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Title: Cumulative Spatial Impact Layers: A Novel Multivariate Spatio-Temporal Analytical Summarization Tool

Abstract

Scientific inquiry often requires analysis of multiple spatio-temporal datasets, ranging in type and size, using complex multi-step processes demanding an understanding of GIS theory and software. Cumulative Spatial Impact Layers (CSIL) is a GIS-based tool that summarizes spatio-temporal datasets based on overlapping features and attributes. Leveraging a recursive quadtree method, and applying multiple additive frameworks, the CSIL tool allows users to analyze raster and vector datasets by calculating data, record, or attribute density. Providing an efficient and robust method for summarizing disparate, multi-format, multi-source geospatial data, CSIL addresses the need for a new integration approach and resulting geospatial product. The built-in flexibility of the CSIL tool allows users to answer a range of spatially-driven questions. Example applications are provided in this paper to illustrate the versatility and variety of uses for this CSIL tool and method. Use cases include addressing regulatory decision-making needs, economic modeling, and resource management. Performance reviews for each use case are also presented, demonstrating how CSILs provides a more efficient and robust approach to assess a range of multivariate spatial data for a variety of uses.

Authors:
ORCiD logo [1]; ORCiD logo [2];  [1]; ORCiD logo [3];  [1]; ORCiD logo [3]
  1. National Energy Technology Lab. (NETL), Albany, OR (United States); Leidos Research Support Team, Albany, OR (United States)
  2. National Energy Technology Lab. (NETL), Albany, OR (United States); Arizona State Univ., Phoenix, AZ (United States)
  3. National Energy Technology Lab. (NETL), Albany, OR (United States)
Publication Date:
Research Org.:
National Energy Technology Lab. (NETL), Albany, OR (United States)
Sponsoring Org.:
USDOE Office of Fossil Energy (FE)
OSTI Identifier:
1524454
Grant/Contract Number:  
FE0004000
Resource Type:
Accepted Manuscript
Journal Name:
Transactions in GIS
Additional Journal Information:
Journal Name: Transactions in GIS
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES; Spatio-temporal Analysis; Multivariate Visualization; Spatial Overlay

Citation Formats

Romeo, Lucy, Nelson, Jake, Wingo, Patrick, Bauer, Jennifer, Justman, Devin, and Rose, Kelly. Cumulative Spatial Impact Layers: A Novel Multivariate Spatio-Temporal Analytical Summarization Tool. United States: N. p., 2019. Web. doi:10.18141/1491843.
Romeo, Lucy, Nelson, Jake, Wingo, Patrick, Bauer, Jennifer, Justman, Devin, & Rose, Kelly. Cumulative Spatial Impact Layers: A Novel Multivariate Spatio-Temporal Analytical Summarization Tool. United States. doi:10.18141/1491843.
Romeo, Lucy, Nelson, Jake, Wingo, Patrick, Bauer, Jennifer, Justman, Devin, and Rose, Kelly. Tue . "Cumulative Spatial Impact Layers: A Novel Multivariate Spatio-Temporal Analytical Summarization Tool". United States. doi:10.18141/1491843.
@article{osti_1524454,
title = {Cumulative Spatial Impact Layers: A Novel Multivariate Spatio-Temporal Analytical Summarization Tool},
author = {Romeo, Lucy and Nelson, Jake and Wingo, Patrick and Bauer, Jennifer and Justman, Devin and Rose, Kelly},
abstractNote = {Scientific inquiry often requires analysis of multiple spatio-temporal datasets, ranging in type and size, using complex multi-step processes demanding an understanding of GIS theory and software. Cumulative Spatial Impact Layers (CSIL) is a GIS-based tool that summarizes spatio-temporal datasets based on overlapping features and attributes. Leveraging a recursive quadtree method, and applying multiple additive frameworks, the CSIL tool allows users to analyze raster and vector datasets by calculating data, record, or attribute density. Providing an efficient and robust method for summarizing disparate, multi-format, multi-source geospatial data, CSIL addresses the need for a new integration approach and resulting geospatial product. The built-in flexibility of the CSIL tool allows users to answer a range of spatially-driven questions. Example applications are provided in this paper to illustrate the versatility and variety of uses for this CSIL tool and method. Use cases include addressing regulatory decision-making needs, economic modeling, and resource management. Performance reviews for each use case are also presented, demonstrating how CSILs provides a more efficient and robust approach to assess a range of multivariate spatial data for a variety of uses.},
doi = {10.18141/1491843},
journal = {Transactions in GIS},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {1}
}

Journal Article:
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This content will become publicly available on January 1, 2020
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