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Lawrence V. Stanislawski

Publications and source records attributed to Lawrence V. Stanislawski.

24 records · Page 2Linked to original sources

Channel cross-section analysis for automated stream head identification

Headwater streams account for more than half of the streams in the United States by length. The substantial occurrence and susceptibility to change of headwater streams makes regular updating of related maps vital to the accuracy of associated analysis and display. Here we present work testing new methods of completely automated remote headwater stream identification using metrics derived from channel Digital Elevation Model (DEM) cross-sections. A jump in standard deviation of curvature (sK) is found to correlate with the presence of stream heads. Field and remotely validated stream and channel initiation points from 4 diverse study areas in North Carolina as well as a simulated surface are used to test the sK findings. The sK value within individual catchments equal to 0.5*Tukey's upper inner fence is found to be a reliable threshold for identifying the upslope extent of channels in varied landscapes.

Environmental Modelling & Software↗

OpenCLC: An open-source software tool for similarity assessment of linear hydrographic features

The National Hydrography Dataset (NHD) is a foundational geospatial data source in the United States that enables extensive and diverse environmental research and supports decision-making in numerous contexts. However, the NHD requires regular validation and update given possible inconsistent initial collection and hydrographic changes. Furthermore, systems or tools that use NHD data must manage regular updates that occur within the high-resolution version of the NHD (NHD HR). This research contributes to filling this gap by establishing an open-source software tool named OpenCLC, which automatically identifies matching and mismatching line features between two sets of hydrographic flowlines. Aside from identifying differences among two version of NHD lines, results can be applied to improve the quality of NHD HR content. OpenCLC significantly outperforms the best available commercial off-the-shelf software in computational scalability, and it is made widely available as part of the CyberGIS Toolkit to benefit broad environmental and geospatial science communities.

SoftwareX↗

Preserving meander bend geometry through scale

Stream meander geometry is a function of hydrologic, geologic, and anthropogenic forces. Meander morphometrics are used in geomorphic classification, ecological characterization, and tectonic and hydrologic change detection. Thus, detailed measurement and classification of meander geometry is imperative to multiscale representation of hydrographic features, which raises important questions. What meander geometries are important to preserve in multi-scale databases? How are geometries measured? How are they preserved? Is the choice between preservation of geometry or use of classification attributes? Questions related to multiscale measurement and representation of hydrographic features continue to emerge with increased spatial and temporal data collection. A key metric for understanding meander bend geometry is sinuosity. The most common measure of sinuosity is the length of a feature divided by the distance between stream head and mouth. The measure relays deviation from a straight line but nothing about meander wavelength. There is not a clear consensus on methods for measuring meander geometry, much less efficiently, at scales made viable with increased data resolution. Here we propose a method for automated characterization of meander wavelength or bend radius. The method, termed Scale-Specific Sinuosity ( S 3 ), is a derivation from the Richardson plot. The Richardson (1961) plot is a classic means of calculating fractal dimension of natural line features and describes feature length (ℓ) given increasing vertex spacing, or step size (S), plotted on a log-log plot. The S 3 metric is defined as negative one times the slope of a Richardson plot for a given stride length. This paper demonstrates utility of S 3 for estimating changes in sinuosity with scale change.

Conference Paper↗

Scale-specific metrics for adaptive generalization and geomorphic classification of stream features

The Richardson plot has been used to illustrate fractal dimension of naturally occurring landscape features that are sensitive to changes in scale or resolution, such as coastlines and river channels. The Richardson method estimates the length of a path by traversing (i.e., “walking”) the path with a specific stride length. Fractal dimension is determined as the slope of the Richardson plot, which shows path length over a range of stride lengths graphed on log-log axes. This paper describes a variant of the Richardson plot referred to as the Scale-Specific Sinuosity (S 3 ) plot. S 3 is defined as negative one times the slope of the Richardson plot for a given stride length. A plot of S 3 against stride length offers a frequency distribution whose area under the curve reflects total sinuosity, and whose points mark the amount of sinuosity contributed to the total sinuosity at each stride length. Mathematical relations of S 3 with fractal dimension and sinuosity for linear features are described. The S 3 metric is demonstrated and discussed for several linear stream features distributed over the conterminous United States. The S 3 metric can help guide the preservation of stream feature sinuosity during cartographic generalization and may assist automated geomorphic classification of river systems.

Conference Paper↗

Simplification of polylines by segment collapse: Minimizing areal displacement while preserving area

This paper reports on a new Area Preserving Segment Collapse (APSC) algorithm for simplifying polygonal boundaries while preserving polygonal area at simplified target scales and minimizing areal displacement. A general segment collapse algorithm is defined by iteratively collapsing segments to Steiner points in priority order, guided by placement and displacement functions. The algorithm is specified by defining functions that minimize areal displacement under the constraint that the areas of adjoining polygons are preserved exactly. Self-intersections can be avoided by testing for intersections with two new line segments associated with each segment collapse operation. The paper demonstrates simplification results for a sample of 10 lakes formed from alpine, Karst, glacial and arid desert processes as well as artificial dams. APSC results are compared with three other simplification routines and evaluated for area preservation, linear and areal displacement, complexity and introduction of boundary self-intersections. Results confirm that the APSC algorithm preserves area exactly and indicate that it outperforms the other tested algorithms for minimizing areal displacement while producing reasonably low measures of linear displacement. Self-intersections can occur more commonly with APSC than other algorithms but are avoided with the proposed topology check. The APSC algorithm additionally preserves polygon complexity better than other tested algorithms.

International Journal of Cartography↗

Generalization in practice within national mapping agencies

National Mapping Agencies (NMAs) are still among the main end users of research into automated generalisation, which is transferred into their produc- tion lines via various means. This chapter includes contributions from seven NMAs, illustrating how automated generalisation is used in practice within their partly or fully automated databases and maps production lines, what results are currently being obtained and what further developments are on-going or planned. A contribution by the European Joint Research Center reports on the use of multiple representation and generalisation in the context of the implementation of the European INSPIRE directive. The chapter finishes with a synthesis of recent achievements, as well as future challenges that NMAs have begun to tackle.

Book chapter↗