Jakub Nowosad (Nowosad)

Nowosad

Geek Repo

Location:Poznań, Poland

Home Page:https://jakubnowosad.com

Twitter:@jakub_nowosad

Github PK Tool:Github PK Tool


Organizations
eRum2016
geocompr
geocompx
r-spatialecology
r-tmap

Jakub Nowosad's repositories

OGH_summer_school_2022

Links and slides from the OpenGeoHub summer school 2022

sabre

sabre: Spatial Association Between REgionalizations

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ogh2022

Presentation "Geocomputation with R’s guide to reproducible spatial data analysis" - OpenGeoHub summer school 2022

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spain-map-layout

Alternative layout for maps of Spain - code and data

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geostatbook

Pakiet zawierający dane do skryptu "Geostatystyka w R"

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belg-examples

Code examples from Nowosad, J.; Gao, P. belg: A Tool for Calculating Boltzmann Entropy of Landscape Gradients. Entropy 2020, 22, 937. https://doi.org/10.3390/e22090937

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Rsagacmd

A package for linking R with the open-source SAGA-GIS

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cc-licenses

Creative Commons Licenses for Github

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crsuggest

Get appropriate CRS suggestions for your spatial data in R

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geocompr

Open source book: Geocomputation with R

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GLCMTextures

This R package calculates the most common gray-level co-occurrence matrix (GLCM) texture metrics used for spatial analysis (Hall-Beyer 2017). It is meant to provide a clearly documented implementation of GLCM texture metrics that gives the user control over key parameters to make it clear to the user exactly what they are calculating. It interfaces with C++ via the Rcpp and RcppArmadillo packages for increased speed.

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sfdep

A tidy interface for spatial dependence

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stars

Spatiotemporal Arrays, Raster and Vector Data Cubes

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thundeR

thundeR - Rapid computation and visualisation of convective parameters from rawinsonde and NWP data

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Virtual_species_SDM

How to create Virtual Species (code related to: Rocchini et al. (2022). A quixotic view of spatial bias in modelling the distribution of species and their diversity.

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