Bibliografía y otros recursos¶
Arribas-Bel, D. (2019). A course on Geographic Data Science. Journal of Open Source Education, 2(14), 42. https://doi.org/10.21105/jose.00042
Dabbas, E. (2021). Interactive Dashboards and Data Apps with Plotly and Dash. Packt Publishing. https://www.packtpub.com/product/interactive-dashboards-and-data-apps-with-plotly-and-dash/9781800568914
Dorman, M. (2021). Spatial Data Programming with Python. https://geobgu.xyz/py/
Gandhi, U. (s. f.). Automating Map Creation with Print Layout Atlas (QGIS3)—QGIS Tutorials and Tips. Recuperado 11 de enero de 2022, de https://www.qgistutorials.com/en/docs/3/automating_map_creation.html
Gandhi, U. (s. f.). Making a Map (QGIS3)—QGIS Tutorials and Tips. Recuperado 11 de enero de 2022, de https://www.qgistutorials.com/en/docs/3/making_a_map.html
Gandhi, U. (2020a, febrero 1). Mastering GDAL Tools. Spatial Thoughts. https://spatialthoughts.com/courses/mastering-gdal-tools/
Gandhi, U. (2020b, febrero 1). Spatial Data Visualization and Analytics. Spatial Thoughts. https://spatialthoughts.com/courses/spatial-data-viz/
Gandhi, U. (2020c, mayo 16). Python Foundation for Spatial Analysis. Spatial Thoughts. https://spatialthoughts.com/courses/python-foundation-for-spatial-analysis/
Gandhi, U. (2021). QGIS Tutorials and Tips. https://www.qgistutorials.com/ GDAL/OGR contributors. (2021). GDAL/OGR Geospatial Data Abstraction software Library. Open Source Geospatial Foundation. https://gdal.org/
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Gillies, S. (s. f.-a). Fiona: Fiona reads and writes spatial data files (1.8.20) [Python; OS Independent]. Recuperado 1 de enero de 2022, de http://github.com/Toblerity/Fiona
Gillies, S. (s. f.-b). rasterio: Fast and direct raster I/O for use with Numpy and SciPy (1.2.10) [C, Cython, Python]. Recuperado 1 de enero de 2022, de https://github.com/mapbox/rasterio
Gillies, S. (s. f.-c). Shapely: Geometric objects, predicates, and operations (1.8.0) [Python; OS Independent]. Recuperado 1 de enero de 2022, de https://github.com/Toblerity/Shapely
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Hwang, J. P. (2021, septiembre 3). Building a Big Data Geographical Dashboard with Open-Source Tools. Plotly. https://medium.com/plotly/building-a-big-data-geographical-dashboard-with-open-source-tools-c5108d7d5683
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Longley, P. A., Goodchild, M. F., Maguire, D. J., & Rhind, D. W. (2005). Geographic Information Systems and Science (2nd edition). Wiley.
Lovelace, R., Nowosad, J., & Münchow, J. (2019). Geocomputation with R. CRC Press, Taylor and Francis Group, CRC Press is an imprint of theTaylor and Francis Group, an informa Buisness, A Chapman & Hall Book. https://geocompr.robinlovelace.net/
Matsuoka, K., Skoglund, A., Roth, G., de Pomereu, J., Griffiths, H., Headland, R., Herried, B., Katsumata, K., Le Brocq, A., Licht, K., Morgan, F., Neff, P. D., Ritz, C., Scheinert, M., Tamura, T., Van de Putte, A., van den Broeke, M., von Deschwanden, A., Deschamps-Berger, C., … Melvær, Y. (2021). Quantarctica, an integrated mapping environment for Antarctica, the Southern Ocean, and sub-Antarctic islands. Environmental Modelling & Software, 140, 105015. https://doi.org/10.1016/j.envsoft.2021.105015
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Olaya, V. (2020). Sistemas de Información Geográfica. https://volaya.github.io/libro-sig/ Oliphant, T. E. (s. f.). numpy: NumPy is the fundamental package for array computing with Python. (1.22.0) [C, Python; MacOS, Microsoft :: Windows, POSIX, Unix]. Recuperado 1 de enero de 2022, de https://www.numpy.org
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Parmer, C. (s. f.). dash: A Python framework for building reactive web-apps. Developed by Plotly. (2.0.0) [Python]. Recuperado 1 de enero de 2022, de https://plotly.com/dash
Pebesma, E., Wagner, W., Verbesselt, J., Goor, E., Briese, C., & Neteler, M. (2016). OpenEO: a GDAL for Earth Observation Analytics. https://r-spatial.org/2016/11/29/openeo.html
Python Software Foundation. (2021). Python Language Reference. https://www.python.org/
Rey, S. J., Arribas-Bel, D., & Wolf, L. J. (2020). Geographic Data Science with Python. https://geographicdata.science/book/
Richards, T. (2021). Getting started with Streamlit for data science: Create and deploy Streamlit web applications from scratch in Python. Packt Publishing. https://www.packtpub.com/product/getting-started-with-streamlit-for-data-science/9781800565500
Robinson, D. (2017, septiembre 6). The Incredible Growth of Python. Stack Overflow Blog. https://stackoverflow.blog/2017/09/06/incredible-growth-python/
Schmitt, M. (2020). Data dashboarding tools | Streamlit v.s. Dash v.s. Shiny vs. Voila vs. Flask vs. Jupyter. https://www.datarevenue.com/en-blog/data-dashboarding-streamlit-vs-dash-vs-shiny-vs-voila
Severance, C. (s. f.). PY4E - Python for Everybody. Recuperado 1 de enero de 2022, de https://www.py4e.com/
Singleton, A., & Arribas‐Bel, D. (2019). Geographic Data Science. Geographical Analysis, gean.12194. https://doi.org/10.1111/gean.12194
Story, R. (s. f.). folium: Make beautiful maps with Leaflet.js & Python [Python]. Recuperado 1 de enero de 2022, de https://github.com/python-visualization/folium
Streamlit Inc. (s. f.). streamlit: The fastest way to build data apps in Python (1.3.1) [Computer software]. Recuperado 1 de enero de 2022, de https://streamlit.io
Tenkanen, H., Heikinheimo, V., & Aagesen, H. W. (2021). Automating GIS-processes. https://autogis-site.readthedocs.io/en/latest/
The Pandas Development Team. (s. f.). pandas: Powerful data structures for data analysis, time series, and statistics (1.3.5) [Cython, Python; OS Independent]. Recuperado 1 de enero de 2022, de https://pandas.pydata.org
Whipp, D., Tenkanen, H., Heikinheimo, V., & Aagesen, H. W. (2021). Geo-Python. https://geo-python-site.readthedocs.io/en/latest/
Wu, Q. (s. f.). Geographic Software Design. Recuperado 2 de enero de 2022, de https://www.youtube.com/playlist?list=PLAxJ4-o7ZoPeUqGpMhvJoVk5G-TrvMAd-
Wu, Q. (2021, octubre 25). A streamlit app for creating timelapse of annual Landsat imagery (1984–2021). Medium. https://giswqs.medium.com/a-streamlit-app-for-creating-timelapse-of-annual-landsat-imagery-1984-2021-3db407a8ac32
Zambelli, P., Gebbert, S., & Ciolli, M. (2013). Pygrass: An Object Oriented Python Application Programming Interface (API) for Geographic Resources Analysis Support System (GRASS) Geographic Information System (GIS). ISPRS International Journal of Geo-Information, 2(1), 201-219. https://doi.org/10.3390/ijgi2010201