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461 records · Page 26

RivGraph: Automatic extraction and analysis of river and delta channel network topology

River networks sustain life and landscapes by carrying and distributing water, sediment, and nutrients throughout ecosystems and communities. At the largest scale, river networks drain continents through tree-like tributary networks. At typically smaller scales, river deltas and braided rivers form loopy, complex distributary river networks via avulsions and bifurcations.In order to model flows through these networks or analyze network structure, the topology, or connectivity, of the network must be resolved. Additionally, morphologic properties of each river channel as well as the direction of flow through the channel inform how fluxes travel through the network’s channels. Riv Graphis a Python package that automates the extraction and characterization of river channel networks from a user-provided binary image, or mask, of a channel network (Fig. 1). Masks may be derived from (typically remotely-sensed) imagery, simulations, or even hand-drawn. RivGraph will create explicit representations of the channel network by resolving river centerlines as links, and junctions as nodes. Flow directions are solved for each link of the network without using auxiliary data, e.g., a digital elevation model (DEM). Morphologic properties are computed as well, including link lengths, widths, sinuosities, branching angles,and braiding indices. If provided,RivGraph will preserve georeferencing information of the mask and will export results as ESRI shapefiles, GeoJSONs, and GeoTIFFs for easy import into GIS software.RivGraph can also return extracted networks as networkx objects for convenient interfacing with the full-featured networkx package (Hagberg et al., 2008). Finally, RivGraph offers a suite of topologic metrics that were specifically designed for river channel network analysis (Tejedor et al., 2015b).

54 ENVIRONMENTAL SCIENCES↗

NGEE Arctic Plant Traits: Plant Community Composition, Kougarok Road Mile Marker 64, Seward Peninsula, Alaska, 2016

This dataset reports the characteristics of the dominant vegetation communities at the NGEE Arctic Kougarok field site, Kougarok Road Mile Marker 64 on the Seward Peninsula. Selected plots were surveyed from 18-23 July 2016. Environmental data (e.g., elevation, slope, soil moisture regime, disturbance type and degree, mean canopy height, etc.) were also recorded for each plot. Elevation measurements were updated 2020-08-18. All plant species (vascular plants, bryophytes and lichens) were recorded along with their percent cover in the plots as determined visually by the lead author. Plots were chosen subjectively in areas of homogeneous and representative vegetation and varied in size from 1-25 m2 depending on canopy structure and height. The site is an east-facing hillslope with vegetation that varies from the summit to the toeslope. The 30 total plots were selected as five replicate plots sampled from each of the six identified habitat types: 1) non-acidic mountain complex at the hillcrest, 2) dwarf-shrub lichen tundra on the shoulder, 3) alder shrublands predominantly on an elevational band across the backslope, 4) willow-birch tundra on the upper backslope, 5) tussock tundra on the footslope in inter-water tracks, and 6) tussock tundra mixed with willow-birch tundra or alder savanna in poor developed water tracks on the footslope. This dataset is comprised of two comma-separated (*.csv) files containing species and environmental data for the plant community composition plots. It also contains seven zipped folders of plot photographs, one map showing plot locations (*.pdf), one blank datasheet with the key to codes used in the field (*.pdf), select photos organized in a (*.pdf), and one User file (*.pdf). The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

(abstract) Timing and Extent of Wurm-Wisconsinan Deglaciation and Subsequent Rebound in Antarctica

Recent information from glacio-geomorphologists, when coupled to new glacio-sedimentary dating of the grounded ice sheet in the Ross Embayment at the last glacial maximum, leads to the conclusion that global geophysical models might require some revision. We investigate such new models and the possible implications for observable geodetic signatures, such as rebound-driven temporal variations in the Earth's low-order gravity field and in vertical crustal motions.

Antarctica↗

Studying the Sky/Planets Can Drown You in Images: Machine Learning Solutions at JPL/Caltech

JPL is working to develop a domain-independent system capable of small-scale object recognition in large image databases for science analysis. Two applications discussed are the cataloging of three billion sky objects in the Sky Image Cataloging and Analysis Tool (SKICAT) and the detection of possibly one million small volcanoes visible in the Magellan synthetic aperture radar images of Venus (JPL Adaptive Recognition Tool, JARTool).

geomorphology↗

Back to Mars: The Mars Pathfinder Mission

Mars Pathfinder successfully landed on the surface of Mars on July 4, 1997, and ushered in a new era in Mars exploration. This era will feature numberous low cost missions which will perform important science investigations and engage the world's population in the excitement of planetary exploration.

Mars↗

Crater Population on Asteroid (101955) Bennu Indicates Impact Armouring and a Young Surface

The impactor-to-crater size scaling relationships that enable estimates of planetary surface ages rely on an accurate formulation of impactor–target physics. An armouring regime, specific to rubble-pile surfaces, has been proposed to occur when an impactor is comparable in diameter to a target surface particle (for example, a boulder). Armouring is proposed to reduce crater diameter, or prevent crater formation in the asteroid surface, at small crater diameters. Here, using measurements of 1,560 craters on the rubble-pile asteroid (101955) Bennu, we show that the boulder population controls a transition from crater formation to armouring at crater diameters ~2–3 m, below which crater formation in the bulk surface is increasingly rare. By combining estimates of impactor flux with the armouring scaling relationship, we find that Bennu’s crater retention age (surface age derived from crater abundance) spans from 1.6–2.2 Myr for craters less than a few meters to ~10–65 Myr for craters >100 m in diameter, reducing the maximum surface age by a factor of >15 relative to previous estimates. The range of crater retention ages, together with latitudinal variations in large-crater spatial density, indicate that ongoing resurfacing processes render the surface many times younger than the bulk asteroid.

Asteroids↗