(Q51146351)

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Improving pest risk assessment and management through the aid of geospatial information technology standards

scientific article published on 13 September 2013

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Improving pest risk assessment and management through the aid of geospatial information technology standards (English)

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1

Trond Rafoss

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author name string

Jarle Skahjem

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2

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John Atle Johansen

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3

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Ståle Johannessen

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4

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Udaya Sekhar Nagothu

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5

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Inger S. Fløistad

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6

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Arild Sletten

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7

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publication date

13 September 2013

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published in

Neobiota

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volume

18

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page(s)

119-130

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copyright license

Creative Commons Attribution 3.0 Unported

start time

13 September 2013

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copyrighted

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WikiProject Invasion Biology

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cites work

EpiCollect: linking smartphones to web applications for epidemiology, ecology and community data collection

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Crossref

reference URL

https://api.crossref.org/works/10.3897%2FNEOBIOTA.18.4017

retrieved

21 January 2018

Effects of the training dataset characteristics on the performance of nine species distribution models: application to Diabrotica virgifera virgifera

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Crossref

reference URL

https://api.crossref.org/works/10.3897%2FNEOBIOTA.18.4017

retrieved

21 January 2018

Darwin Core: an evolving community-developed biodiversity data standard

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Crossref

reference URL

https://api.crossref.org/works/10.3897%2FNEOBIOTA.18.4017

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21 January 2018

Open geospatial technology standards and their potential in plant pest risk management—GPS-enabled mobile phones utilising open geospatial technology standards Web Feature Service Transactions support the fighting of fire blight in Norway

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Crossref

reference URL

https://api.crossref.org/works/10.3897%2FNEOBIOTA.18.4017

retrieved

21 January 2018

Integrating species distribution models and interacting particle systems to predict the spread of an invasive alien plant

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Crossref

reference URL

https://api.crossref.org/works/10.3897%2FNEOBIOTA.18.4017

retrieved

21 January 2018

Novel strategies for assessing and managing the risks posed by invasive alien species to global crop production and biodiversity

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Crossref

reference URL

https://api.crossref.org/works/10.3897%2FNEOBIOTA.18.4017

retrieved

21 January 2018

Novel methods improve prediction of species’ distributions from occurrence data

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stated in

Crossref

reference URL

https://api.crossref.org/works/10.3897%2FNEOBIOTA.18.4017

retrieved

21 January 2018

Species Distribution Models: Ecological Explanation and Prediction Across Space and Time

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stated in

Crossref

reference URL

https://api.crossref.org/works/10.3897%2FNEOBIOTA.18.4017

retrieved

21 January 2018

Identifiers

DOI

10.3897/NEOBIOTA.18.4017

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ResearchGate publication ID

272923190

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(Q51146351)

Improving pest risk assessment and management through the aid of geospatial information technology standards

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