Krzysztof Dyba (kadyb)

kadyb

Geek Repo

Company:Adam Mickiewicz University

Location:Poland

Twitter:@krzysztof_dyba

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Krzysztof Dyba's repositories

geotips

Collection of tips for faster spatial data processing in R

rgugik

Download datasets from Polish Head Office of Geodesy and Cartography

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raster-benchmark

Raster processing benchmarks for Python and R packages

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vector-benchmark

Vector processing benchmarks for Python and R packages

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OGH2023

OpenGeoHub 2023 Workshop: "Unsupervised classification (clustering) of satellite images"

stars-parallel

Tutorial on parallel processing of raster data in the {stars} package

OGH2023_hack

Hackathon "Automatic land cover mapping" at OpenGeoHub Summer School 2023

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geomorph_classification

Automatic gemorphological classification based on Digital Geomorphological Maps of Poland

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gis2024

Kurs "Zaawansowane analizy przestrzenne" 2024 UMCS

image-segmentation

Comparison of kmeans and supercells for image semgentiation in R

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LST-PL

Interactive map of land surface types of Poland

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sf_load_save

Tutorial on how to load and save spatial vector data in R

actions

GitHub Actions for the R community

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geos-1

Open Source Geometry Engine ('GEOS') R API

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gstat

Spatial and spatio-temporal geostatistical modelling, prediction and simulation

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hexbin

Hexagonal binning routines and plotting methods

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r-spatial.org

r-spatial.org blog sources

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raster

R raster package https://rspatial.github.io/raster/reference/raster-package.html

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rsgeo

R bindings to the geo Rust crate

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sf

Simple Features for R

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sp

Classes and methods for spatial data

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Spatial

CRAN Task View: Analysis of Spatial Data

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SpatioTemporal

CRAN Task View: Handling and Analyzing Spatio-Temporal Data

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stars

Spatiotemporal Arrays, Raster and Vector Data Cubes

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terra

R package for spatial data handling https://rspatial.github.io/terra/reference/terra-package.html

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xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

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yyjsonr

Fast JSON package for R

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