Python za geoinformatiko

Osnove Pythona, analiza in vizualizacija podatkov, obdelava prostorskih podatkov in spletno kartiranje

Od prvih vrstic kode do prostorskih analiz

Python za geoinformatiko

Praktičen uvod v programiranje, analizo in vizualizacijo podatkov ter obdelavo prostorskih podatkov s Pythonom.

Začni z uvodom Oglej si vsebino

Vsebina knjige

01

Uvod in delovno okolje

Pripravi Python, JupyterLab in VS Code ter spoznaj zapisovanje učnih gradiv z Markdownom.

Odpri prvi del →

02

Python in analiza podatkov

Osvoji jezik Python ter delo z NumPy, SciPy, Matplotlibom in pandasom.

Odpri drugi del →

03

Geoprostorski podatki

Obdeluj vektorske in rastrske podatke, modele višin ter satelitske posnetke.

Odpri tretji del →

04

Primeri in dodatki

Znanje poveži v uporabnih primerih, projektnih nalogah ter delu z Gitom in GitHubom.

Odpri četrti del →

O knjigi

Knjiga združuje osnove programiranja v Pythonu, analizo podatkov in obdelavo geoprostorskih podatkov v enotno učno celoto. Namenjena je geoinformatikom, geodetom, geografom, gozdarjem, kmetijcem in drugim uporabnikom, ki želijo Python uporabljati pri delu s prostorskimi podatki.

Razlagalna poglavja dopolnjujejo praktične vaje v Jupyterjevih zvezkih. Spletna različica je namenjena sprotnemu učenju in hitri navigaciji, PDF pa linearnemu branju in tisku.

Anaconda. b. d. „Advance AI with Open Source“. Pridobljeno 30. junij 2026. https://www.anaconda.com/.

Bivand, Roger. 2021. „Progress in the R Ecosystem for Representing and Handling Spatial Data“. Journal of Geographical Systems 23 (4): 515–46. https://doi.org/10.1007/s10109-020-00336-0.

Bivand, Roger, Edzer Pebesma, in Virgilio Gómez-Rubio. 2013. Applied Spatial Data Analysis with R. Springer.

Burrough, Peter A., Rachael McDonnell, in Christopher D. Lloyd. 2015. Principles of Geographical Information Systems. 3. izd. Oxford University Press.

conda-forge. (2019) 2026. Conda-Forge/Miniforge. november 14, Released junij 30. https://github.com/conda-forge/miniforge.

Dorman, Michael, Anita Graser, Jakub Nowosad, in Robin Lovelace. 2025. Geocomputation with Python. CRC Press. https://py.geocompx.org/.

GeoPandas contributors. 2023. GeoPandas: V0.14.0. Različica 0.14.0. Zenodo, released. https://doi.org/10.5281/zenodo.8348034.

Gillies, Sean idr. 2007. Shapely: Manipulation and Analysis of Geometric Objects. Released. https://github.com/shapely/shapely.

GitHub, Inc. 2008–. GitHub. Released. https://github.com/.

Harris, Charles R., K. Jarrod Millman, Stéfan J. van der Walt, idr. 2020. „Array Programming with NumPy“. Nature 585 (7825): 357–62. https://doi.org/10.1038/s41586-020-2649-2.

Jenny, Bernhard, Bojan Šavrič, Nicholas D. Arnold, Brooke E. Marston, in Charles A. Preppernau. 2017. „A Guide to Selecting Map Projections for World and Hemisphere Maps“. V Choosing a Map Projection, uredil Miljenko Lapaine in E. Lynn Usery. Springer.

Jordahl, Kelsey, Joris Van den Bossche, Martin Fleischmann, idr. b. d. Geopandas/Geopandas. Zenodo. https://doi.org/10.5281/zenodo.3946761.

Lovelace, Robin, Jakub Nowosad, in Jannes Muenchow. 2025. Geocomputation with R. 2. izd. CRC Press. https://r.geocompx.org/.

Met Office. 2015. Cartopy: A Cartographic Python Library with a Matplotlib Interface. Met Office, released. https://scitools.org.uk/cartopy/.

Pebesma, Edzer, in Roger Bivand. 2023. Spatial Data Science: With Applications in R. CRC Press. https://r-spatial.org/book/.

Plotly Technologies Inc. 2015–. Plotly Python Open Source Graphing Library. Released. https://plotly.com/python/.

Pronk, Maarten, Rafael Schouten, Anshul Singhvi, Felix Cremer, in Jakub Nowosad. 2024. Geocomputation with Julia. CRC Press. https://julia.geocompx.org/.

Python.org. 2026. „Welcome to Python.Org“. junij 29. https://www.python.org/.

Šavrič, Bojan, Bernhard Jenny, in Helen Jenny. 2016. „Projection Wizard – an Online Map Projection Selection Tool“. The Cartographic Journal 53 (2): 177–85. https://doi.org/10.1080/00087041.2015.1131938.

The pandas development team. b. d. Pandas-Dev/Pandas: Pandas. Zenodo. https://doi.org/10.5281/zenodo.3509134.

Tomlin, C. Dana. 1990. Geographic Information Systems and Cartographic Modeling. Prentice Hall.

Tomlin, C. Dana. 1994. „Map Algebra: One Perspective“. Landscape and Urban Planning 30 (1–2): 3–12. https://doi.org/10.1016/0169-2046(94)90063-9.

Torvalds, Linus, Junio C. Hamano, idr. 2005–. Git. Released. https://git-scm.com/.

Virtanen, Pauli, Ralf Gommers, Travis E. Oliphant, idr. 2020. „SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python“. Nature Methods 17 (3): 261–72. https://doi.org/10.1038/s41592-019-0686-2.

Waskom, Michael L. 2021. „Seaborn: Statistical Data Visualization“. Journal of Open Source Software 6 (60): 3021. https://doi.org/10.21105/joss.03021.