NoBa Land Cover Retriever 2.0 – A tool for retrieving land cover data needed in statistical assessment and planning of quarantine pest surveys

This release provides updated source code of 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.

The current update addressed the outdated 'rgdal' library (Bivand et al., 2022), which has been removed from the CRAN repository due to lack of maintenance. Since the 'raster library (Hijmans, 2022) relies on 'rgdal', all spatial operations in the NoBa LCR application were reconstructured to use 'terra' (Hijmans, 2025) and 'sf' (Pebesma, 2018) libraries. This transition enables smoother future development of the application.

Additionally, data on the Centres for Economic Development, Transport and the Environment in Finland were updated (Statistics Finland, 2025a). The Economic Development Centres were also added as new administrative regions, allowing calculation of entry sites and target populations for these areas. The borders of the Economic Development Centres were defined using the data on Regions in Finland (Statistics Finland, 2025b)

New functionality was also introduced to the interactive maps using the 'leaflet.extras' (Gatscha et al., 2024 ) and 'leaflet.extras2' (Gatscha, 2025) libraries.

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', 'leaflet.extras', 'leaflet.extas2', ‘terra’, ‘sf’, ‘shiny’, ‘shinybusy’, ‘shinyhelper’, ‘shinythemes’, ‘shinyWidgets’, 'htmlwidgets', 'tidyverse' and 'zip'.
5. Run the command runApp() in R.

NoBa LCR was originally 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 2.0 is written with R version 4.2.2 (R Core Team 2024) and its package ‘shiny’ (Chang et al. 2022). R packages ‘terra’ (Hijmans, 2025) and ‘sf’ (Pebesma, 2018) are used for retrieving and analyzing the GIS data. R package ‘leaflet’(Cheng et al., 2022) and its extensions 'leaflet.extras' (Gatscha et al., 2024) and 'leaflet.extras2' (Gatscha, 2025) are 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), 'htmlwidgets' (Vaiduananthan et al., 2023), ‘tidyverse’ (Wickham et al., 2019) and ‘zip’ (Csárdi et al., 2021).

Please note that the data required for the NoBa LCR application on  administrative regions (GADM, 2020; Estonian Land Board, 2021; Statistics Finland, 2025a; 2025b) is not included in this release. You will need to download it separately from the GADM, Estonian Land Board, and Statistics Finland databases.

References

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

Bivand R, Keitt T, Rowlingson B (2022). rgdal: Bindings for the 'Geospatial' DatabAbstraction 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, 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, 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, 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. URL: www.gadm.org (Accessed 14th September 2022)

Gatscha S, Karambelkar B, Schloerke B (2024). leaflet.extras: Extra Functionality for 'leaflet' Package. R package version 2.0.1. https://CRAN.R-project.org/package=leaflet.extras

Gatscha S (2025). leaflet.extras2: Extra Functionality for 'leaflet' Package_. R package version 1.3.1. https://CRAN.R-project.org/package=leaflet.extras2

EEA (2022). Copernicus Land Monitoring Service 2022, European Environment Agency (EEA)

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

Hijmans R (2022). raster: Geographic Data Analysis and Modeling. R package version 3.5–29. https://CRAN.R-project.org/package=raster

Hijmans R (2025). terra: Spatial Data Analysis_. R package version 1.8-50. https://CRAN.R-project.org/package=terra

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, 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 (2024). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/

Statistics Finland (2025a). Centres for Economic Development, Transport and the Environment (ELY) 2025 (1:4 500 000). Statistics Finland. The material was downloaded from Statistics Finland's interface service on 27 August 2025 with the license CC BY 4.0

Statistics Finland (2025b). Regions 2025 (1:4 500 000). Statistics Finland. The material was downloaded from Statistics Finland's interface service on 27 August 2025 with the license CC BY 4.0

Vaidyanathan R, Xie Y, Allaire J, Cheng J, Sievert C, Russell K (2023). htmlwidgets: HTML Widgets for R_. R package version 1.6.4. https://CRAN.R-project.org/package=htmlwidgets

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