Using fractal geometry to make rapid field measurements of riverbed topography at ecologically useful spatial scales

2002 ◽  
Vol 53 (6) ◽  
pp. 999 ◽  
Author(s):  
B. J. Robson ◽  
E. T. Chester ◽  
L. A. Barmuta
Keyword(s):  
Fractal Dimension ◽  
Fractal Geometry ◽  
Random Sampling ◽  
Spatial Scales ◽  
Field Measurements ◽  
Habitat Types ◽  
River Bed ◽  
Bed Roughness ◽  
Rolling Balls

A method is described for making rapid in situ field measurements of riverbed topography over spatial scales of ≅1–10 m. This method uses rolling balls to make quick, accurate measurements of river-bed roughness at several spatial scales. Random sampling and replication generate multiple estimates of the fractal dimension (d) that can be used to test for significant differences in the complexity of riverbed architecture between habitat types and spatial scales.

Impact of variability in measured and simulated tundra snowpack properties on heat transfer metrics

2021 ◽  
Author(s):  
Victoria Dutch ◽  
Nick Rutter ◽  
Leanne Wake ◽  
Mel Sandells ◽  
Chris Derksen ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Spatial Variability ◽  
Spatial Scales ◽  
Field Measurements ◽  
Density Profiles ◽  
Community Land Model ◽  
Spatially Distributed ◽  
Snowpack Properties ◽  
The Impact

<p>Tundra snowpack properties are highly heterogenous over a variety of spatial scales and evolve over the course of the winter. Variations in snowpack properties such as snow density and microstructure control the transfer of heat through the snowpack. Thermal properties of the snowpack impact the subnivean environment; snow insulates the underlying soil, allowing films of liquid water to remain unfrozen, enabling biological processes to take place. In this study, field measurements from four field campaigns across two different winters (March and November 2018, January and March 2019) are used to capture and constrain the spatial variability of the snowpack. These include 1050 spatially distributed Snow MicroPenetrometer (SMP) profiles throughout the Trail Valley Creek catchment in the Northwest Territories, Canada. Bespoke coefficients for tundra snowpacks were calculated (based on the work of King et al., 2020) to convert raw SMP force measurements to densities. This allowed density changes of vertical profiles to be assessed and spatial variability in the thickness and properties of three snowpack layers (wind slab, indurated hoar and depth hoar) to be quantified. 105 needleprobe measurements from 37 snowpits were used to contrast the density and thermal conductivity of snowpack layers, as well as thermal conductivities estimated from recalibrated SMP density profiles. These in-situ measurements will be compared to 1-D simulations of snowpack properties from the Community Land Model (PTCLM 5.0) over the two winter seasons. The impact of snowpack layering on snow heat transfer metrics will be investigated using both 2-layer (wind slab: depth hoar) and 3-layer (wind slab: indurated hoar: depth hoar) snowpack configurations. The spatial variability of heat transfer metrics across the Trail Valley Creek catchment will also be considered.</p>

scholarly journals Modeling volcanic ash aggregation processes and related impacts on the April/May 2010 eruptions of Eyjafjallajökull Volcano with WRF-Chem

2019 ◽  
Author(s):  
Sean D. Egan ◽  
Martin Stuefer ◽  
Peter W. Webley ◽  
Taryn Lopez ◽  
Catherine F. Cahill ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Volcanic Ash ◽  
Field Measurements ◽  
Volcanic Eruptions ◽  
Collision Kernel ◽  
Aggregation Process ◽  
Airborne Measurements ◽  
Aggregation Processes ◽  
Ash Transport

Abstract. Volcanic eruptions eject ash and gases into the atmosphere that can contribute to significant hazards to aviation, public and environment health, and the economy. Several volcanic ash transport and dispersion (VATD) models are in use to simulate volcanic ash transport operationally, but none include a treatment of volcanic ash aggregation processes. Volcanic ash aggregation can greatly reduce the atmospheric budget, dispersion and lifetime of ash particles and therefore its impacts. To enhance our understanding and modeling capabilities of the ash aggregation process, a volcanic ash aggregation scheme was integrated into the Weather Research Forecasting with online Chemistry (WRF-Chem) model. Aggregation rates and ash mass loss in this modified code are calculated in-line with the meteorological conditions, providing a fully coupled treatment of aggregation processes. The updated-model results were compared to field measurements of tephra fallout and in situ airborne measurements of ash particles from the April/May 2010 eruptions of Eyjafjallajökull Volcano, Iceland. WRF-Chem, coupled with the newly added aggregation code, modeled ash clouds that agreed spatially and temporally with these in situ and field measurements. A sensitivity study provided insights into the mechanics of the aggregation code by analyzing each aggregation process (collision kernel) independently, as well as by varying the fractal dimension of the newly formed aggregates. In addition, the airborne lifetime (e-folding) of total domain ash mass was analyzed for a range of fractal dimension, and a maximum reduction of 79.5 % of the airborne ash lifetime was noted.

scholarly journals Evaluating the influence of erosion and tectonic processes on California’s topography by measuring its fractal dimension and anisotropy across scales

2021 ◽  
Author(s):  
Hervé Guillon ◽  
Belize Lane ◽  
Colin F. Byrne ◽  
Gregory B. Pasternack ◽  
Samuel Sandoval Solis
Keyword(s):  
Fractal Dimension ◽  
Spatial Scales ◽  
Bedload Transport ◽  
Friction Laws ◽  
Erosion Processes ◽  
Bed Elevation ◽  
Tectonic Processes ◽  
Auto Correlation ◽  
River Bed ◽  
End Members

<p>Roughness is paramount in Earth sciences, and landscapes, laboratory alluvial fans, river bed elevation, bedload transport and the friction laws of fluid mechanics all exhibit a fractal behavior described by a scale-persistent roughness. Yet, for a given landscape, the exact meaning of statistical roughness, or fractal dimension, remains unclear. The fractal dimension of topography is mainly understood as two end-members: at large spatial scales, it describes tectonic processes; at small spatial scales it describes erosion processes. In this study, we nuance this description by identifying the spatial scale at which erosion processes are inadequately described by fractal dimension and provide quantitative bounds on the meaning of the statistical roughness of topography at scales from 0.25 km to 100 km using three lines of evidence. First, we leverage spatial statistics to evaluate the auto-correlation structure of topographic statistical roughness across the physiographically diverse state of California, USA. Second, we identify the down-slope and across-slope directions using two-dimensional Fourier analysis, and measure the anisotropy of topography by evaluating statistical roughness in each direction. Third, we perform a spatial correlation analysis between statistical roughness and the Péclet number which describes the balance between diffusion and incision processes. Our preliminary results indicate that correlation between statistical roughness and Péclet number fades at scales greater than 4.6 km. In addition, auto-correlation saturation occurs for statistical roughness at scales greater than 16.5 km. Hence our analysis provides a more nuanced description of the statistical roughness of topography: it represents erosion processes at scales up to 4.6 km while being dominated by tectonics at scales greater than 16.5 km.</p>

Imaging solar-terrestrial interactions on the global scale: The SMILE mission

2021 ◽  
Author(s):  
Graziella Branduardi-Raymont ◽  
Chi Wang ◽  
C. Philippe Escoubet ◽  
Steve Sembay ◽  
Eric Donovan ◽  
...  
Keyword(s):  
Solar Wind ◽  
Spatial Scales ◽  
Field Measurements ◽  
Scientific Data ◽  
Current Status ◽  
The Sun ◽  
Particle Injection ◽  
X Ray ◽  
X Ray Imaging

<p>A key link in the Sun – Earth connection is the solar wind coupling with the terrestrial magnetosphere. Mass and energy enter geospace via dayside magnetic reconnection; reconnection in the tail leads to release of energy and particle injection deep into the magnetosphere, causing geomagnetic substorms. The end product of these processes is the visual manifestation of variable auroral emissions. These have been observed both from the ground and from space, the latter for relatively short continuous periods of time. In situ measurements by a fleet of solar wind and magnetospheric missions, current and planned, can provide the most detailed observations of the plasma conditions both in the incoming solar wind and magnetospheric plasma. However, we are still unable to quantify the global effects of the drivers of Sun - Earth connections, and to monitor their evolution with time. This information is the key missing link for developing a comprehensive understanding of how the Sun gives rise to and controls the Earth's plasma environment and space weather. We are now able to take a novel approach to global monitoring of geospace: X-ray imaging of the magnetosheath and cusps is made possible by the X-ray emission produced in the process of solar wind charge exchange, first observed at comets, and subsequently found to occur in the vicinity of solar system planets, including the Earth's magnetosphere. This is where SMILE (Solar wind Magnetosphere Ionosphere Link Explorer) comes in.</p><p>SMILE is a novel self-standing mission dedicated to observing the solar wind – magnetosphere coupling at Earth via simultaneous X-ray imaging of the magnetosheath and polar cusps (large spatial scales at the magnetopause), UV imaging of global auroral distributions (mesoscale structures in the ionosphere) and in situ solar wind/magnetosheath plasma and magnetic field measurements. SMILE will provide scientific data on solar wind – magnetosphere interaction at the global level while monitoring it continuously for long, uninterrupted periods of time from a highly elliptical northern polar orbit.</p><p>SMILE is a collaborative mission between ESA and the Chinese Academy of Sciences that was selected in Nov. 2015, adopted into ESA’s Cosmic Vision Programme in March 2019, and is due for launch at the end of 2024. The novel science that SMILE will deliver, the ongoing technical developments and scientific preparations, and the current status of the mission, will be presented.</p>

scholarly journals Spatial scales of snow texture as indicator for snow class

2010 ◽  
Vol 51 (54) ◽  
pp. 55-63 ◽  
Author(s):  
P.K. Satyawali ◽  
M. Schneebeli
Keyword(s):  
Fractal Dimension ◽  
Spatial Scales ◽  
Field Measurements ◽  
Small Scale ◽  
Large Numbers ◽  
Penetration Force ◽  
Parallel Direction ◽  
The Alps ◽  
Natural Snow ◽  
Fast Classification

AbstractA method for automated and fast classification of snow texture would be useful for applications where snow structure must be quantified. Large numbers of field measurements were carried out on natural snow in order to investigate small-scale variations of the micro-penetration force. Snow characterization was done for snow from the Himalaya and the Alps, using a high-resolution snow penetrometer (SnowMicroPen). Measurements of snow resistance at equal intervals of 4 μm were geostatistically evaluated. The range parameter (correlation length, or CL) of penetration force was estimated for all major snow classes from the sample semivariogram. Average CL was lowest for new snow and highest for melt–freeze snow. For major snow classes, CL was found to increase with snow density. Ground-perpendicular and ground-parallel snow profiles were also obtained for homogeneous snow, and CL was estimated along these directions. New snow showed larger CL in the ground-parallel direction, and depth-hoar snow showed larger CL in the ground-perpendicular direction. Based on CL, the directional anisotropy was calculated. An attempt was also made to show the relationship between CL and texture index. The semivariogram was used to estimate the fractal dimension. Both CL and fractal dimension were found to be potential parameters to describe snow.

A protocol for sampling pastures in hill country

2016 ◽  
Vol 78 ◽  
pp. 203-209 ◽  
Author(s):  
K.J. Hutchinson ◽  
D.R. Scobie ◽  
J. Beautrais ◽  
A.D. Mackay ◽  
G.M. Rennie ◽  
...  
Keyword(s):  
Random Sampling ◽  
Geographical Information Systems ◽  
Field Measurements ◽  
Decision Support Tool ◽  
Accurate Estimate ◽  
Ease Of Use ◽  
Geographical Information ◽  
Support Tool ◽  
Topographic Complexity ◽  
Hill Country

To develop a protocol to guide pasture sampling for estimation of paddock pasture mass in hill country, a range of pasture sampling strategies, including random sampling, transects and stratification based on slope and aspect, were evaluated using simulations in a Geographical Information Systems computer environment. The accuracy and efficiency of each strategy was tested by sampling data obtained from intensive field measurements across several farms, regions and seasons. The number of measurements required to obtain an accurate estimate was related to the overall pasture mass and the topographic complexity of a paddock, with more variable paddocks requiring more samples. Random sampling from average slopes provided the best balance between simplicity and reliability. A draft protocol was developed from the simulations, in the form of a decision support tool, where visual determination of the topographic complexity of the paddock, along with the required accuracy, were used to guide the number of measurements recommended. The protocol was field tested and evaluated by groups of users for efficacy and ease of use. This sampling protocol will offer farmers, consultants and researchers an efficient, reliable and simple way to determine pasture mass in New Zealand hill country settings. Keywords: hill country, feed budgeting, protocol pasture mass, slope

Optimal Density Determination of Bouguer Anomaly Using Fractal Analysis (Case of study: Charak area,IRAN)

2005 ◽  
Vol 1 (1) ◽  
pp. 21-24
Author(s):  
Hamid Reza Samadi
Keyword(s):  
Surface Roughness ◽  
Fractal Dimension ◽  
Fractal Analysis ◽  
Fractal Geometry ◽  
Host Rock ◽  
Bouguer Anomaly ◽  
Research Area ◽  
Density Difference ◽  
Optimal Density

In exploration geophysics the main and initial aim is to determine density of under-research goals which have certain density difference with the host rock. Therefore, we state a method in this paper to determine the density of bouguer plate, the so-called variogram method based on fractal geometry. This method is based on minimizing surface roughness of bouguer anomaly. The fractal dimension of surface has been used as surface roughness of bouguer anomaly. Using this method, the optimal density of Charak area insouth of Hormozgan province can be determined which is 2/7 g/cfor the under-research area. This determined density has been used to correct and investigate its results about the isostasy of the studied area and results well-coincided with the geology of the area and dug exploratory holes in the text area

scholarly journals Mapping High Spatiotemporal-Resolution Soil Moisture by Upscaling Sparse Ground-Based Observations Using a Bayesian Linear Regression Method for Comparison with Microwave Remotely Sensed Soil Moisture Products

2021 ◽  
Vol 13 (2) ◽  
pp. 228
Author(s):  
Jian Kang ◽  
Rui Jin ◽  
Xin Li ◽  
Yang Zhang
Keyword(s):  
Soil Moisture ◽  
Large Scale ◽  
Spatial Scales ◽  
Microwave Remote Sensing ◽  
In Situ Measurements ◽  
Spatial Density ◽  
Linear Regression Method ◽  
Spatiotemporal Resolution ◽  
Pixel Scale

In recent decades, microwave remote sensing (RS) has been used to measure soil moisture (SM). Long-term and large-scale RS SM datasets derived from various microwave sensors have been used in environmental fields. Understanding the accuracies of RS SM products is essential for their proper applications. However, due to the mismatched spatial scale between the ground-based and RS observations, the truth at the pixel scale may not be accurately represented by ground-based observations, especially when the spatial density of in situ measurements is low. Because ground-based observations are often sparsely distributed, temporal upscaling was adopted to transform a few in situ measurements into SM values at a pixel scale of 1 km by introducing the temperature vegetation dryness index (TVDI) related to SM. The upscaled SM showed high consistency with in situ SM observations and could accurately capture rainfall events. The upscaled SM was considered as the reference data to evaluate RS SM products at different spatial scales. In regard to the validation results, in addition to the correlation coefficient (R) of the Soil Moisture Active Passive (SMAP) SM being slightly lower than that of the Climate Change Initiative (CCI) SM, SMAP had the best performance in terms of the root-mean-square error (RMSE), unbiased RMSE and bias, followed by the CCI. The Soil Moisture and Ocean Salinity (SMOS) products were in worse agreement with the upscaled SM and were inferior to the R value of the X-band SM of the Advanced Microwave Scanning Radiometer 2 (AMSR2). In conclusion, in the study area, the SMAP and CCI SM are more reliable, although both products were underestimated by 0.060 cm3 cm−3 and 0.077 cm3 cm−3, respectively. If the biases are corrected, then the improved SMAP with an RMSE of 0.043 cm3 cm−3 and the CCI with an RMSE of 0.039 cm3 cm−3 will hopefully reach the application requirement for an accuracy with an RMSE less than 0.040 cm3 cm−3.

scholarly journals Underwater Holographic Sensor for Plankton Studies In Situ Including Accompanying Measurements

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4863
Author(s):  
Victor Dyomin ◽  
Alexandra Davydova ◽  
Igor Polovtsev ◽  
Alexey Olshukov ◽  
Nikolay Kirillov ◽  
...  
Keyword(s):  
World Ocean ◽  
Field Tests ◽  
Field Measurements ◽  
Measuring Systems ◽  
Water Turbidity ◽  
Background Data ◽  
Average Size ◽  
Size Dispersion

The paper presents an underwater holographic sensor to study marine particles—a miniDHC digital holographic camera, which may be used as part of a hydrobiological probe for accompanying (background) measurements. The results of field measurements of plankton are given and interpreted, their verification is performed. Errors of measurements and classification of plankton particles are estimated. MiniDHC allows measurement of the following set of background data, which is confirmed by field tests: plankton concentration, average size and size dispersion of individuals, particle size distribution, including on major taxa, as well as water turbidity and suspension statistics. Version of constructing measuring systems based on modern carriers of operational oceanography for the purpose of ecological diagnostics of the world ocean using autochthonous plankton are discussed. The results of field measurements of plankton using miniDHC as part of a hydrobiological probe are presented and interpreted, and their verification is carried out. The results of comparing the data on the concentration of individual taxa obtained using miniDHC with the data obtained by the traditional method using plankton catching with a net showed a difference of no more than 23%. The article also contains recommendations for expanding the potential of miniDHC, its purpose indicators, and improving metrological characteristics.

scholarly journals Laboratory and In Situ Determination of Hydraulic Conductivity and Their Validity in Transient Seepage Analysis

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1131
Author(s):  
Soonkie Nam ◽  
Marte Gutierrez ◽  
Panayiotis Diplas ◽  
John Petrie
Keyword(s):  
Hydraulic Conductivity ◽  
Field Measurements ◽  
Natural Soil ◽  
In Situ Tests ◽  
Seepage Analysis ◽  
Soil Deposits ◽  
Seepage Modeling ◽  
Sample Disturbance

This paper critically compares the use of laboratory tests against in situ tests combined with numerical seepage modeling to determine the hydraulic conductivity of natural soil deposits. Laboratory determination of hydraulic conductivity used the constant head permeability and oedometer tests on undisturbed Shelby tube and block soil samples. The auger hole method and Guelph permeameter tests were performed in the field. Groundwater table elevations in natural soil deposits with different hydraulic conductivity values were predicted using finite element seepage modeling and compared with field measurements to assess the various test results. Hydraulic conductivity values obtained by the auger hole method provide predictions that best match the groundwater table’s observed location at the field site. This observation indicates that hydraulic conductivity determined by the in situ test represents the actual conditions in the field better than that determined in a laboratory setting. The differences between the laboratory and in situ hydraulic conductivity values can be attributed to factors such as sample disturbance, soil anisotropy, fissures and cracks, and soil structure in addition to the conceptual and procedural differences in testing methods and effects of sample size.

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