Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10662/19713
Títulos: Bi-dimensional vector data analysis of positional accuracy of landsat-8 image with pycircularstats
Autores/as: Cuartero Sáez, Aurora
Paoletti Ávila, Mercedes Eugenia
Rey Presas, Andrea
Haut Hurtado, Juan Mario
Palabras clave: Analysis data;Circular graphical statistics;Geospatial big data;Remote sensing;Análisis de datos;Estadísticas de gráficos circulares;Macrodatos geoespaciales;Teledetección
Fecha de publicación: 2022
Editor/a: IEEE
Resumen: Analyzing directional data, in particular circular data, requires methods that are being available in libraries with a well-known prestige as Python including SciPy, NumPy or SciKit-Learn libs. An open-source library has been implemented to be executed by the Python interpreter, called PyCircularStats. Source code: https://github.com/mhaut/pycircularstats The potential of PyCircularStats is shown with an example of analyzing two-dimensional data using circular statistics. The practical case chosen is the positional accuracy analysis of a satellite image of LandSat-8 in Cáceres, Spain, with 99 control points taken with GNSS systems. In this work, the possibilities of two-dimensional data analysis using circular statistics using the PyCircularStats tool with the results of this case of use is presented.
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/10662/19713
ISBN: 978-1-6654-2792-0
DOI: 10.1109/IGARSS46834.2022.9883588.
Colección:DEXGR - Artículos

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