Формализация пространственных характеристик лавиносборов для расчета динамических параметров снежных лавин

<p>Land cover and particularly forests have significant impact on snow avalanche initiation and propagation. Mountain forests can prevent avalanche initiation by stabilizing the snow in release areas, and potentially decelerate an avalanche, thus reducing runout distances. Interaction between forests and avalanches is recognized in avalanche modelling mostly by increasing friction parameters. For instance, the dry –Coulomb friction μ of the Voellmy friction law is thought to summarize snow properties, whereas the velocity-dependent friction ξ aims at representing the roughness of the path potentially related to land cover properties. In this work, we hypothesize on the temporal variability of both friction factors, inherited from their dependability on land cover, particularly the forest fraction, namely the aerial percentage of the terrain covered by forests within the extension of the avalanche path. Specifically, we show how the evolution of the forest fraction within the avalanche path affects the return period of runout distances and further dynamical characteristics of simulated avalanches. First, a Bayesian statistical-dynamical model is used to model avalanche frequency and magnitude on the selected path. The two processes are independently modelled, and the joint posterior distribution is estimated using a sequential Metropolis-Hastings algorithm. The forest-avalanche interaction is represented by increasing the total basal friction within the Voellmy friction law (TBF). Accordingly, to increase TBF, the velocity-dependent friction (turbulent friction) ξ is gradually decreased, whereas the dry –Coulomb friction μ is increased. To that end, ξ is assumed to be exponentially decaying with the forest fraction and is modelled as such. The dry –Coulomb friction μ  is assumed to be normally distributed with parameters characterizing its dependency on the release abscissa, mean release depth and the forest fraction. Then, the return period for runout distances and the whole distribution of velocities, flow depths and pressures corresponding to any return periods is computed for different forest fractions representing the true forest evolution within the studied path. Results for a typical avalanche path of the French Alps notably show that, logically, the larger the forest fraction, the higher the return period, but only for runout distances exceeding a given threshold. Future work will include the explicit calibration of the forest cover dependency within the statistical-dynamical approach.</p><p> </p>

A digital elevation model (DEM) is a digital model or 3D representation of a terrain’s surface. There are many methods to create DEM such as LiDAR, stereo photogrammetry and topographic maps. DEMs are very important for many applications such as extracting terrain parameters for geomorphology and modeling water flow for hydrology or mass movement. A number of websites are available to provide DEM such as SRTM, GTOPO30 and ASTER GDEM but their accuracy differs from one to another and also selecting a small DEM size (high resolution) gives accurate information, but the analysis takes long time. This paper aims to analyze the impact of using different available DEMs on watershed geomorphological properties on order to provide guidelines for users to select the most suitable DEM that obtain an accurate analysis in less time. Three programs; watershed modeling systems: WMS, Global Mapper and Google Earth were used in this study. Three case studies were studied to check the accuracy of these models and select the most accurate one for application. Satellite images downloaded from Google Earth were used as a guide reference for the comparison due to their accuracy and high resolution. The results indicated that the SRTM model was more accurate (95%) for all case studies according to our comparison between its delineation and satellite images. ASTER GDEM is the second most accurate model with an accuracy of 87%, the GTOPO30’s accuracy is 80%.

A digital model of the ground surface has many potential applications in forestry. Nowadays, Light Detection and Ranging (LiDAR) is one of the main sources for collecting morphological data. Point clouds obtained via laser scanning are used for modelling the ground surface by interpolation, a process which is affected by various errors. Using LiDAR data to collect ground surface data for forestry applications is a challenging scenario because the presence of forest vegetation will hinder the ability of laser pulses to reach the ground. The density of ground observations will be therefore reduced and not homogenous (as it is affected by the variations in canopy density). Furthermore, forest areas are generally present in mountainous areas, in which case the interpolation of the ground surface is more challenging. In this paper, we present a comparative analysis of interpolation accuracy for nine algorithms, which are used for generating Digital Terrain Models from Airborne Laser Scanning (ALS) data, in mountainous terrain covered by dense forest vegetation. For most of the algorithms we find a similar performance in terms of general accuracy, with RMSE values between 0.11 and 0.28 m (when model resolution is set to 0.5 m). Five of the algorithms (Natural Neighbour, Delauney Triangulation, Multilevel B-Spline, Thin-Plate Spline and Thin-Plate Spline by TIN) have vertical errors of less than 0.20 m for over 90 percent of validation points. Meanwhile, for most algorithms, major vertical errors (of over 1 m) are associated with less than 0.05 percent of validation points. Digital Terrain Model (DTM) resolution, ground slope and point cloud density influence the quality of the ground surface model, while for canopy density we find a less significant link with the quality of the interpolated DTMs.

This paper investigates the possibilities of improving aboveground forest biomass and basal area weighted mean height estimates from optical multispectral satellite data by adding Canopy Height Models (CHMs) obtained from matching multiple view-angle satellite data. The analysis was carried out using data collected over the Remningstorp test site in southern Sweden from 2008–2011 and used training and validation data from airborne laser scanning and field data. CHMs were produced by subtracting a Digital Elevation Model (based on airborne laser scanning data) from the Digital Surface Models created by matching multiple view-angle SPOT-5 HRS and ALOS PRISM data. By modeling biomass and height using regression analysis on multispectral data from SPOT-5 HRG in combination with height metrics from the CHMs, an improved root mean squared error (RMSE) was attained, compared with using the individual satellite data sources alone. A comparison between SPOT-5 HRS and ALOS PRISM CHMs in combination with multispectral data was made at stand level using biomass and height estimates from laser scanning data as reference data. For biomass, the relative RMSE improved from 32.9% when using only multispectral data, to 29.2% and 22.4% when adding the CHM from SPOT-5 HRS and ALOS PRISM, respectively. The corresponding improvements for height were from 16.1% to 15.3% with the SPOT-5 HRS CHM and to 12.9% with the ALOS PRISM CHM. A further analysis of combining the ALOS PRISM CHM and multispectral data was made at sub-stand level with field measurements as reference data. This combination gave a relative RMSE of 20.6% for biomass and 10.5% for height. In conclusion, the estimation accuracy for aboveground biomass and basal area weighted mean height was improved by adding CHM data to multispectral data from optical satellites.

ABSTRACTQuasi-global, medium-resolution land surface models – the Shuttle Radar Topography Mission digital elevation model (SRTM1 DEM), the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global DEM (ASTER GDEM), and the Advanced Land Observing Satellite World 3D digital surface model (AW3D30 DSM) – are widely used in geosciences. We carried out a comparative analysis of accuracy for these models exemplified by the Zaoksky testing ground, Central European Russia. First, we extracted related portions from the SRTM1 DEM, ASTER GDEM, and AW3D30 DSM for the study area. In the further analysis, we used 69 ground control points (GCPs) within the testing ground, as well as a reference DEM photogrammetrically generated from aerial stereo images. For each GCP, we determined an elevation value in four models and a related vertical error. For each model, we carried out a statistical analysis of vertical errors. To visualize the spatial distribution of vertical errors, we calculated matrices of residuals between the reference DEM and the quasi-global models. The results demonstrate that the AW3D30 DSM can be considered the most accurate quasi-global, medium-resolution land surface model. We do not recommend the use of the ASTER GDEM because it is marked by high errors with chaotically distributed hummock-like patterns.

A methodology for a cost-effective and detailed assessment of the riparian zone of segments (/spl sim/30 km) of the Brisbane River and Lockyer Creek in Queensland, Australia is described. Digital terrain models (DTMs) of the stream banks as well as detailed maps of the riparian vegetation type and structure were produced using airborne laser scanner and digital video data. The methodology is applicable to almost any stream or river system worldwide. DTMs of the river banks and adjacent land approximately 100 m from the waters edge were produced from the laser scanner data with an accuracy of 30 cm or better for 80% of the data. Open areas with little understorey or grass cover tended to be accurate to approximately 10 cm. Vegetation maps at a scale of approximately 1:4,000 were produced. Each clump of shrubs or small trees as well as larger individual trees were delineated and attributed with species, weed infestation levels, height and foliage projected cover (FPC) values. The vegetation mapping was completed through classification of the laser data and manual interpretation of the video imagery supported by field verification. The accuracy of the floristic components of the vegetation map is estimated to be approaching 100% although validation has not yet been completed. The spatial accuracy of vegetation polygons delineated is approximately one meter. The laser data as captured for this project allows for maps to be produced at a scale of 1:1000.

Slope angle and aspect as influencing factors on the accuracy of the SRTM and the ASTER GDEM databases

In this paper, the results of an experiment about the vertical accuracy of generated digital terrain models were assessed. The created models were based on two techniques: LiDAR and photogrammetry. The data were acquired using an ultralight laser scanner, which was dedicated to Unmanned Aerial Vehicle (UAV) platforms that provide very dense point clouds (180 points per square meter), and an RGB digital camera that collects data at very high resolution (a ground sampling distance of 2 cm). The vertical error of the digital terrain models (DTMs) was evaluated based on the surveying data measured in the field and compared to airborne laser scanning collected with a manned plane. The data were acquired in summer during a corridor flight mission over levees and their surroundings, where various types of land cover were observed. The experiment results showed unequivocally, that the terrain models obtained using LiDAR technology were more accurate. An attempt to assess the accuracy and possibilities of penetration of the point cloud from the image-based approach, whilst referring to various types of land cover, was conducted based on Real Time Kinematic Global Navigation Satellite System (GNSS-RTK) measurements and was compared to archival airborne laser scanning data. The vertical accuracy of DTM was evaluated for uncovered and vegetation areas separately, providing information about the influence of the vegetation height on the results of the bare ground extraction and DTM generation. In uncovered and low vegetation areas (0–20 cm), the vertical accuracies of digital terrain models generated from different data sources were quite similar: for the UAV Laser Scanning (ULS) data, the RMSE was 0.11 m, and for the image-based data collected using the UAV platform, it was 0.14 m, whereas for medium vegetation (higher than 60 cm), the RMSE from these two data sources were 0.11 m and 0.36 m, respectively. A decrease in the accuracy of 0.10 m, for every 20 cm of vegetation height, was observed for photogrammetric data; and such a dependency was not noticed in the case of models created from the ULS data.

Detection and extraction of mining-induced ground deformation can be used to understand the deformation process and space distribution and to estimate the deformation laws and trends. This study focuses on the application of ground deformation detection and extraction combined with digital surface model (DSM), derived from China’s ZiYuan-3 (ZY-3) satellite stereo imagery and the advanced spaceborne thermal emission and reflection radiometer global digital elevation model (ASTER GDEM) data. A district covering 200 km2 around the west open-pit mine in Fushun of Liaoning Province, a city located in Northeast China, is chosen as the study area. Regional overall deformation, typical region deformation, and topographical profile deformation are extracted to analyze the distribution and the link between the regional ground deformations. The results show that the mean elevation has already increased by 3.12 m from 2010 to 2015; 71.18% of this area is deformed, and 22.72% of this area has an elevation variation of more than 10 m. Four districts of rising elevation and three districts of descending elevation are extracted. They are deformed with distinct elevation and volume changes. The total area with distinct rising elevation (>15 m) is about 8.44 km2, and the change in volume is 2.47 × 108 m3. However, the total area with distinct descending elevation (<−10 m) is about 6.12 km2, and the change in volume is 2.01 × 108 m3. Moreover, the deformation in the local mining area has expanded to the surrounding areas. Experiments in the mining area demonstrate that ground deformation, especially acute deformation such as large fractures or landslides, can be monitored using DSMs derived from ZY-3 satellite stereo images.

Topographical information is fundamental to many geo-spatial related information and applications on Earth. Remote sensing satellites have the advantage in such fields because they are capable of global observation and repeatedly. Several satellite-based digital elevation datasets were provided to examine global terrains with medium resolutions e.g. the Shuttle Radar Topography Mission (SRTM), the global digital elevation model by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER GDEM). A new global digital surface model (DSM) dataset using the archived data of the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) onboard the Advanced Land Observing Satellite (ALOS, nicknamed “Daichi”) has been completed on March 2016 by Japan Aerospace Exploration Agency (JAXA) collaborating with NTT DATA Corp. and Remote Sensing Technology Center, Japan. This project is called “ALOS World 3D” (AW3D), and its dataset consists of the global DSM dataset with 0.15 arcsec. pixel spacing (approx. 5 m mesh) and ortho-rectified PRISM image with 2.5 m resolution. JAXA is also processing the global DSM with 1 arcsec. spacing (approx. 30 m mesh) based on the AW3D DSM dataset, and partially releasing it free of charge, which calls “ALOS World 3D 30 m mesh” (AW3D30). The global AW3D30 dataset will be released on May 2016. This paper describes the processing status, a preliminary validation result of the AW3D30 DSM dataset, and its public release status. As a summary of the preliminary validation of AW3D30 DSM, 4.40 m (RMSE) of the height accuracy of the dataset was confirmed using 5,121 independent check points distributed in the world.

Abstract. In 2016, the first processing of the semi-global digital surface models (DSMs) utilizing all the archives of stereo imageries derived from the Panchromatic Remote sensing Instrument for Stereo Mapping (PRISM) onboard the Advanced Land Observing Satellite (ALOS) was successfully completed. The dataset was freely released to the public in 30 m grid spacing as the ‘ALOS World 3D - 30m (AW3D30)’, which was generated from its original version processed in 5 m or 2.5 m grid spacing. The dataset has been updated since then to improve the absolute/relative height accuracies with additional calibrations. However, the most significant update that should be applied for improving the data usability is the filling of void areas, which correspond to approx. 10% of semiglobal coverage, mostly due to cloud covers. In 2020, we completed the filling process by using other open-access digital elevation models (DEMs) such as Shuttle Radar Topography Mission (SRTM) DEM, Advanced Spaceborne Thermal Emission and Reflection Radiometer Global DEM (ASTER GDEM), ArcticDEM, etc., except for Antarctica. In this paper, we report on the filling process of the remaining voids in Antarctica by using other open-access DEMs such as Reference Elevation Model of Antarctica (REMA) DSM, TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X, TDX) 90m DEM, and ASTER GDEM to complete the void-free semi-global AW3D30 datasets.

Sagittal plane motion in the human lumbar spine: Comparison of the in vitro quasistatic neutral zone and dynamic motion parameters

Abstract. Airborne laser scanning has become a standard method for recording topographic data. A new generation of laser scanners digitises the complete waveform of the backscattered signal and thus offers the possibility of analysing the signal shape. As a product of the laser scanning, a digital surface model (DSM) or a digital terrain model (DTM) can be derived. In water regions, data acquisition by laser scanning is limited to the water surface because the near-infrared laser pulses hardly penetrate water. Therefore, a height model generated from laser scanner point clouds over water regions does not represent the actual terrain. The generation of a DTM thus requires the detection of water surfaces. In this study, a method for the detection and classification of water surfaces in airborne laser scanning data is proposed. The method works with both geometrical features (e.g. height or height variation) and characteristics of the pulses derived from the full waveform of the returned signal (e.g. intensity or pulse width). In our strategy, based on fuzzy logic, all classification parameters are derived automatically from training areas. According to their statistical distributions, the features are considered with individual weights. The aim of this paper is to analyse crucial features for classification and to investigate the potential of full waveform laser scanning data for this application. We present results from different areas with lakes and rivers, analysing the contribution of the individual groups of features for the detection of water surfaces.

Abstract. Urban environments face increasing challenges related to thermal discomfort and heat stress due to climate change and rapid urbanization. This study presents a methodology for developing a 4D digital thermal comfort model by integrating time-series pedestrian-level microclimate measurements with a 3D urban model. A mobile field campaign in Rabat, Morocco, collected air temperature, relative humidity, wind speed, and black globe temperature at 22 sampling points over 9 summer days. These measurements were used to calculate the Universal Thermal Climate Index (UTCI). A detailed 3D urban model was created from laser scanning data, featuring Level of Detail 3 (LoD3) for buildings and trees of interest. UTCI point measurements were spatially interpolated using Empirical Bayesian Kriging 3D combined with shading analysis. The interpolated hourly 3D UTCI maps were combined into a voxel dataset through an automated Python workflow, enabling dynamic visualization of thermal comfort evolution. Results revealed distinct diurnal patterns with UTCI values ranging from 17°C (no thermal stress) to 43°C (very strong heat stress), with relatively consistent spatial patterns. Vegetation demonstrated significant cooling effects, with broad-canopied species providing 3-5°C UTCI reduction compared to unshaded areas, while tall palm trees offered minimal cooling, as expected. Interestingly, some vegetation areas exhibited complex thermal behaviour, appearing slightly warmer during morning and evening periods. The approach provides insights into the temporal dynamics of pedestrian-level thermal comfort, establishing a promising foundation for climate-responsive urban planning interventions in Moroccan cities.

Pyroclastic flows from Unzen were generated by gravitational collapse of the growing lava dome. As soon as the parental lobe failed at the edge of the dome, spontaneous shattering of lava occurred and induced a gravity flow of blocks and finer debris. The flows had a overhanging, tongue-like head and cone- or rollershaped vortices expanding outward and upward. Most of the flows traveled from 1 to 3 km, but some flows reached more than 4 km, burning houses and killing people in the evacuated zone of Kita-kamikoba on the eastern foot of the volcano. The velocities of the flows ranged from 15 to 25 m/s on the gentle middle flank. Observations of the flows and their deposits suggest that they consisted of a dense basal avalanche and an overlying turbulent ash cloud. The basal avalanche swept down a topographic low and formed to tongue-like lobe having well-defined levees; it is presumed to have moved as a non-Newtonian fluid. The measured velocities and runout distances of the flows can be matched to a Bingham model for the basal avalanche by the addition of turbulent resistance. The rheologic model parameters for the 29 May flow are as follows: the density is 1300 kg/m3, the yield strength is 850 Pa, the viscosity is 90 Pa s, and the thickness of the avalanche is 2 m. The ash cloud is interpreted as a turbulent mixing layer above the basal avalanche. The buoyant portions of the cloud produced ash-fall deposits, whereas the dense portions moved as a surge separated from the parental avalanche. The ash-cloud surges formed a wide devastated zone covered by very thin debris. The initial velocities of the 3 June surges, when they detached from avalanches, are determined by the runout distance and the angle of the energy-line slope. A comparison between the estimated velocities of the 3 June avalanches and the surges indicates that the surges that extended steep slopes along the avalanche path, detached directly from the turbulent heads of the avalanches. The over-running surge that reached Kita-Kamikoba had an estimated velocity higher than that of the avalanche; this farther-travelled surge is presumed to have been generated by collapse of a rising ash-cloud plume.