Airborne Lidar Survey Research Articles

A multi-proxy assessment of terrace formation in the lower Trinity River valley, Texas

Abstract. A proposed null hypothesis for fluvial terrace formation is that internally generated or autogenic processes, such as lateral migration and river-bend cutoff, produce variabilities in channel incision that lead to the abandonment of floodplain segments as terraces. Alternatively, fluvial terraces have the potential to record past environmental changes from external forcings that include temporal changes in sea level and hydroclimate. Terraces in the Trinity River valley have been previously characterized as Deweyville groups and interpreted to record episodic cut and fill during late Pleistocene sea level variations. Our study uses high-resolution topography of a bare-earth digital elevation model derived from airborne lidar surveys along ∼ 88 linear kilometers of the modern river valley. We measure both differences in terrace elevations and widths of paleo-channels preserved on these terraces in order to have two independent constraints on terrace formation mechanisms. For 52 distinct terraces, we quantify whether terrace elevations fit distinct planes – expected for allogenic terrace formation tied to punctuated sea level and/or hydroclimate change – by comparing variability in a grouped set of Deweyville terrace elevations against variability associated with randomly selected terrace sets. Results show Deweyville groups record an initial valley floor abandoning driven by allogenic forcing, which transitions into autogenic forcing for the formation of younger terraces. For these different terrace sets, the slope amongst different terraces stays constant. For 79 paleo-channel segments preserved on these terraces, we connected observed changes in paleo-channel widths to estimates for river paleo-hydrology over time. Our measurements suggest the discharge of the Trinity River increased systematically by a factor of ∼ 2 during the late Pleistocene. Despite this evidence of increased discharge, the similar down-valley slopes between terrace sets indicate that there were likely no increases in sediment-to-water discharge ratios that could be linked to allogenic terrace formation. This is consistent with our elevation clustering analysis that suggests younger terraces are indistinguishable in their elevation variance from autogenic terrace formation mechanisms, even if the changing paleo-channel dimensions might, viewed in isolation, provide a mechanism for allogenic terrace formation. Methods introduced here combine river-reach-scale observations of terrace sets and paleo-hydrology with local observations of terraces and paleo-channels to show how interpretations of allogenic versus autogenic terrace formation can be evaluated within a single river system.

Mapping Ancient Architecture via Unpiloted Aerial Vehicle–acquired LiDAR: A Case Study of Hōlualoa Royal Centre, Kona District, Hawai‘i Island

At present there is no systematic record of the size, form or density of architecture at Hawaiian royal centres. We report on the results of a UAV LiDAR survey of one of the best-preserved examples of a royal centre in the archipelago: Hōlualoa Royal Centre, Kona District, Hawai‘i Island. The resolution of our data (0.3–0.1 m) is far superior to previous airborne LiDAR surveys (1.0 m); however, several factors, including thick understory vegetation, made resolving archaeological targets challenging. We nonetheless were able measure the volume of building material of the largest features, which allows us to compare structures in this royal centre with other monuments in the region. This study highlights the advantages, and limitations, of UAV LiDAR as well as the need for more high-quality quantitative data on architecture at royal centres.

Assessing Storm Response of Multiple Intertidal Bars Using an Open-Source Automatic Processing Toolbox

Intertidal bars are common features of sandy beaches in meso- and macro-tidal environments, yet their behaviour under storm impact and subsequent recovery remain poorly documented. Intensive surveys provide valuable information; however, it takes time to process the vast amount of data. This study presents the morphological response of a multibarred macro-tidal beach along the Belgian coast after a severe storm that happened on 8–12 February 2020, and to develop and apply an oPen-source Raster prOcessing Toolbox for invEstigation Coast intertidal bar displacemenT (PROTECT) in Python for automated bar extraction. This toolbox was applied to the digital surface models of pre- and post-storm airborne LiDAR surveys of a multibarred intertidal beach. The PROTECT toolbox is capable of detecting the position and elevation of intertidal bars accurately. The uncertainty in the elevation characteristics of the bars induces an error in the elevation dimension of 0.10 m. Using the toolbox, the results showed that the intertidal bars changed in term of variations in bar number, dimensions and shape across the storm event. Overall, the storm significantly eroded the dune and the upper-beach zone with a sand loss equivalent elevation decrease of −0.14 m. This was followed by a continuous and full recovery after 9 months under fair weather conditions. In contrast, the sand budget in the intertidal zone did not change over the entire monitoring period although the bars showed significant morphological change. Applying the PROTECT toolbox on high-resolution 3D topographic datasets allows to increase the temporal mapping resolution of intertidal bars from long-term (years) to short (storm events) time scales. Similar assessments at locations worldwide would allow the improvement of our knowledge on the morphodynamical role of multibarred beaches and to forecast their evolution, thus contributing to manage future storm response and the progressively accelerating sea level rise.

Ecological impacts of shortening fire return intervals on boreal peatlands and transition zones using integrated in situ field sampling and lidar approaches

AbstractAridity associated with rising air temperatures in northern latitudes is expected to contribute to increased frequency of wildland fires. Here, we examined regenerating vegetation following short return interval (SRI) fire (56 years post‐fire) compared to long return interval (LRI) fire (>80 years post‐fire) in boreal peatlands and their adjacent transitional areas. The objectives of this study were to quantify if differences exist between (1) peatland and transitional soil characteristics in LRI versus SRI areas and (2) regenerating vegetation species, structural characteristics and diversity. We also determined if patterns of vegetation structural characteristics observed using field data also occur across the broader landscape using airborne lidar data. The Utikuma Region Study Area (URSA) is located in central Alberta, Canada. Here, 19 peatlands were sampled, coincident with an airborne lidar survey of the broader region, where 120 peatlands in short and long fire return intervals were identified. We found that SRI transitional areas had significantly deeper organic soil deposits than those found in LRI (p < 0.0001). Proportions of regenerating species differed significantly between peatlands and transitional areas in SRI versus LRI, where greater proportion of coniferous species were observed in LRI. Deciduous transitional–upland species and taller post‐fire vegetation heights were more commonly found SRI peatlands compared with LRI. This suggest that fires with SRIs in this region may result in enhanced deciduous succession, which may transition boreal peatlands into ecosystems that have some characteristics of transitional and upland forests.

Airborne Lidar Survey, Density-Based Clustering, and Ancient Maya Settlement in the Upper Usumacinta River Region of Mexico and Guatemala

We present results from the archaeological analysis of 331 km2 of high-resolution airborne lidar data collected in the Upper Usumacinta River basin of Mexico and Guatemala. Multiple visualizations of the DEM and multi-spectral data from four lidar transects crossing the Classic period (AD 350–900) Maya kingdoms centered on the sites of Piedras Negras, La Mar, and Lacanja Tzeltal permitted the identification of ancient settlement and associated features of agricultural infrastructure. HDBSCAN (hierarchical density-based clustering of applications with noise) cluster analysis was applied to the distribution of ancient structures to define urban, peri-urban, sub-urban, and rural settlement zones. Interpretations of these remotely sensed data are informed by decades of ground-based archaeological survey and excavations, as well as a rich historical record drawn from inscribed stone monuments. Our results demonstrate that these neighboring kingdoms in three adjacent valleys exhibit divergent patterns of structure clustering and low-density urbanism, distributions of agricultural infrastructure, and economic practices during the Classic period. Beyond meeting basic subsistence needs, agricultural production in multiple areas permitted surpluses likely for the purposes of tribute, taxation, and marketing. More broadly, this research highlights the strengths of HDBSCAN to the archaeological study of settlement distributions when compared to more commonly applied methods of density-based cluster analysis.

Rapid shrub expansion in a subarctic mountain basin revealed by repeat airborne LiDAR

As a consequence of increasing temperatures, a rapid increase in shrub vegetation has occurred throughout the circumpolar North and is expected to continue. Rates of shrub expansion are highly variable, both at the regional scale and within local study areas. This study uses repeat airborne LiDAR and field surveys to measure changes in shrub vegetation cover along with landscape-scale variations in a well-studied subarctic headwater catchment in Yukon Territory, Canada. Airborne LiDAR surveys were conducted in August 2007 and 2018, whereas vegetation surveys were conducted in summer 2019. Machine learning classification algorithms were used to predict shrub presence/absence in 2018 based on rasterized LiDAR metrics, with the best-performing model applied to the 2007 LiDAR to create binary shrub cover layers to compare between survey years. Results show a 63.3% total increase in detectable shrub cover >= 0.45 m in height between 2007 and 2018, with an average yearly expansion of 5.8%. These changes were compared across terrain derivatives to quantify the influence of topography on shrub expansion. Terrain comparisons show that shrubs are located in and are preferentially expanding into lower and flatter areas near stream networks, at lower slope positions and with a higher potential for topographic wetness. Overall, the findings from this research reinforce the documented increase in pan-Arctic shrub vegetation in recent years, quantify the variation in shrub expansion over terrain derivatives at the landscape scale, and demonstrate the feasibility of using LiDAR to compare changes in shrub properties over time.

The impact of logging on vertical canopy structure across a gradient of tropical forest degradation intensity in Borneo

Abstract Forest degradation through logging is pervasive throughout the world's tropical forests, leading to changes in the three‐dimensional canopy structure that have profound consequences for wildlife, microclimate and ecosystem functioning. Quantifying these structural changes is fundamental to understanding the impact of degradation, but is challenging in dense, structurally complex forest canopies. We exploited discrete‐return airborne LiDAR surveys across a gradient of logging intensity in Sabah, Malaysian Borneo, and assessed how selective logging had affected canopy structure (Plant Area Index, PAI, and its vertical distribution within the canopy). LiDAR products compared well to independent, analogue models of canopy structure produced from detailed ground‐based inventories undertaken in forest plots, demonstrating the potential for airborne LiDAR to quantify the structural impacts of forest degradation at landscape scale, even in some of the world's tallest and most structurally complex tropical forests. Plant Area Index estimates across the plot network exhibited a strong linear relationship with stem basal area (R2 = 0.95). After at least 11–14 years of recovery, PAI was ~28% lower in moderately logged plots and ~52% lower in heavily logged plots than that in old‐growth forest plots. These reductions in PAI were associated with near‐complete lack of trees >30‐m tall, which had not been fully compensated for by increasing plant area lower in the canopy. This structural change drives a marked reduction in the diversity of canopy environments, with the deep, dark understorey conditions characteristic of old‐growth forests far less prevalent in logged sites. Full canopy recovery is likely to take decades. Synthesis and applications. Effective management and restoration of tropical forests requires detailed monitoring of the forest and its environment. We demonstrate that airborne LiDAR can effectively map the canopy architecture of the complex tropical forests of Borneo, capturing the three‐dimensional impact of degradation on canopy structure at landscape scales, therefore facilitating efforts to restore and conserve these ecosystems.

Comprehensive bathymetry and intertidal topography of the Amazon estuary

Abstract. The characterization of estuarine hydrodynamics primarily depends on knowledge of the bathymetry and topography. Here, we present the first comprehensive, high-resolution dataset of the topography and bathymetry of the Amazon River estuary, the world's largest estuary. Our product is based on an innovative approach combining spaceborne remote sensing data, an extensive and processed river depth dataset, and auxiliary data. Our goal with this mapping is to promote the database usage in studies that require this information, such as hydrodynamic modeling or geomorphological assessments. Our twofold approach considered 500 000 sounding points digitized from 19 nautical charts for bathymetry estimation, in conjunction with a state-of-the-art topographic dataset based on remote sensing, encompassing intertidal flats, riverbanks, and adjacent floodplains. Finally, our estimate can be accessed in a unified 30 m resolution regular grid referenced to the Earth Gravitational Model 2008 (EGM08), complemented both landward and seaward by land (Multi-Error-Removed Improved-Terrain digital elevation model, MERIT DEM) and ocean (General Bathymetric Chart of the Oceans version 2020, GEBCO_2020) topographic data. Extensive validation against independent and spatially distributed data, from an airborne lidar survey, from ICESat-2 altimetric satellite data, and from various in situ surveys, shows a typical vertical accuracy of 7.2 m (riverbed) and 1.2 m (non-vegetated intertidal floodplains). The dataset is available at https://doi.org/10.17632/3g6b5ynrdb.2 (Fassoni-Andrade et al., 2021).

Recovery of logged forest fragments in a human-modified tropical landscape during the 2015-16 El Ni\xf1o

The past 40 years in Southeast Asia have seen about 50% of lowland rainforests converted to oil palm and other plantations, and much of the remaining forest heavily logged. Little is known about how fragmentation influences recovery and whether climate change will hamper restoration. Here, we use repeat airborne LiDAR surveys spanning the hot and dry 2015-16 El Niño Southern Oscillation event to measure canopy height growth across 3,300 ha of regenerating tropical forests spanning a logging intensity gradient in Malaysian Borneo. We show that the drought led to increased leaf shedding and branch fall. Short forest, regenerating after heavy logging, continued to grow despite higher evaporative demand, except when it was located close to oil palm plantations. Edge effects from the plantations extended over 300 metres into the forests. Forest growth on hilltops and slopes was particularly impacted by the combination of fragmentation and drought, but even riparian forests located within 40 m of oil palm plantations lost canopy height during the drought. Our results suggest that small patches of logged forest within plantation landscapes will be slow to recover, particularly as ENSO events are becoming more frequent.

Disentangling the effect of topography and microtopography on near-ground growing-season frosts at the boreal-temperate forest ecotone (Québec, Canada)

Permanent landscape attributes such as topography (elevation [m]) and microtopography (local variation in elevation [cm]) can increase the risk of cold air drainage down-slopes and in microtopographic depressions, causing important temperature gradients that generate localized growing-season frosts. Since most studies on growing-season frosts are restricted to the northern parts of the boreal forest or to mountainous areas, their negative consequences on tree productivity at the boreal-temperate forest ecotone is often ignored. We quantified the intensity and probability of growing-season frosts at the boreal-temperate forest ecotone in regard to topographic and microtopographic landscape attributes, which were extracted from airborne LiDAR surveys. In situ air temperature was measured for two summers (2016–2017) with 252 temperature loggers installed in two 18-years-old spruce plantations established in both temperate and boreal mixedwood forests. Growing-season frosts were more intense and probable at the boreal mixedwood forest site compared to the temperate forest site. Still, at both sites, when growing-season frost occurred, air temperature could vary by 4 °C along the elevation gradient of 15 m, often reaching sub-zero values at low elevation while reaching above-freezing values at high elevation. The importance of microtopography on the risk of sub-zero temperatures increased where frost events were less likely to occur such as at the temperate forest and at high elevation. Considering that growing-season frosts can considerably reduce tree productivity, the effects of both topography and planting microsite should be considered when determining where to establish plantations in the landscape and to determine suitable frost-free planting microsites within a plantation.

Historic and Modern Approaches for the Discovery of Abandoned Wells for Methane Emissions Mitigation in Oil Creek State Park, Pennsylvania.

Hundreds of oil wells were drilled along Oil Creek in Pennsylvania in the mid-1800s, birthing the modern oil industry. No longer in operation, many wells are now classified as abandoned, and, due to their age, their locations are either unknown or inaccurately recorded. These historic-well sites present environmental, safety, and economic concerns in the form of possible methane leaks and physical hazards. Airborne magnetic and LiDAR surveys were conducted in the Pioneer Run watershed in Oil Creek State Park to find abandoned wells in a historically significant but physically challenging location. Wells were drilled in this area prior to modern geolocation and legal documentation. Although a large number of old wells were abandoned summarily without remediation of the site, much of the land area within Oil Creek State Park is now covered in trees and dense underbrush, which can obscure wellheads. The thick vegetation and steep terrain limited the possibility of ground-based surveys to easily find well sites for methane emissions studies. The data from remote sensing surveys were used to corroborate potential well locations from historic maps and photographs. Potential well sites were verified in a ground-based field survey and monitored for methane emissions. Two historic photographs documenting oil activity in the late 1800s were georeferenced using a combination of magnetic and LiDAR data. LiDAR data, which were more useful in georeferencing and in field verification, identified 290 field locations in the Pioneer Run watershed, 86% of which were possible well sites. Sixty-two percent of the ground-verified wells remained unplugged and comprised the majority of leaking wells. The mean methane emissions factor for unplugged wells was 0.027 ± 0.099 kg/day, lower than other Appalachian Basin methane emissions estimates. LiDAR was used for the first time, in combination with an airborne magnetic survey, to reveal underground oil industry features and inform well identification and remediation efforts in difficult-to-navigate regions. In the oldest oil fields, where well casing has been removed or wood conductor casing was installed, historic photographs provide additional lines of evidence for oil wells where ground disturbances have concealed surface features. Identification of well sites is necessary for mitigation efforts, as unplugged wells emit methane, a potent greenhouse gas.

Preparation of High-Resolution DTM and Orthophoto Using LiDAR in Nepal

The high-resolution terrain model has varied usages including development planning, engineering works, environmental management, disaster management, urban planning, irrigation, geological study, archeological study and cadastral application. Currently, this data is not available for Nepal and it has also hindered the socio and economic development of the country. Airborne Lidar is economically cost-effective and viable means for topography related data collection. Lidar which is an acronym for Light Detection and Ranging is an active remote sensing technology in which Laser beams are used for surveying and mapping. The Survey Department of Nepal has taken initiative to prepare the High-Resolution DTM and Orthophoto of about 20,000 square kilometres of Nepal using Lidar surveying and mapping. Survey Department is conducting a LiDAR survey in the western terai regions of Nepal from Chitwan to Kanchanpur district. Airborne LiDAR survey data along with a very high resolution (0.15 m) orthophoto shall be generated. Further, processing of LiDAR points data will generate a highly precise digital terrain model of 1 m grid data having an accuracy of 0.25 m and finally 0.5 m contour interval data. This endeavor is one of the milestones in the surveying and mapping sector of Nepal and it will have far-reaching consequence in the social and economic development of Nepal.

Optimization of Optical Image Geometric Modeling, Application to Topography Extraction and Topographic Change Measurements Using PlanetScope and SkySat Imagery

The volume of data generated by earth observation satellites has increased tremendously over the last few decades and will increase further in the coming decade thanks in particular to the launch of nanosatellites constellations. These data should open new avenues for Earth surface monitoring due to highly improved spectral, spatial and temporal resolution. Many applications depend, however, on the accuracy of the image geometric model. The geometry of optical images, whether acquired from pushbroom or frame systems, is now commonly represented using a Rational Function Model (RFM). While the formalism has become standard, the procedures used to generate these models and their accuracies are diverse. As a result, the RFM models delivered with commercial data are commonly not accurate enough for 3-D extraction, subpixel registration or ground deformation measurements. In this study, we present a methodology for RFM optimization and demonstrate its potential for 3D reconstruction using tri-stereo and multi-date Cubesat images provided by SkySat and PlanetScope, respectively. We use SkySat data over the Morenci Mine, Arizona, which is the largest copper mine in the United States. The re-projection error after the RFM refinement is 0.42 pix without using ground control points (GCPs). Comparison of our Digital Elevation Model (DEM with ~3 m GSD) with a reference DEM obtained from an airborne LiDAR survey (with ~1 m GSD) over stable areas yields a standard deviation of the elevation differences of ~3.9 m. The comparison of the two DEMs allows detecting and measuring the topographic changes due to the mine activity (excavation and stockpiles). We assess the potential of PlanetScope data, using multi-date DOVE-C images from the Shisper glacier, located in the Karakoram (Pakistan), which is known for its recent surge. We extracted DEMs in 2017 and 2019 before and after the surge. The re-projection error after the RFM refinement is 0.38 pix without using GCPs. The accuracy of our DEMs (with ~9 m GSD) is evaluated through comparison with the SRTM DEM (GSD ~30 m) and with a DEM (GSD ~2 m) calculated from Geoeye-1 (GE-1) and World-View-2 (WV-2) stereo images. The standard deviation of the elevation differences in stable areas between the PlanetScope DEM and SRTM is ~12 m, and ~7 m with the GE-1&WV-2 DEM. The mass transfer due to the surge is clearly revealed from a comparison of the 2017 and 2019 DEMs. The study demonstrates that, with the proposed scheme for RFM optimization, times series of DEM extracted from SkySat and PlanetScope images can be used to measure topographic changes due to mining activities or ice flow, and could also be used to monitor geomorphic processes such as landslides, or coastal erosion for example.

Morpho-chronology of monogenetic scoria cones from their level contour curves. Applications to the Chichinautzin monogenetic field, Central Mexico

The genesis, distribution and hazards associated with monogenetic volcanic fields pose particular difficulties derived from their dispersed character. Establishing a relationship between the spatial and the age distributions of volcanic cones is necessary both to understand the nature of monogenetic field formation and evolution and to set supported hazard-assessment criteria. We present here a new method –specifically developed to quantify the degree of age-dependent erosion of individual scoria cones– aimed to estimate the relative ages of undated scoria cones in a monogenetic volcanic field from a contour level morphometric analysis of the field digital elevation model (DEM). This method is based on the hypothesis that age and the degree and type of erosion causing significant morphological changes on scoria cones are markedly correlated. It is assumed that, at the time of their formation, monogenetic volcanoes have diverse, yet smooth shapes, which mechanical processes of wearing gradually change in different spatial scales. This evolution is largely evidenced both as changes of the volcano slopes and as height-dependent undulations of the cone surface generated by the hydrometeorological ablation in the otherwise uniform elevation contour lines. Here, we characterize the time-dependence of the shape and size of the altitude isoline undulations by means of the Elliptical Fourier Descriptor spectra of the contour curves of volcanic cones. To test the effects of the DEM data type and resolution on this morpho-chronological dating, we analyze the correlations of published radiometric ages of cones with two datasets of contour curves from the Sierra Chichinautzin monogenetic volcanic field in Central Mexico (SCVF): one obtained from airborne LIDAR surveys (INEGI, Mexico) and the other from a satellite radar mission (DLR, Germany).

Mapping of liquefaction risk on road network based on relationship between liquefaction potential and liquefaction-induced road subsidence

On March 11, 2011, a large earthquake of Mw 9.0 shook north-eastern Japan and caused severe liquefaction-induced damage over a wide area of reclaimed lands along the coast of Tokyo Bay. Although regional mapping of the liquefaction hazard had been performed in many automounts bodies in Japan, it seems that the maps were not effectively used on all fronts of disaster-prevention management, because the maps only provide liquefaction susceptibilities and little quantitative information on how seriously the ground might deform in a scenario earthquake, which is absolutely necessary information for discussing what-if scenarios. Konagai et al. (2013) conducted air-borne LiDAR surveys to obtain liquefaction-induced ground deformations over the north-eastern stretch of the Tokyo Bay shore area, including Urayasu City, where approximately 85% of the city area was heavily liquefied. Meanwhile, the authors have developed a geotechnical database for liquefaction risk assessments, compiling all the available borehole logs and soil testing data provided by Urayasu City (2012). Given the potential risk of re-liquefaction in a future scenario earthquake, it is an overriding priority to develop a knowledge-sharing liquefaction hazard map reflecting precise records from the past, such as liquefaction-induced ground subsidence and liquefaction-related damage. This paper attempts to assess the liquefaction-induced damage risk on road network, examining the relationship between the liquefaction potential index and the actual ground subsidence. For this purpose, firstly, the spatial distribution of the liquefaction potential (PL) was estimated over Urayasu City based on the above-mentioned geotechnical database developed by the authors. Secondly, the spatial distribution of the PL values and the actual liquefaction-induced road subsidence confirmed through air-born LiDAR surveys were compared to develop an empirical rule for estimating the potential road subsidence in a scenario earthquake. This empirical rule was found to describe the actual damage to roads and manholes in a satisfactory manner. Therefore, it is expected that a risk map, developed on the basis of this empirical rule, will not only help to assess liquefaction-induced damage, but also to design countermeasures against the what-if scenarios of liquefaction.

Inferring Distributed Snow Depth by Leveraging Snow Pattern Repeatability: Investigation Using 47 Lidar Observations in the Tuolumne Watershed, Sierra Nevada, California

AbstractSnow distribution is controlled by the interaction between local meteorology and static features like topography and vegetation. The resulting spatial pattern of snow in mountainous terrain is often repeatable and can be used to infer snowpack distribution at periods when observations are limited. This study uses a library of airborne lidar surveys (ALS) in California's Tuolumne watershed to analyze snow patterns at extents (1,650 km2), resolutions (25 m), and temporal scales (47 ALS observations over 7 years) unmatched by previous research. Distributed snow depth was inferred from snow depth observations covering a portion of the domain (< 4%) at a period near peak‐snowpack timing and snow distribution patterns from different years. Snow patterns from different years differed as a function of snow extents, variability, and interannual noise (r = 0.30 to 0.90). However, matching criteria like seasonal timing and snow extents were able to identify pairs of snow patterns with increased spatial agreement (median r > 0.84). Distributed snow depth inferred using a strip of observations (<4% coverage), and a well‐correlated snow pattern (r≥ 0.90) had a mean absolute error (MAE) of 0.22 m and snow volume error of −6%. Distributed snow depth inferred using patterns of reduced accuracy (r < 0.80) were often too homogeneous, thereby increasing MAE and decreasing the duration of the simulated snowmelt season. This work has applications in water management, where distributed snow depth observations in watersheds with interannual snow pattern repeatability could decrease the extent of observations necessary in future years.

Structure from Motion of Multi-Angle RPAS Imagery Complements Larger-Scale Airborne Lidar Data for Cost-Effective Snow Monitoring in Mountain Forests

Snowmelt from mountain forests is critically important for water resources and hydropower generation. More than 75% of surface water supply originates as snowmelt in mountainous regions, such as the western U.S. Remote sensing has the potential to measure snowpack in these areas accurately. In this research, we combine light detection and ranging (lidar) from crewed aircraft (currently, the most reliable way of measuring snow depth in mountain forests) and structure from motion (SfM) remotely piloted aircraft systems (RPAS) for cost-effective multi-temporal monitoring of snowpack in mountain forests. In sparsely forested areas, both technologies give similar snow depth maps, with a comparable agreement with ground-based snow depth observations (RMSE ~10 cm). In densely forested areas, airborne lidar is better able to represent snow depth than RPAS-SfM (RMSE ~10 cm vs ~10–20 cm). In addition, we find the relationship between RPAS-SfM and previous lidar snow depth data can be used to estimate snow depth conditions outside of relatively small RPAS-SfM monitoring plots, with RMSE’s between these observed and estimated snow depths on the order of 10–15 cm for the larger lidar coverages. This suggests that when a single airborne lidar snow survey exists, RPAS-SfM may provide useful multi-temporal snow monitoring that can estimate basin-scale snowpack, at a much lower cost than multiple airborne lidar surveys. Doing so requires a pre-existing mid-winter or peak-snowpack airborne lidar snow survey, and subsequent well-designed paired SfM and field snow surveys that accurately capture substantial snow depth variability.

Monumental architecture at Aguada Fénix and the rise of Maya civilization.

Archaeologists have traditionally thought that the development of Maya civilization was gradual, assuming that small villages began to emerge during the Middle Preclassic period (1000-350BC; dates are calibrated throughout) along with the use of ceramics and the adoption of sedentism1. Recent finds of early ceremonial complexes are beginning to challenge this model. Here we describe an airborne lidar survey and excavations of the previously unknown site of Aguada Fénix (Tabasco, Mexico) with an artificial plateau, which measures 1,400m in length and 10 to 15m in height and has 9causeways radiating out from it. We dated this construction to between 1000 and 800BC using a Bayesian analysis of radiocarbon dates. To our knowledge, this is the oldest monumental construction ever found in the Maya area and the largest in the entire pre-Hispanic history of the region. Although the site exhibits some similarities to the earlier Olmec centre of San Lorenzo, the community of Aguada Fénix probably did not have marked social inequality comparable to that of San Lorenzo. Aguada Fénix and other ceremonial complexes of the same period suggest the importance of communal work in the initial development of Maya civilization.

Beach-dune Recovery from the Extreme 2013-2014 Storms Erosion at Truc Vert Beach, Southwest France: New Insights from Ground-penetrating Radar

Robin, N.; Billy, J.; Castelle, B.; Hesp, P.; Laporte-Fauret, Q.; Nicolae-Lerma, A.; Marieu, V.; Rosebery, D.; Bujan, S.; Destribats, B., and Michalet., 2020. Beach-dune recovery from the extreme 2013-2014 storms erosion at Truc Vert Beach, Southwest France: New insights from ground-penetrating radar. In: Malvárez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 588–592. Coconut Creek (Florida), ISSN 0749-0208.Foredunes are efficient natural coastal defenses acting as protective barriers during storm events. A striking example is the response of coastal dunes along the Aquitaine Coast (SW France) to the 2013-2014 winter, which was the most energetic winter since at least the mid-20th century in most of the NE Atlantic. The aim of this study is to analyze the (partial) foredune recovery from the 2013-2014 winter at Truc Vert beach using ground-penetrating radar (GPR) and through the coastal dune internal structure. Geophysical data was compared with semi-monthly DGPS topographic data of the beach, UAV-photogrammetry and Airborne LiDAR surveys of the coastal dune. Three main recovery phases were identified from the 2013-2014 winter: (i) aggradation of the upper-beach and dune front-crest during the post-storm summer; (ii) distinct phases of incipient dune-foot development with dune-crest stability during the following year, and (iii) since 2016, aggradation of both dune-foot and dune front-crest tending towards an equilibrium profile. This study shows that GPR surveys, combined with chronological topographic data, is an efficient tool to provide comprehensive understanding of the beach-dune system evolution at a decadal scale. This approach opens new perspectives to document foredune recovery timing and magnitude along sandy coasts.

Identification of Riparian Vegetation Types with Machine Learning Based on LiDAR Point-Cloud Made Along the Lower Tisza’s Floodplain

Abstract The very dense floodplain vegetation on the artificially confined floodplains results in decreased flood conveyance, thus increase in flood levels and flood hazard. Therefore, proper floodplain management is needed, which must be supported by vegetation assessment studies. The aims of the paper are to introduce the method and the results of riparian vegetation classification of a floodplain area along the Lower Tisza (Hungary) based on automatized acquisition of airborne LiDAR survey. In the study area 15x15 m large training plots (voxels) were selected, and the statistical parameters of their LiDAR point clouds were determined. Applying an automatized parameter selection and 10-fold cross-validation he most suitable decision tree was selected, and following a series of classification steps the training plots were classified. Based on the decision tree all the pixels of the entire study area were analysed and their vegetation types were determined. The classification was validated by field survey. On the studied floodplain area the accuracy of the classification was 83%.