Generalizing linear stream features to preserve sinuosity for analysis and display: A pilot study in multi-scale data science

Larry V. Stanislawski; Barry J. Kronenfeld; Barbara P. Buttenfield; Tyler Brockmeyer

Generalizing linear stream features to preserve sinuosity for analysis and display: A pilot study in multi-scale data science

Larry V. Stanislawski, Barry J. Kronenfeld, Barbara P. Buttenfield, Tyler Brockmeyer

Eastern Illinois University

Research output: Contribution to journal › Article › peer-review

Original language	American English
Journal	22nd International Research Symposium on Computer-based Cartography and GIScience
State	Published - Jan 1 2018

Disciplines

Mathematics
Artificial Intelligence and Robotics

Cite this

Generalizing linear stream features to preserve sinuosity for analysis and display: A pilot study in multi-scale data science. / Stanislawski, Larry V.; Kronenfeld, Barry J.; Buttenfield, Barbara P. et al.
In: 22nd International Research Symposium on Computer-based Cartography and GIScience, 01.01.2018.

Research output: Contribution to journal › Article › peer-review

@article{83019c6d9b8b4614bc8a9faff37bd4c8,

title = "Generalizing linear stream features to preserve sinuosity for analysis and display: A pilot study in multi-scale data science",

author = "Stanislawski, {Larry V.} and Kronenfeld, {Barry J.} and Buttenfield, {Barbara P.} and Tyler Brockmeyer",

note = "Cartographic generalization can impact geometric properties of geospatial data and subsequent analyses. This study evaluates simplification methods with the goal of preserving geometric details, such as sinuosity.",

year = "2018",

month = jan,

day = "1",

language = "American English",

journal = "22nd International Research Symposium on Computer-based Cartography and GIScience",

}

TY - JOUR

T1 - Generalizing linear stream features to preserve sinuosity for analysis and display: A pilot study in multi-scale data science

AU - Stanislawski, Larry V.

AU - Kronenfeld, Barry J.

AU - Buttenfield, Barbara P.

AU - Brockmeyer, Tyler

N1 - Cartographic generalization can impact geometric properties of geospatial data and subsequent analyses. This study evaluates simplification methods with the goal of preserving geometric details, such as sinuosity.

PY - 2018/1/1

Y1 - 2018/1/1

UR - https://pubs.er.usgs.gov/publication/70199190

M3 - Article

JO - 22nd International Research Symposium on Computer-based Cartography and GIScience

JF - 22nd International Research Symposium on Computer-based Cartography and GIScience

ER -

Generalizing linear stream features to preserve sinuosity for analysis and display: A pilot study in multi-scale data science

Disciplines

Other files and links

Cite this