evolution at reservoirs located upstream and downstream of the canyon head (dynamic equilibrium vs. transient response). The persistence of this geomorphic divide is supported over historical time scales by distinctive trends in planform channel changes, suggesting that sedimentary signal propagation downstream becomes abruptly interrupted at the canyon head. Over this 10-year natural experiment, the spatial pattern of erosion along the canyon exemplifies a striking case of transient response to anthropogenic forcing, where decadal topographic change, modulated by varying styles of hillslope-channel coupling, declines nonlinearly downstream. Depth of incision along the canyon increases progressively upstream, suggesting that the canyon head has been evolving toward a more unstable configuration with no significant change in sediment supply. This tendency, which points to a possible runaway style of development as bedload wearing on weak pelitic side walls continues, may hold basic implications for our understanding of channel incision into bedrock and strath terrace formation.

LiDAR DEM and HEC-RAS On-Grid Rainfall Hydrograph Model for Irrigation System

The capacity of the Saddang River Irrigation Canal will be increased by 30% to accommodate long-term irrigation discharge needs. Analysis of the hydraulic model of the irrigation and discharge channels is examined in this study. High resolution LiDAR Digital Elevation and HEC-RAS Model are used to estimate the flow depth and velocities in the event of rain with extreme intensity. HEC-RAS Model solves the 2-D depth-averaged St.Venant equations that are mainly used for river simulation. The HEC-RAS model uses on-grid precipitation hydrograph and flexible meshes that may contain arbitrarily quadrilateral and triangular cells. A hybrid mesh may achieve the best compromise between solution accuracy and computing demand. The HEC-RAS model solved variables include water surface elevation, water depth, depth averaged velocity, Froude number, and bed shear stress. The optimization of the model is useful for improving the drainage modulus, lining channel, drain time period and the performance of the irrigation and drainage channels.

Robbins Island: The index site for regional Last Interglacial sea level, wave climate and the subtropical ridge around Bass Strait, Australia

A unique index-record of Last Interglacial (Marine Isotope Stage 5e MIS5e) relative sea level (RSL) and wave climate history in South-east Australia is presented from Robbins Island, in western Bass Strait. This is applied to interpret the wider MIS5e coastal evidence around Bass Strait. At Robbins Island, the combination of low wave and wind energy, a tide-modified regime and a sand supply resulted in the shoreline progradation throughout MIS5e. This preserved a time-series of paleo-sea level across a 7 km wide strandplain (Remarkable Banks). After a highstand, MIS5e RSL attained a stillstand of +5.75 ± 0.5 m above modern mean sea level during 126 to ∼119 ka BP. The MIS5e RSL interpretation is underpinned by modern analogues and hydrodynamic modelling of waves, tides and currents. A high resolution LiDAR Digital Elevation Model (DEM) supported by morpho-sedimentary studies, ground-penetration radar (GPR) surveys and a geochronology based upon Optically Stimulated Luminescence (OSL) methods were used to define the proxy RSL record. The observed RSL history was compared to modelled RSL history that accounted for the theoretical fall in RSL (regression) throughout MIS5e, due to the Glacio-Isostatic Adjustment (GIA) forcing.

Evaluación del Modelo de Elevación Digital de la Misión Topográfica de Radar en Transbordador (SRTM) en la Macro-Cuenca del Papaloapan, Mexico, usando LiDAR como referencia

The Digital Elevation Model (DEM) from the Shuttle Radar Topography Mission (SRTM) is evaluated using a LiDAR DEM from INEGI as benchmark in the Papaloapan Basin (~58,000km2) in Mexico. Three representative regions are selected: 1) a hilly region with strong slopes and elevations over 3,000m, 2) a transitional region with relatively smoother slopes and elevations around 1,000m, and 3) a floodplain with flat terrain and elevations below 100m. The straight comparison of both datasets shows very similar elevation values at the hilly and transitional regions. However, in the floodplain, the relationship has a parabolic shape, and errors are relatively higher, in terms of the elevation range. This is probably due to systematic errors in SRTM being very close to the actual low elevations. Maps of errors suggest strong association with water bodies and the aspect. For example, in the transitional region, most negative errors are found on slopes facing east, while positive errors are found on slopes facing west. Three-dimensional histograms of errors vs. topographic features (elevation, slope, and aspect) are estimated. The histograms suggest a systematic error, which means SRTM could be improved with a simple calibration at least in these cases. Evaluations of public DEMs from different sources in Mexico are considered necessary for the identification of their strengths and weaknesses. We believe these evaluations might provide the grounds for the creation of improved MEDs in the future either by either a simple calibration or through composite MEDs from multiple sources.

Using Lidar Digital Elevation Models for Reflectometry Land Applications

Lidar elevation maps are utilized in a bistatic electromagnetic scattering model of the Cyclone Global Navigation Satellite System over San Luis Valley in Colorado, USA. The results are compared with results generated using the Shuttle Radar Topography Mission (SRTM) 1 arcsecond global digital elevation model (DEM). The high resolution lidar maps are also used to generate maps of surface roughness at length scales finer than the horizontal resolution of SRTM. Model results using these maps illustrate the importance of the spatial variation of surface roughness on reflectometry signals. Results also highlight the shortcomings of using SRTM in scattering models and show improvements when a lidar DEM is used.

Source Model and Triggered Aseismic Faulting of the 2021 Mw 7.3 Maduo Earthquake Revealed by the UAV-Lidar/Photogrammetry, InSAR, and Field Investigation

Multi-source datasets, including the UAV-Lidar/Photogrammetry, InSAR, and field investigation data, have been used for revealing the complex surface displacement pattern and focal mechanism of the 2021 Maduo Mw 7.3 earthquake. First, a co-seismic surface deformation field was extracted from the Synthetic Aperture Radar (SAR) images captured by ALOS-2 and Sentinel-1 satellites. Second, the SAR pixel offset tracking results were adopted to detect the initial location of the seismogenic fault. Then, the Lidar digital elevation model with high spatial resolution and field investigation were employed to refine and verify the location of the seismogenic fault. It was found that bifurcated strike-slip rupture should account for the 2021 Maduo earthquake. As indicated by the estimated faulting model based on the InSAR data, the maximal fault slip was ~6.2 m, occurring in the southeast of the main seismogenic fault, and five remarkable slip concentrations controlled the surface displacement of the 2021 Maduo earthquake. Furthermore, the co- and post-seismic InSAR deformation, dilatation, shear strain, Coulomb failure stress, and aftershock sequence suggest that the co-seismic rupture of the two main seismogenic faults have triggered the aseismic slip along the Changmahe fault. Lastly, according to the Coulomb failure stress change due to the historical earthquakes and the 2021 Maduo earthquake, the 1937 M 7.8 earthquake predominantly controlled the Coulomb failure stress change along the Kunlun fault, and the Xidatan-Alake Lake and Maqin segments had a higher risk of future earthquake than the other segments.

The impact of terrain model source and resolution on snow avalanche modeling

Abstract. Natural hazard models need accurate digital elevation models (DEMs) to simulate mass movements on real-world terrain. A variety of platforms (terrestrial, drones, aerial, satellite) and sensor technologies (photogrammetry, lidar, interferometric synthetic aperture radar) are used to generate DEMs at a range of spatial resolutions with varying accuracy. As the availability of high-resolution DEMs continues to increase and the cost to produce DEMs continues to fall, hazard modelers must often choose which DEM to use for their modeling. We use satellite photogrammetry and topographic lidar to generate high-resolution DEMs and test the sensitivity of the Rapid Mass Movement Simulation (RAMMS) software to the DEM source and spatial resolution when simulating a large and complex snow avalanche along Milford Road in Aotearoa/New Zealand. Holding the RAMMS parameters constant while adjusting the source and spatial resolution of the DEM reveals how differences in terrain representation between the satellite photogrammetry and topographic lidar DEMs (2 m spatial resolution) affect the reliability of the simulation estimates (e.g., maximum core velocity, powder pressure, runout length, final debris pattern). At the same time, coarser representations of the terrain (5 and 15 m spatial resolution) simulate avalanches that run too far and produce a powder cloud that is too large, though with lower maximum impact pressures, compared to the actual event. The complex nature of the alpine terrain in the avalanche path (steep, rough, rock faces, treeless) makes it a suitable location to specifically test the model sensitivity to digital surface models (DSMs) where both ground and above-ground features on the topography are included in the elevation model. Considering the nature of the snowpack in the path (warm, deep with a steep elevation gradient) lying on a bedrock surface and plunging over a cliff, RAMMS performed well in the challenging conditions when using the high-resolution 2 m lidar DSM, with 99 % of the simulated debris volume located in the documented debris area.

An integrated remote sensing and biomarker maturity parameter-based approach to trace petroleum migration in a complex fault zone lineament of the Brazilian Equatorial Margin

The present paper investigates the oil migration and lineament distribution in fault zones within a sedimentary basin, showcasing the results from an integrated use of geochemical, and remote sensing data along the Fazenda Belém Fault Zone (FBFZ) in the Potiguar Basin, Brazilian Equatorial Margin. Lineaments were detected from a LiDAR digital elevation model data set using the quantitative method of morphology recognition based on horizontal and vertical curvature calculation and mapping. The polynomial regression-based spatial distribution of 20S/(20S + 20R) C29 steranes is successfully used in oils from offshore and onshore reservoirs of the Potiguar Basin, tracing field-scale oil migration direction. These multidisciplinary analyses revealed that the oil initially migrated from an offshore area along the NE-oriented fault zone, and then parts moved along the branches of this zone to finally reach the areas of the onshore reservoirs. In addition, NE-oriented lineaments enhanced the near-surface fluid circulation, while they commonly correspond to the topographic features and fault zones. Anisotropy tensors and slip- and dilation tendency calculated from the lineament map also indicate that the geometric complexity of the lineament pattern is influenced by present-day and partitioned stress fields in the Potiguar Basin. The integration of remote-sensing and geochemistry analyses at the FBFZ area proved to be effective in approaching the tectonic aspects of a fault zone in a petroleum basin, as well as in investigating the field-scale migration of oil along the fracture corridor in a fault zone.

The use of spatial data and satellite information in legal compliance and planning in forest management.

A key part of native forest management in designated wood production areas is identifying locations which must be exempt from logging. Forest laws, government regulations, and codes of practice specify where logging is and is not permitted. Assessing compliance with these regulations is critical but can be expensive and time consuming, especially if it entails field measurements. In some cases, spatial data products may help reduce the costs and increase the transparency of assessing compliance. However, different spatial products can vary in their accuracy and resolution, leading to uncertainty in forest management. We present the results of a detailed case study investigating the compliance of logging operations with laws preventing cutting on slopes exceeding 30°. We focused on two designated water catchments in the Australian State of Victoria which supply water to the city of Melbourne. We compared slopes that had been logged on steep terrain using spatial data based on a Digital Elevation Model (DEM) derived from LiDAR, a 1 arc second DEM derived from the Shuttle Radar Topography Mission, and a Digital Terrain Model (DTM) with a resolution of 10m. While our analyses revealed differences in slope measurements among the different spatial products, all three datasets (and the on-site slope measurements) estimated the occurrence of widespread logging of forests on slopes >30° in both water catchments. We found the lowest resolution Shuttle Radar Topography Mission DEM underestimated the steepness of slopes, whilst the DTM was variable in its estimates. As expected, the LiDAR generated slope calculations provided the best fit with on-site measurements. Our study demonstrates the value of spatial data products in assessing compliance with logging laws and codes of practice. We suggest that LiDAR DEMs, and DTMs also can be useful in proactive forest planning and management by helping better identify which areas should be exempt from cutting before logging operations commence.

Surface drainage features identification using LiDAR DEM smoothing in agriculture area: a study case of Kebumen Regency, Indonesia

ABSTRACT Digital Elevation Model (DEM) is the most vital data to generate drainage networks and to provide critical terrain factors and hydrologic derivatives, such as slope, aspect, and streamflow. The accuracy of generated drainage features is extensively dependent on the quality and resolution of DEM, such as LiDAR-derived DEM. Contrary, it has a high level of roughness and complexity. Thus, smoothing methods are sometimes employed to conquer the roughness. This paper presents feature-preserving DEM smoothing (FPDEM-S) and edge-preserving DEM smoothing (EPDEM-S) approaches to smooth surface complexity in kind of preserving small drainage features using the 0.5 m – resolution LiDAR DEM of the Kedungbener River area in Kebumen Regency, Indonesia. Entangling linear morphometric factors, those smoothing approaches delivered a slight difference of stream number, with the FPDEM-S stream length ratio performing 7% better tendencies. The FPDEM-S method perormed better than EPDEM-S in this study area to provide an optimal smoothed LiDAR DEM at certain parameter values. Summarising that two smoothing methods approaches performed similar characteristics of watershed as an oval structure close to the circular shape. Also, it can be revealed that the watershed did not reach maturity phase.