Recent Posts

Considerations for the pattern-based spatial analysis

TLTR: This is a last blog post in a series about motif - an R package aimed for pattern-based spatial analysis. It sums up previous posts, but also underlines potential considerations when working with spatial patterns. Finally, it lists underexplored topics and future ideas related to pattern-based …

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Clustering similar spatial patterns

TLTR: Clustering similar spatial patterns requires one or more raster datasets for the same area. Input data is divided into many sub-areas, and spatial signatures are derived for each sub-area. Next, distances between signatures for each sub-area are calculated and stored in a distance matrix. The …

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Quantifing changes of spatial patterns

TLTR: Quantifing changes of spatial patterns requires two datasets for the same variable in the same area. Both datasets are divided into many sub-areas, and spatial signatures are derived for each sub-area for each dataset. Next, distances for each pair of areas are calculated. Sub-areas with the …

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Recent Publications

  • Dyba K, Nowosad J (2021) rgugik: Search and Retrieve Spatial Data from the Polish Head Office of Geodesy and Cartography in R. Journal of Open Source Software, 6(59), 2948, DOI: 10.21105/joss.02948
    Abstract Online DOI
  • Nowosad J, Stepinski TF (2021) Pattern-based identification and mapping of landscape types using multi-thematic data, International Journal of Geographical Information Science, DOI: 10.1080/13658816.2021.1893324
    Abstract Online Preprint DOI
  • Nowosad, J., 2021, Motif: an open-source R tool for pattern-based spatial analysis. Landscape Ecol 36(1), 29-43, https://doi.org/10.1007/s10980-020-01135-0
    Abstract Online Preprint DOI
  • Nowosad J., Gao P. (2020) belg: A Tool for Calculating Boltzmann Entropy of Landscape Gradients. Entropy. 22(9), 937, DOI:10.3390/e22090937
    Abstract Online DOI
  • Nowosad, J., (2020). Elementarz programisty: wstęp do programowania używając R. Wydanie pierwsze. Poznań: Space A. Online: https://nowosad.github.io/elp/ ISBN: 978-83-953296-1-9
    Abstract PDF Online