The World Spatiotemporal Analytics and Mapping Project (WSTAMP): Further Progress in Discovering, Exploring, and Mapping Spatiotemporal Patterns Across the World’s Largest Open Source Data Sets

J. Piburn, R. Stewart, A. Myers, A. Sorokine, E. Axley, D. Anderson, J. Burdette, C. Biddle, A. Hohl, R. Eberle, J. Kaufman, A. Morton

Open source

DOI: 10.5194/isprs-annals-iv-4-w2-199-2017
Published: 10
Container: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publisher: Not recorded
Open access: yes

Credibility signals

uncertain Score 53/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
supportingDirectory of Open Access Journals: A matching record was returned by DOAJ. Source: DOAJ; license: CC0
not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer

Cite this work

BibTeX

@article{allodium:10.5194/isprs-annals-iv-4-w2-199-2017,
  title = {The World Spatiotemporal Analytics and Mapping Project (WSTAMP): Further Progress in Discovering, Exploring, and Mapping Spatiotemporal Patterns Across the World’s Largest Open Source Data Sets},
  author = {J. Piburn and R. Stewart and A. Myers and A. Sorokine and E. Axley and D. Anderson and J. Burdette and C. Biddle and A. Hohl and R. Eberle and J. Kaufman and A. Morton},
  year = {2017},
  journal = {ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences},
  doi = {10.5194/isprs-annals-iv-4-w2-199-2017},
  url = {https://doi.org/10.5194/isprs-annals-iv-4-w2-199-2017}
}

RIS

TY  - JOUR
TI  - The World Spatiotemporal Analytics and Mapping Project (WSTAMP): Further Progress in Discovering, Exploring, and Mapping Spatiotemporal Patterns Across the World’s Largest Open Source Data Sets
AU  - J. Piburn
AU  - R. Stewart
AU  - A. Myers
AU  - A. Sorokine
AU  - E. Axley
AU  - D. Anderson
AU  - J. Burdette
AU  - C. Biddle
AU  - A. Hohl
AU  - R. Eberle
AU  - J. Kaufman
AU  - A. Morton
PY  - 2017
JO  - ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
DO  - 10.5194/isprs-annals-iv-4-w2-199-2017
UR  - https://doi.org/10.5194/isprs-annals-iv-4-w2-199-2017
ER  -

APA

Piburn, J., Stewart, R., Myers, A., Sorokine, A., Axley, E., Anderson, D., Burdette, J., Biddle, C., Hohl, A., Eberle, R., Kaufman, J., & Morton, A. (2017). The World Spatiotemporal Analytics and Mapping Project (WSTAMP): Further Progress in Discovering, Exploring, and Mapping Spatiotemporal Patterns Across the World’s Largest Open Source Data Sets. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. https://doi.org/10.5194/isprs-annals-iv-4-w2-199-2017

Source records

doaj · retrieved 2026-09-26T15:59:37.765Z