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add citations guidelines and reformat (#382)
* add citations guidelines * edit refs up to and including pathfinding * add rest of xrsptial modules citations * add Citations styles and cite us in readme
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‎Citation-styles.md‎

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## Citations Formats:
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- For scientific literature in the form of books or articles in peer-reviewed journals:
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APA7 guidelines
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- For Websites or resources available by following a link to an html, pdf, or other formatted style output:
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Author, Organization, Title, url, "Accesssed" date accessed [Mon. dd, yyyy]
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- For YouTube:
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Poster username, Channel, date posted [Mon. dd, yyyy] "YouTube", , url, "Accessed" date accessed [Mon. dd, yyyy]
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- For software packages:
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Platform username, package name, version, link
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- For source code:
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- On GitHub:
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username/repo, link, access date [Mon. dd, yyyy]

‎README.md‎

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@@ -215,3 +215,7 @@ With the introduction of projects like Numba, Python gained new ways to provide
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- @SAN154
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- @SapirLastimoza-Dooley
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- @lex-c
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Cite our code:
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`makepath/xarray-spatial, https://github.com/makepath/xarray-spatial, ©2020.`

‎xrspatial/aspect.py‎

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Notes:
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----------
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Algorithm References:
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- http://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-analyst-toolbox/how-aspect-works.htm#ESRI_SECTION1_4198691F8852475A9F4BC71246579FAA # noqa
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- Burrough, P. A., and McDonell, R. A., 1998. Principles of Geographical
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Information Systems (Oxford University Press, New York), pp 406
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- esri, How Aspect Works, http://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-analyst-toolbox/how-aspect-works.htm#ESRI_SECTION1_4198691F8852475A9F4BC71246579FAA, Accessed Apr. 21, 2021. # noqa
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- Burrough, P. A., McDonnell, R., McDonnell, R. A., & Lloyd, C. D. (2015). Principles of geographical information systems. Oxford university press. pp 406. # noqa
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Examples:
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* lat (lat) float64 0.0 1.0 2.0 3.0 4.0
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Terrain Example:
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- https://makepath.github.io/xarray-spatial/assets/examples/user-guide.html
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- makepath, User Guide, https://makepath.github.io/xarray-spatial/assets/examples/user-guide.html, Accessed Apr. 21, 2021 # noqa
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"""
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# numpy case

‎xrspatial/bump.py‎

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Notes:
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----------
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Algorithm References:
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- http://www.mountaincartography.org/mt_hood/pdfs/nighbert_bump1.pdf
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- Nighbert, JS, Bureau of Land Management, Portland, OR, Using “Materials and Textures” in Cartographic Presentations A.K.A. “Bump Mapping”, http://www.mountaincartography.org/mt_hood/pdfs/nighbert_bump1.pdf, Accessed Apr. 21, 2021. # noqa
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Examples:
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res: 1
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Terrrain Example:
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- https://makepath.github.io/xarray-spatial/assets/examples/user-guide.html # noqa
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- makepath, User Guide, https://makepath.github.io/xarray-spatial/assets/examples/user-guide.html, Accessed Apr. 21, 2021. # noqa
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"""
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linx = range(width)

‎xrspatial/classify.py‎

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Adapted from PySal:
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- https://pysal.org/mapclassify/_modules/mapclassify/classifiers.html
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Adapted from PySAL:
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- PySAL, Source code for mapclassify.classifiers, https://pysal.org/mapclassify/_modules/mapclassify/classifiers.html, Accessed Apr. 21, 2021. # noqa
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Adapted from PySAL:
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- https://pysal.org/mapclassify/_modules/mapclassify/classifiers.html#Quantiles # noqa
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- PySAL, Source code for mapclassify.classifiers, https://pysal.org/mapclassify/_modules/mapclassify/classifiers.html#Quantiles, Accessed Apr. 21, 2021. # noqa
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Note that dask's percentile algorithm is approximate,
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while numpy's is exact. This may cause some differences
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Algorithm References:
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Map Classify:
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- https://pysal.org/mapclassify/_modules/mapclassify/classifiers.html#NaturalBreaks # noqa
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- PySAL, Source code for mapclassify.classifiers, https://pysal.org/mapclassify/_modules/mapclassify/classifiers.html#NaturalBreaks, Accessed Apr. 21, 2021. # noqa
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perrygeo:
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- https://github.com/perrygeo/jenks/blob/master/jenks.pyx
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- perrygeo/jenks, https://github.com/perrygeo/jenks/blob/master/jenks.pyx, Apr. 21, 2021. # noqa
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PySal:
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- https://pysal.org/mapclassify/_modules/mapclassify/classifiers.html#EqualInterval # noqa
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- PySAL, Source code for mapclassify.classifiers, https://pysal.org/mapclassify/_modules/mapclassify/classifiers.html#EqualInterval, Accessed Apr. 21, 2021. # noqa
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SciKit:
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- https://scikit-learn.org/stable/auto_examples/classification/plot_classifier_comparison.html#sphx-glr-auto-examples-classification-plot-classifier-comparison-py # noqa
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- scikit-learn, Classifier comparison, https://scikit-learn.org/stable/auto_examples/classification/plot_classifier_comparison.html#sphx-glr-auto-examples-classification-plot-classifier-comparison-py, Accessed Apr. 21, 2021. # noqa
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‎xrspatial/curvature.py‎

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Algorithm References:
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- https://pro.arcgis.com/en/pro-app/latest/tool-reference/spatial-analyst/how-curvature-works.htm # noqa
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- esri, How Curvature works, https://pro.arcgis.com/en/pro-app/latest/tool-reference/spatial-analyst/how-curvature-works.htm, Accessed Apr. 21, 2021. # noqa
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Examples:
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‎xrspatial/hillshade.py‎

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Algorithm References:
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- http://geoexamples.blogspot.com/2014/03/shaded-relief-images-using-gdal-python.html # noqa
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- GeoExamples, Shaded relief images using GDAL python, http://geoexamples.blogspot.com/2014/03/shaded-relief-images-using-gdal-python.html, Accessed Apr. 21, 2021. # noqa
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‎xrspatial/multispectral.py‎

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Algorithm References:
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https://modis.gsfc.nasa.gov/sci_team/pubs/abstract_new.php?id=03667
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- Kaufman, Y. J., & Tanre, D. (1992). Atmospherically resistant vegetation index (ARVI) for EOS-MODIS. IEEE transactions on Geoscience and Remote Sensing, 30(2), 261-270. # noqa
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https://en.wikipedia.org/wiki/Enhanced_vegetation_index
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- Wikipedia, Enhanced Vegetation Index, https://en.wikipedia.org/wiki/Enhanced_vegetation_index, Accessed Apr. 21, 2021. # noqa
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https://en.wikipedia.org/wiki/Enhanced_vegetation_index
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- Wikipedia, Enhanced Vegetation Index, https://en.wikipedia.org/wiki/Enhanced_vegetation_index, Accessed Apr. 21, 2021. # noqa
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- USGS, Landsat Normalized Burn Ratio, https://www.usgs.gov/land-resources/nli/landsat/landsat-normalized-burn-ratio, Accessed Apr. 21, 2021. # noqa
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"NBR2 modifies the Normalized Burn Ratio (NBR)
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https://www.usgs.gov/land-resources/nli/landsat/landsat-normalized-burn-ratio-2
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- USGS, Landsat Normalized Burn Ratio 2, https://www.usgs.gov/land-resources/nli/landsat/landsat-normalized-burn-ratio-2, Accessed Apr. 21, 2021. # noqa
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http://ceholden.github.io/open-geo-tutorial/python/chapter_2_indices.html
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- Holden, C, Chapter 2: Your first remote sensing vegetation index, http://ceholden.github.io/open-geo-tutorial/python/chapter_2_indices.html, Accessed Apr. 21, 2021. # noqa
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Examples:
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>>> import numpy as np
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https://www.usgs.gov/land-resources/nli/landsat/normalized-difference-moisture-index
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- USGS, Normalized Difference Moisture Index, https://www.usgs.gov/land-resources/nli/landsat/normalized-difference-moisture-index, Accessed Apr. 21, 2021. # noqa
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- Huete, A. R. (1988). A soil-adjusted vegetation index (SAVI). Remote sensing of environment, 25(3), 295-309. # noqa
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- Wikipedia, Enhanced Vegetation Index, https://en.wikipedia.org/wiki/Enhanced_vegetation_index, Accessed Apr. 21, 2021. # noqa
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- RDRR.io, EBBI: Enhanced Built-Up and Bareness Index, https://rdrr.io/cran/LSRS/man/EBBI.html, Accessed Apr. 21, 2021. # noqa
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‎xrspatial/pathfinding.py‎

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- Patel, A, Red Blob Games, Implementation of A*, https://www.redblobgames.com/pathfinding/a-star/implementation.html, Accessed Apr. 21, 2021. # noqa
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- Swift, N, Medium, Easy A* (star) Pathfinding, https://medium.com/@nicholas.w.swift/easy-a-star-pathfinding-7e6689c7f7b2, Accessed Apr. 21, 2021. # noqa
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‎xrspatial/perlin.py‎

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numba-ized from Paul Panzer example available here:
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https://stackoverflow.com/questions/42147776/producing-2d-perlin-noise-with-numpy
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http://www.mountaincartography.org/mt_hood/pdfs/nighbert_bump1.pdf
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- numba-ized from Paul Panzer example available here: #noqa
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- tgirod, Panzer, Paul, StackOverflow, https://stackoverflow.com/questions/42147776/producing-2d-perlin-noise-with-numpy, Accessed Apr. 21, 2021. # noqa
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- Nighbert, JS, Bureau of Land Management, Portland, OR, Using “Materials and Textures” in Cartographic Presentations A.K.A. “Bump Mapping”, http://www.mountaincartography.org/mt_hood/pdfs/nighbert_bump1.pdf, Accessed Apr. 21, 2021. # noqa
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