Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10662/19717
Títulos: | Pycircularstats: a python-based tool for remote sensing circular statistics and graphical analysis |
Autores/as: | Cuartero Sáez, Aurora Paoletti Ávila, Mercedes Eugenia García Rodríguez, Pablo Haut Hurtado, Juan Mario |
Palabras clave: | Analysis data;Circular graphical statistics;Geospatial data engineering;Remote sensing;Análisis de datos;Estadísticas de gráficos circulares;Ingeniería de los datos geoespaciales;Teledetección |
Fecha de publicación: | 2022 |
Editor/a: | IEEE |
Resumen: | Circular data, as a part of directional data engineering, is used in a wide range of fields such as Geology, Biology, Meteorology and Geomatics. It differs from traditional linear data because it is closed and has no beginning or end along the real line, i.e., circular data occurs around a circle, normally measured in degrees. Analyzing directional data, in particular circular data, requires methods that are be available in libraries with a well-known prestige as Python including SciPy, NumPy or SciKit-Learn libs. However, these libraries have a specific area of expertise and they do not combine information in a useful way for two-dimensional data analysis. In this paper, an open-source library has been implemented to be executed by the Python interpreter, called PyCircularStats. Source code: https://github.com/mhaut/pycircularstats |
Descripción: | Ponencia presentada en IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. Kuala Lumpur, Malaysia, 17-22 July 2022 |
URI: | http://hdl.handle.net/10662/19717 |
ISBN: | 978-1-6654-2792-0 |
DOI: | 10.1109/IGARSS46834.2022.9884758 |
Colección: | DEXGR - Artículos DISIT - Artículos DTCYC - Artículos |
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