NoBa Land Cover Retriever - A tool for retrieving land cover data needed in statistical assessment and planning of quarantine pest surveys

This release provides the source code for the web application ‘NoBa Land Cover Retriever’  (NoBa LCR) that is available at https://noba-lcr.2.rahtiapp.fi/.

NoBa LCR is a web application for retrieving CORINE Land Cover (CLC) data (EEA 2022) needed in the statistical assessment and planning of quarantine pest surveys. The countries included in this version of the application are Estonia, Finland, Lithuania, Norway and Sweden.

NoBa LCR was developed in the Risk Assessment Unit of the Finnish Food Authority in 2022 as part of a project 'Assessing the confidence in pest freedom gained in the past pine wood nematode surveys'. The project was a co-operation between the Finnish Food Authority, the Estonian Agriculture and Food Board (EAFB), the State Plant Service under the Ministry of Agriculture of the Republic of Lithuania (SPSMoA), the Norwegian Scientific Committee for Food and Environment (VKM), and the Swedish University of Agricultural Sciences (SLU). The project was co-funded by the European Food Safety Authority (EFSA) Partnering grant (GP/EFSA/ENCO/2020/03), yet EFSA is not responsible for any use that may be made of the information contained in the app.

NoBa LCR is written with R version 4.2.1 (R Core Team 2022) and its package ‘shiny’ (Chang et al. 2022). R packages ‘raster’ (Hijmans 2022), ‘sf’ (Pebesma 2018), ‘sp’ (Pebesma and Bivand 2005, Bivand et al. 2013) and ‘rgdal’ (Bivand et al. 2022) are used for retrieving and analysing the GIS data. R package ‘leaflet’ (Cheng et al. 2022) is used to create an interactive map for visual exploration of the results.

The following R packages are used to finalize the user experience of the application: ‘shinythemes’ (Chang 2021), ‘shinyhelper’ (Mason-Thom 2019), ‘shinybusy’ (Meyer and Perrier 2022), ‘shinyWidgets’ (Perrier et al. 2022), ‘tidyverse’ (Wickham et al. 2019) and ‘zip’ (Csárdi et al. 2021).

Please note that the data required for the NoB LCR application on  administrative regions (GADM 2020, Estonian Land Board 2021, Statistics Finland 2022) is not included in this release. You will need to download it separately from the GADM, Estonian Land Board, and Statistics Finland databases.

To run the source code locally in your computer you need to:

1. Install R from https://www.r-project.org/
2. Save the files ‘app.R’ and 'functions.R' in your working directory.
3. Create a folder into your working directory called ‘data’, and unzip the file “data.zip” there.
4. Install R packages 'leaflet', ‘raster’, ‘rgdal’, ‘sf’, ‘shiny’, ‘shinybusy’, ‘shinyhelper’, ‘shinythemes’, ‘shinywidgets’, 'sp', 'tidyverse' and 'zip'.
5. Run the command runApp() in R.

Rerefences

Bivand RS, Pebesma E and Gomez-Rubio V, 2013. Applied spatial data analysis with R, Second edition. Springer, NY. https://asdar-book.org/

Bivand R, Keitt T and Rowlingson B, 2022. rgdal: Bindings for the 'geospatial' data abstraction library. R package version 1.5–32, https://CRAN.R-project.org/package=rgdal

Chang W, 2021. shinythemes: Themes for shiny. R package version 1.2.0, https://CRAN.R-project.org/package=shinythemes

Chang W, Cheng J, Allaire J, Sievert C, Schloerke B, Xie Y, Allen J, McPherson J, Dipert A and Borges B, 2022. shiny: Web application framework for R. R package version 1.7.2. https://CRAN.R-project.org/package=shiny

Cheng J, Karambelkar B and Xie Y, 2022. leaflet: Create interactive web maps with the JavaScript 'leaflet' library. R package version 2.1.1. https://CRAN.R-project.org/package=leaflet

Csárdi G, Podgórski K and Geldreich R, 2021. zip: Cross-platform 'zip' compression. R package version 2.2.0. https://CRAN.R-project.org/package=zip

GADM, 2020. GADM database of global administrative areas, version 4.1. www.gadm.org (Accessed 14 September 2022)

EEA (European Environment Agency), 2022. Copernicus, Land Monitoring Service, CLC 2018. In: Copernicus. https://land.copernicus.eu/pan-european/corine-land-cover/clc2018

Estonian Land Board, 2021. Administrative and settlement units, Estonian Land Board. https://geoportaal.maaamet.ee/eng/Spatial-Data/Administrative-and-Settlement-Division-p312.html (Accessed 1 December 2021)

Hijmans R, 2022. raster: Geographic data analysis and modeling. R package version 3.5–29. https://CRAN.R-project.org/package=raster

Mason-Thom C, 2019. shinyhelper: Easily add markdown help files to 'shiny' app elements. R package version 0.3.2. https://CRAN.R-project.org/package=shinyhelper

Meyer F and Perrier V, 2022. shinybusy: Busy indicators and notifications for 'shiny' spplications. R package version 0.3.1. https://CRAN.R-project.org/package=shinybusy

Pebesma E, 2018. Simple features for R: standardized support for spatial vector data. The R Journal 10 (1), 439-446. https://doi.org/10.32614/RJ-2018-009

Pebesma EJ and Bivand RS, 2005. Classes and methods for spatial data in R. R News 5 (2). https://cran.r-project.org/doc/Rnews/

Perrier V, Meyer F and Granjon D, 2022. shinyWidgets: Custom inputs widgets for shiny. R package version 0.7.3. https://CRAN.R-project.org/package=shinyWidgets

R Core Team, 2022. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/

Statistics Finland, 2022. Centres for economic development, transport and the environment (ELY), Statistics Finland. The material was downloaded from Statistics Finland's interface service on 13 September 2022 with the license CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/deed.en)

Wickham H, Averick M, Bryan J, Chang W, McGowan LD, François R, Grolemund G, Hayes A, Henry L, Hester J, Kuhn M, Pedersen TL, Miller E, Bache SM, Müller K, Ooms J, Robinson D, Seidel DP, Spinu V, Takahashi K, Vaughan D, Wilke C, Woo K and Yutani H, 2019. “Welcome to the tidyverse.” Journal of Open Source Software, 4(43), 1686. https://doi.org/10.21105/joss.01686