Resolution Digital Surface Models Research Articles

UAS-based mapping of the July 3, 2019, ballistics density distribution on the W flank of Stromboli with uncertainty quantification

Stromboli is a volcanic island in a persistent state of activity, located off the northern coast of Sicily. The paroxysms have been the most powerful explosive phenomena at Stromboli in the last 150 years. These explosions can produce ballistic projectiles that can heavily affect trails and observation sites as well as hit inhabited areas at lower elevations, down to the coast. On July 3, 2019, a paroxysm significantly affected a great portion of the island with ballistic projectiles. In particular, many decimeter and meter-sized spatter bombs hit the W flank of Stromboli, and ignited multiple fires. In May 2022, we conducted an Unmanned Aerial System photogrammetric campaign over a sector of the W flank of Stromboli that was heavily affected by the paroxysm. The largest clasts were still preserved after 3 years, not disturbed by significant mass wasting phenomena or human interference, and they were not yet hidden by the post-fire regrowth of the brush vegetation. In this study, we constrained the main sources of uncertainty affecting the bombs distribution on the ground, by characterizing a percentage of uncertain clasts, testing various density estimators, and by modeling an areal buffer around the mapped clasts. We produced a 0.18 km2 wide 1.6-cm resolution orthomosaic, a 10-cm resolution Digital Surface Model, and 2813 outlines of the mapped ballistics. Spatial distribution of the ground cover and associated uncertainty were analyzed as a function of the distance and of the angular direction from the source.

Integration of HEC-RAS and HEC-HMS with GIS in Flood Modeling and Flood Hazard Mapping

Floods are among the most devastating disasters in terms of socio-economics and casualties. However, these natural disasters can be managed and their effects can be minimized by flood modeling performed before the occurrence of a flood. In this study, flood modeling was developed for the Göksu River Basin, Mersin, Türkiye. Flood hazard and risk maps were prepared by using GIS, HEC-RAS, and HEC-HMS. In hydraulic modeling, Manning’s n values were obtained from 2018 CORINE data, return period flow rates (Q25, Q50, Q100, Q500) were obtained from HEC-HMS, and the application was carried out on a 5 m resolution digital surface model. In the study area, the water depths could reach up to 10 m, and water speeds were approximately 0.7 m/s. Considering these values and the fact that the study area is an urban area, hazard maps were obtained according to the UK Department for Environment, Food and Rural Affairs (DEFRA) method. The results indicated that possible flood flow rates from Q25 to Q500, from 1191.7 m3/s to 1888.3 m3/s, were detected in the study area with HEC-HMS. Flooding also occurred under conditions of the Q25 flow rate (from 4288 km2 to 5767 km2), and the impacted areas were classified as extremely risky by the DEFRA method.

Detection of Beach–Dune Geomorphic Changes by Means of Satellite and Unmanned Aerial Vehicle Data: The Case of Altamura Island in the Gulf of California

Although sandy islands in arid environments are vital protection sites for endemic species, they face constant natural and anthropogenic hazards, such as storm surge impacts and the occasional presence of off-road vehicles. Monitoring the sedimentary dune-beach displacement and balance is essential because sediment transportation usually does not depend on external sources, such as rivers. The latest generation of geomatic applications may be relevant to understanding coastal vulnerability due to their ability to acquire and process spatial data at unprecedented scales. The objective of this study was to analyze the sedimentary dynamics of a distinctive dune corridor on Altamura Island in the Gulf of California, Mexico. We compared three ultra-high spatial resolution digital surface models (DSMs) with geomorphic change detection (DoD), covering the 1150 m coastal stretch. We used light detection and ranging (LiDAR) data and analyzed changes in the coastline with the semi-automatic CoastSat tool. Although the orthomosaics and the DSM collected in April, June, and October 2021 show different conditions in sediment distribution along the beach-dune interface, depending on the direction and intensity of the wind, the two DoDs showed a constant sediment distribution balance of ~13 M m3 between April and June and June and October. LiDAR data along the 40-km length of the sandy island indicate that the entire island could present a similar sedimentation pattern between the dune and beach interface. The CoastSat data indicate a constant accretion of 125 m in the beach-ocean interface between 2015 and 2022. This study demonstrates that the sediment balance between the dune and the beach on arid sandy islands is vital for conserving their shoreline and all associated coastal ecosystems.

Assessing the short-term inter-annual growth of the largest documented gully network in South Africa using UAV and SfM methodology

ABSTRACT This research explores intra-gully sediment volume changes of a massive gully network (42 ha) located in the Eastern Cape, RSA, in response to high rainfall events during a three-year study period (2017–2020). Unmanned aerial vehicles (UAVs) and photogrammetric processing were used to generate high resolution digital surface models (DSMs). Volumetric calculations were run to estimate the extent of gully expansion within the system to determine intra-gully changes and sediment erosion over the study period. The gully was categorised into four zones based on predominant structure and processes. These are the Extension Zone, Expansion Zone, Transport/Deposition Zone and the Side Branches. Rainfall data from a rainfall station (10 km away) was used to investigate the correlation between rainfall depth, rainfall intensity, and flow accumulation over two wetter years and one drier year with gully expansion experienced during these periods. The gully network encountered a total gully sediment volume erosion of 104,489 m3 (6.01%) over the study period. Nineteen high to extreme intensity (>20 mm per day) rainfall events produced the runoff necessary for gully expansion during the 2017 and 2018 hydrological years. Notably, lower gully growth was recorded in the Expansion and Transport/Deposition Zones during the subsequent below average hydrological year in 2019–2020.

Permafrost degradation in the ice-wedge tundra terrace of Paulatuk Peninsula (Darnley Bay, Canada)

The warming of high latitudes climate is enhancing the degradation of ground-ice and inducing important landscape changes across the Arctic. This new Arctic state affects geomorphological dynamics, hydrology, and ecosystems, and poses challenges to the stability of infrastructure and livelihoods of Arctic communities. This study focuses on the hamlet of Paulatuk within the Inuvialuit Settlement Region of the Amundsen Gulf, south Darnley Bay, in northern Canada. In the summer of 2019, an ultra-high resolution aerial survey with a fixed-wing Unmanned Aerial Vehicle (UAV) was conducted, generating a 5 cm spatial resolution orthomosaic and Digital Surface Model (DSM). These, together with field observations were used to produce a very-high resolution geomorphological map of the settlement and surrounding coastal areas. Landscape changes were analyzed using historical aerial imagery of 1975 and 1993, the 2019 UAV survey and a very-high resolution Pléiades satellite scene from 2020. The area is a tundra terrace made up of sandy fluvioglacial sediments affected by a dense network of ice-wedge polygons, mostly high-centered, but also low-centered, showing signs of permafrost degradation. Air and ground temperatures have increased respectively by 0.8 and 1.9 °C over last two decades at Paulatuk, and inter-polygon ponds surface increased by 23,000 m2 since 1975 due to ice-wedge thawing. The airstrip enhanced thaw pond formation on its margins, especially after 1993. The DSM reveals a depression south of the airstrip, which can be potentially flooded due to its proximity to the coastal waters.

Measuring landslide-driven ground displacements with high-resolution surface models and optical flow

This study proposes and evaluates the performance of two image matching algorithms applied to hillshades derived from consecutive high-resolution digital surface models (DSMs) to measure surface displacements on landslides. The method is applied on Te Horo, a slow-moving landslide in the Dart Valley of New Zealand’s Southern Alps/Kā Tiritiri o te Moana using pairs of hillshades derived from Airborne and Satellite Photogrammetric Mapping (APM/SPM) of imagery captured in 2018 and 2020. This novel approach uses the consistency of displacement predictions generated from multiple hillshade pairs to gauge match quality and mask unreliable displacement predictions. The study compares a widely used normalised cross-correlation algorithm (NCC) alongside an optical flow approach for image matching. The performances of both algorithms are assessed against manually derived displacements of prominent surface features. We demonstrate the effectiveness of the masking approach as well as the good performance of the optical flow algorithm in delivering dense, accurate displacement measurements efficiently, particularly when high resolution DSMs are available. The results show that the main translational body of the landslide was displaced at rates averaging 25–55 mm day−1 over the 2018–2020 period.

Weekly high-resolution multi-spectral and thermal uncrewed-aerial-system mapping of an alpine catchment during summer snowmelt, Niwot Ridge, Colorado

Abstract. Alpine ecosystems are experiencing rapid change as a result of warming temperatures and changes in the quantity, timing and phase of precipitation. This in turn impacts patterns and processes of ecohydrologic connectivity, vegetation productivity and water provision to downstream regions. The fine-scale heterogeneous nature of these environments makes them challenging areas to measure with traditional instrumentation and spatiotemporally coarse satellite imagery. This paper describes the data collection, processing, accuracy assessment and availability of a series of approximately weekly-interval uncrewed-aerial-system (UAS) surveys flown over the Niwot Ridge Long Term Ecological Research site during the 2017 summer-snowmelt season. Visible, near-infrared and thermal-infrared imagery was collected. This unique series of 5–25 cm resolution multi-spectral and thermal orthomosaics provides a unique snapshot of seasonal transitions in a high alpine catchment. Weekly radiometrically calibrated normalised difference vegetation index maps can be used to track vegetation health at the pixel scale through time. Thermal imagery can be used to map the movement of snowmelt across and within the near sub-surface as well as identify locations where groundwater is discharging to the surface. A 10 cm resolution digital surface model and dense point cloud (146 points m−2) are also provided for topographic analysis of the snow-free surface. These datasets augment ongoing data collection within this heavily studied and important alpine site; they are made publicly available to facilitate wider use by the research community. Datasets and related metadata can be accessed through the Environmental Data Initiative Data Portal, https://doi.org/10.6073/pasta/dadd5c2e4a65c781c2371643f7ff9dc4 (Wigmore, 2022a), https://doi.org/10.6073/pasta/073a5a67ddba08ba3a24fe85c5154da7 (Wigmore, 2022c), https://doi.org/10.6073/pasta/a4f57c82ad274aa2640e0a79649290ca (Wigmore and Niwot Ridge LTER, 2021a), https://doi.org/10.6073/pasta/444a7923deebc4b660436e76ffa3130c (Wigmore and Niwot Ridge LTER, 2021b), https://doi.org/10.6073/pasta/1289b3b41a46284d2a1c42f1b08b3807 (Wigmore and Niwot Ridge LTER, 2022a), https://doi.org/10.6073/pasta/70518d55a8d6ec95f04f2d8a0920b7b8 (Wigmore and Niwot Ridge LTER, 2022b). A summary of the available datasets can be found in the data availability section below.

Morphometric analysis of hillslope evolution in the Kadisha River Basin based on archived aerial photographs

The morphometric analysis of hillslope evolution, using the traditional method of interpreting archived aerial photographs, requires both considerable time and subjectivity. It is well-established that the Structure from Motion (SfM) approach, a photogrammetric method producing high resolution Digital Surface Models (DSM), is more effective. This study aims to determine how hillslope evolution in the upper basin of Kadisha watershed can be better analysed for an accurate morphometric analysis. It investigates and validates the influence of the applied Morphometric Slope Index (MSI) on morphology, depth, and erosion volume, as well as the processes of the computed pre-erosion surfaces in GIS environment. To enable testing the hypothesis that the characteristics of drainage networks are highly affected by the MSI, the following drainage network parameters were quantified in the thirty-two sub-basins: MSI, Drainage Density (D d ), average slope (ASL), depth, and eroded volume (V). Correlation between morphometric features and erosion was identified to reveal the mechanism of hillslope evolution. The results largely support what was hypothesized: MSI was useful in capturing single slope morphometric characteristics in sub-basins. The process revealed that pre-erosion MSI is a desired slope morphometry indicator and a hillslope evolution predictor in the study area.

Vegetation shadow casts impact remotely sensed reflectance from permafrost thaw ponds in the subarctic forest-tundra zone

Thermokarst lakes and ponds are a common landscape feature resulting from permafrost thaw, but their intense greenhouse gas emissions are still poorly constrained as a feedback mechanism for global warming because of their diversity, abundance, and remoteness. Thermokarst waterbodies may be small and optically diverse, posing specific challenges for optical remote sensing regarding detection, classification, and monitoring. This is especially relevant when accounting for external factors that affect water reflectance, such as scattering and vegetation shadow casts. In this study, we evaluated the effects of shadowing across optically diverse waterbodies located in the forest–tundra zone of northern Canada. We used ultra-high spatial resolution multispectral data and digital surface models obtained from unmanned aerial systems for modeling and analyzing shadow effects on water reflectance at Earth Observation satellite overpass time. Our results show that shadowing causes variations in reflectance, reducing the usable area of remotely sensed pixels for waterbody analysis in small lakes and ponds. The effects were greater on brighter and turbid inorganic thermokarst lakes embedded in post-glacial silt–clay marine deposits and littoral sands, where the mean reflectance decrease was from -51 to -70%, depending on the wavelength. These effects were also dependent on lake shape and vegetation height and were amplified in the cold season due to low solar elevations. Remote sensing will increasingly play a key role in assessing thermokarst lake responses and feedbacks to global change, and this study shows the magnitude and sources of optical variations caused by shading that need to be considered in future analyses.

Geographic information system data considerations in the context of the enhanced bathtub model for coastal inundation

AbstractThis study determines input data appropriateness for geographic information system‐based enhanced bathtub model (eBTM) modeling of coastal inundation in an urban setting. Various tests were conducted concerning digital surface models (DSMs) to determine: (a) the highest appropriate resolution achievable from available LiDAR data and consider variations between derived sub‐meter DSMs; (b) optimal DSM horizontal resolution for coastal inundation modeling based on “out‐the‐box” solutions; and (c) mechanisms to address the challenge presented by DSMs regarding overhanging structures for a study site in False Bay, South Africa. Results showed that while sub‐meter DSMs are achievable, low point cloud densities may result in the misrepresentation of structures, which affects the inundation extents. High horizontal resolution DSMs are required for inundation modeling in an urban setting to account for narrow thoroughfares. Challenges posed by first return LiDAR depicting bridges as solid structures could be circumvented by modifying the input water source for the eBTM processing.

Automatic detection of forest trees from digital surface models derived by aerial images

For the sustainable management of forests, obtaining the spatial information of the tree existence (location, number, height, and crown diameter of trees, etc.) with high accuracy and quickly is very important. In this context, the study aims to detect forest trees automatically through flow analysis applied to a 5 m resolution digital surface model by geospatial analysis. The study was carried out in five sample areas with different physical and topographic characteristics in the Antalya province of Turkey. The method consists of two steps which are identifying tree populations and determining tree peaks by applying flow analysis on the surface model. First, the canopy height model was extracted by applying a morphological filter to the image-based digital surface model. Then, the tree peak points are considered sink points, and these sink points were determined on the inverted surface model by the flow analysis approach which is frequently used in hydrological studies. The results showed that the applied method gives approximately 70% accuracy depending on the terrain conditions. Tree crown diameter, distance between trees, slope of the land, and digital surface model resolution significantly affect the accuracy of the results. It is predicted that this study will be an important guide for decision-makers in the preparation of forest plans.

An Illumination-Invariant Shadow-Based Scene Matching Navigation Approach in Low-Altitude Flight

Differences in acquisition time, light conditions, and viewing angle create significant differences among the airborne remote sensing images from Unmanned Aerial Vehicles (UAVs). Real-time scene matching navigation applications based on fixed reference maps are error-prone and have poor robustness. This paper presents a novel shadow-based matching method for the localization of low-altitude flight UAVs. A reference shadow map is generated from an accurate (0.5 m spatial resolution) Digital Surface Model (DSM) with the known date and time information; a robust shadow detection algorithm is employed to detect shadows in aerial images; the shadows can then be used as a stable feature for scene matching navigation. Combining the conventional intensity-based matching method, a fusion scene navigation scheme that is more robust to illumination variations is proposed. Experiments were performed with Google satellite maps, DSM data, and real aerial images of the Zurich region. The radial localization error of the Shadow-based Matching (SbM) is less than 7.3 m at flight height below 1200 m. The fusion navigation approach also achieves an optimal combination of shadow-based matching and intensity-based matching. This study shows the solution to the inconsistencies caused by changes in light, viewing angle, and acquisition time for accurate and effective scene matching navigation.

Estimation of mean dominant height using NAIP digital aerial photogrammetry and lidar over mixed deciduous forest in the southeastern USA

• Temperate deciduous tree heights estimated with point clouds from digital aerial photogrammetry. • Photogrammetrically-derived point clouds a possible surrogate for those derived from lidar data. • Lidar-derived DEM necessary to normalize point clouds derived from digital aerial photogrammetry. • A poor photogrammetric solution led to reduced estimation accuracy in some shadowed areas. In the absence of complete lidar coverage, digital surface models (DSMs) and point clouds produced from the United States Department of Agriculture National Agriculture Imagery Program (NAIP) are increasingly being analyzed for quality and application feasibility. This study compared canopy heights derived from NAIP DSMs (10 m) and point clouds to those derived from lidar data collected over Mountain Lake Biological Station and the Great Smoky Mountains Twin Creeks Site by the National Ecological Observatory Network (NEON) Airborne Observation Platform for 62 mixed deciduous tree plots. Mean dominant height (MDH) was estimated using lidar and the NAIP products using the 90th percentile of heights in a given plot as the independent variable for both the lidar- and NAIP-derived point clouds. The dependent variable was field-measured MDH, calculated using the four tallest trees for each 0.04-hectare plot based on the NEON woody vegetation structure dataset. All data (field and remotely sensed) were collected in 2018. Using maximum likelihood spatial error model for all analyses, the NAIP DSM (10 m resolution) resulted in a strong relationship with MDH (coefficient of determination ( R 2 ) = 0.90, standard error ( SE ) = 1.71 m). However, the 90th percentiles of heights derived from the point clouds were better at estimating MDH than was the comparatively coarse resolution DSM (NAIP point clouds: R 2 = 0.94, SE = 1.40 m; lidar: R 2 = 0.95, SE = 1.29 m, respectively) and are strongly correlated to each other ( R 2 = 0.99, SE = 0.68 m). The main limitation of the NAIP datasets was found to be where shadowing occurred due to steep terrain in the Great Smoky Mountain site. These areas resulted in erroneously high vegetation heights. Mean dominant heights estimated using NAIP DSMs and point clouds are thus comparable to those estimated using lidar data in these closed-canopy temperate deciduous forests where shadowing from steep terrain is not present. The utility of both the NAIP-derived 10 m DSM and the point clouds for estimating tree heights paves the way for statewide mapping of heights over the deciduous forests in Tennessee, Virginia, and possibly beyond.

Intra-gully mapping of the largest documented gully network in South Africa using UAV photogrammetry: Implications for restoration strategies

Gully erosion can reach alarming dimensions, and in several cases contributes significantly to soil loss and sediment yield in catchments. The studied example is one of the largest known gully networks in the world (its surface area is approximately 0.5 million m2 and volume 5 million m3), more than twice as large compared to the largest gullies described in peer-reviewed literature. To improve gully management strategies, it is not only critical to understand the factors that lead to erosion, but also to identify the extent of in-channel erosional and depositional features. Few studies consider in-channel patterns of erosion and deposition within gully systems. This study utilises a fixed-wing Unmanned Aerial Vehicle (UAV) and Structure-from-Motion (SfM) photogrammetry to create a high resolution orthomosaic and Digital Surface Model (DSM) to determine the position and spatial extent of erosional and depositional features within a large gully network in South Africa. Formation of such a large gully in relation to a relatively small drainage area is unusual but can be explained by the presence of dispersive soils and regional landscape incision. Longitudinal and cross-sectional profiles indicate that the gully network consists of three channel types (i.e. V-shaped, U-shaped and trapezoidal), each with a unique combination of erosional and depositional features. This study demonstrates the value of identifying and mapping of intra-gully features to better understand sediment transfer within the gully network to implement appropriate restoration strategies, which in this instance should focus on depositional zones to enhance channel decoupling.

A localized counter-based filtering approach for generating digital terrain model from medium resolution digital surface model

The Digital Terrain Model (DTM) is an important dataset for various applications such as hydrology, environmental sciences, urban planning, etc. Majority of the satellite-based medium resolution (30 m − 90 m) Digital Surface Model (DSM) products are freely available and widely used around the world. The generation of a DTM from these products is a tedious process. In this paper, a simple algorithm is developed to classify the ground and non-ground pixels in the DSM. The algorithm is tested on ALOS – World 3 D 30 m (AW3D30) DSM for small patches in the cities of Chennai, Mumbai and Cairo. Based on general assumption of the minimum elevation difference that exists between the ground and non-ground objects a slope threshold is used to initially classify the DSM. The elevations of the classified pixels are then used iteratively to assign counter values to the pixels. These counter values are finally used to classify the data and the ground pixels are interpolated using Inverse Distance Weighted (IDW) technique to generate the DTM. The proposed algorithm is quantitatively assessed and has a Type I error of 2.33%, Type II error of 1.67%, Total error of 2% and Kappa coefficient value of 96%. Additionally, R2 and RMSE values of 0.9589 and ± 0.429 m were observed when compared against a reference DTM.

Efficient dead pine tree detecting method in the Forest damaged by pine wood nematode (Bursaphelenchus xylophilus) through utilizing unmanned aerial vehicles and deep learning-based object detection techniques

Pine wood nematode (Bursaphelenchus xylophilus) is an invasive pathogen in South Korea, where it has caused pine wilt disease (PWD) with extremely high mortality of native pine species (Pinus densiflora, Pinus thunbergii, and Pinus koraiensis). Since the disease spreads by its vectors, native pine sawyer beetles (Monochamus alternatus and Monochamus saltuarius), the cost of monitoring the expansion has been rapidly increasing. Furthermore, it is even more costly to eliminate new and isolated infections since unremoved infected trees act as new sources of infection through the preferred oviposition of the beetles on such trees. The methodology of combining unmanned aerial vehicle (UAV) and object detection based on deep learning provides the opportunity to solve such problems, as UAV with RGB camera can provide high spatial resolution aerial image and digital surface model (DSM), which can be used for object detection with excellent results. In this study, we evaluated the performance of this method to detect dead pine trees in PWD-damaged areas. In particular, to ensure low omission error of monitoring, YOLOv3 was employed for object detection as the model design is focused on minimizing the omission error. We also modified the model so that the positions and crown diameter could be estimated. Four detection models were trained using four different combinations between aerial images (R, G, B) and DSM from UAV. Among them, the model from RGB showed the highest performance (recall: 0.9909, precision: 0.8438) and was selected as the optimal model. Our results suggest that our method can contribute to low-cost and effective monitoring of the dead pine trees while maintaining low omission error, which is critical for PWD management.

Morphological evolution of a non-engineered managed realignment site following tidal inundation

There is growing evidence that managed realignment (MR) sites have lower biodiversity than natural saltmarshes, which has been associated with differences in the physical function and morphological evolution following site breaching. This evidence has been derived from MR sites previously used for intensive arable agriculture or modified during site construction. Therefore, the development of these sites may not be representative of the sedimentological evolution that would have otherwise occurred. This paper presents analysis of high spatial resolution digital surface models derived from the images collected using a small-unmanned aerial system from a non-engineered MR site at Cwm Ivy Marsh, Gower Peninsula, Wales. These models are examined alongside a novel combination of high frequency measurements of the rate and patterns of sedimentation, suspended sediment concentration (SSC), and the sub-surface structure and geochemical profiles. Results indicated that although the site became topographically less variable over a four year period, the intertidal morphology developed through an increase in the abundance of higher order creek systems and sediment being deposited at a rate of between 3 and 7 cm/year. The SSC followed an inverse pattern to water depth, with bed elevation increasing and then decreasing during both the flood and ebb tidal phases. Analysis of the sediment subsurface geochemical composition indicated redox profiles similar to natural intertidal environments; evidence of a fluctuating water table was found at a saltmarsh site, in comparison to waterlogging identified at an anoxic mudflat site. These findings provide a new insight to the sedimentological processes in a MR site without the influence of landscaping or site engineering prior to site breaching, which can be used to inform the design of future MR sites.

Photovoltaic generation on vertical façades in urban context from open satellite-derived solar resource data

Solar radiation incident at building façades and elements in an urban context is essential in determining the energy production on building rooftops and vertical façades. The proper determination of solar irradiance incident on a vertical façade needs quality input of the components of solar radiation and a high resolution digital surface model with the heights of buildings and other elements in the urban area of study. In this work a thorough methodology for modeling PV generation, in hourly basis, at building façades with open available data and methods is presented. Hourly data of satellite-derived solar irradiance is used with high resolution digital model from LIDAR information to estimate with the Sandia model the PV generation of five small arrays at west, south and east façades of a building in Madrid. PV output modeled for west and south arrays are in rather good agreement with the monitored experimental data of the production. RMSE of 8% and 12% was observed for the monthly power predicted for west and south facades, respectively. The east façade case was much more challenging due to variability of shadows it receives from the nearby large deciduous trees throughout the year, which results in high uncertainty in the shading influence estimation. Anyway, the methodology proves the benefits and possibilities of detailed estimation of PV production in building façades from open available information regarding both solar resource, open modeling tools and urban topography, even in a very challenging conditions associated to the variability of trees canopy.

High resolution mapping and analysis of shore platform morphology in Galicia, northwestern Spain

Most research on shore platforms has been at fairly large spatial scales over distances ranging from hundreds to thousands of metres. Other work at much smaller scales, ranging from one to several decimetres, often corresponds to the dimensions of micro-erosion meter stations. Few studies have been concerned with platform morphology in which the basic data are acquired at intermediate or meso-scales ranging up to a few metres. This is due, in part, to terrestrial surveying at meso-scales being time-consuming while aerial surveys using LiDAR are expensive. A meso-scale study was made on three shore platforms in western Galicia, northwestern Spain using data from an Unmanned Aerial Vehicle (UAV) to produce high resolution Digital Surface Models (DSMs) and to calculate local surface elevation, roughness, slope, and joint density at a 0.5 m pixel scale, and joint orientation and length. This was supplemented by Equotip field measurements of rock hardness. A granitic platform was higher and had rougher surfaces and steeper slopes than two platforms in schist. The relationship between platform morphology and rock hardness and joint density was complex, however, reflecting in part the role of schistosity in accounting for the formation of low, regular platforms in hard schists with low joint density. The study suggested that while tidal range, inheritance, and other environmental and evolutionary factors can be dominant in determining platform morphology at the macro- or regional scale, geological, and particularly structural, factors become increasingly important in Galicia as the scale diminishes, and they are generally dominant at the local or meso-scale.

Evidence of Surface Rupture Associated With Historical Earthquakes in the Lower Tagus Valley, Portugal. Implications for Seismic Hazard in the Greater Lisbon Area

The Lower Tagus Valley Fault, Portugal, has long been associated with the damaging earthquakes that affected the Greater Lisbon Area in historical times. These include a poorly documented earthquake that occurred in 1344, the relatively well-documented 1531 earthquake, and the most recent M6.0 1909 earthquake. In this work, we use a 0.5 m resolution LiDAR-based digital elevation model and a 0.5 cm resolution digital surface model based on UAV photogrammetry to accurately locate the fault scarps in the northernmost portion of the western fault strand and to select sites to perform paleoseimolological investigations. The paleoseismological and geochronological analysis performed in the Alviela trench site document the fault activity in the last 3000 years, including two earthquakes during historical times. We performed ground motion scenarios for 20 km, 40 km, and 60 km ruptures including the trench site. The ground motion fields obtained for the 40 km and 60 km ruptures are in agreement with most macroseismic intensity data available for the 1531 earthquake, implying a magnitude in the range M6.8–7.4. However, the degree of deformation preserved in the trench suggests a value closer to the lower magnitude bound. The intensity level observed in Lisbon in 1531 (IX) is lower than the modeled intensities for all considered scenarios and could be related to a particularly high level of vulnerability of the building stock.