L
Linda See
Researcher at International Institute for Applied Systems Analysis
Publications - 338
Citations - 13633
Linda See is an academic researcher from International Institute for Applied Systems Analysis. The author has contributed to research in topics: Land cover & Crowdsourcing. The author has an hindex of 55, co-authored 312 publications receiving 10755 citations. Previous affiliations of Linda See include International Institute of Minnesota & University College London.
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Software, Data and Modelling News: HydroTest: Further development of a web resource for the standardised assessment of hydrological models
TL;DR: A number of recent improvements to Hydro Test are reported, including a fresh user interface, additional statistical measures of model performance, a graphing facility, and an option to perform the simultaneous analysis of multiple model outputs.
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Using volunteered geographic information (VGI) in design-based statistical inference for area estimation and accuracy assessment of land cover
TL;DR: Combining VGI from a non-probability sample with data from a probability sample using the certainty stratum approach or the model-assisted approach are viable alternatives that meet the conditions required for design-based inference and use the VGI data to advantage to reduce standard errors.
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A Fuzzy Cellular Automata Urban Growth Model (FCAUGM) for the City of Riyadh, Saudi Arabia. Part 1: Model Structure and Validation
TL;DR: The authors conclude that the model offers significant benefits for simulating urban growth and change, for urban planning and decision-support for policy makers and others, but further research will be necessary on methods of validating and interpreting the detailed results.
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Citizen Science and Open Data: a model for Invasive Alien Species in Europe
Ana Cristina Cardoso,Konstantinos Tsiamis,Eugenio Gervasini,Sven Schade,Fabio Taucer,Tim Adriaens,Kyle Copas,Spyridon Flevaris,Philippe Galiay,Eleanor Jennings,Melanie Josefsson,Bernat C. López,John Magan,Elizabete Marchante,Elena Montani,Helen E. Roy,René von Schomberg,Linda See,Mafalda A. C. Quintas +18 more
TL;DR: The workshop highlighted the need for using an open and accessible platform to upload data originating from CS sources or to mirror validated data into a single, easy-to-use web service, in line with the EU Open Science Strategic Priority.
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A spatial statistical analysis of the occurrence of earthquakes along the Red Sea floor spreading: clusters of seismicity
TL;DR: In this paper, the authors apply spatial pattern analysis techniques to a seismic data catalog of earthquakes beneath the Red Sea to try and detect clusters and explore global and local spatial patterns in the occurrence of earthquakes over the years from 1900 to 2009 using a geographical information system (GIS).