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: | Estadística circular;Circular graphical statistics;Datos geoespaciales;Teledetección;Geospatial big data;Remote sensing |
Fecha de publicación: | 2022-07-17 |
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. |
URI: | http://hdl.handle.net/10662/19713 |
DOI: | 10.1109/IGARSS46834.2022.9883588. |
Colección: | DEXGR - Artículos |
Archivos
Archivo | Descripción | Tamaño | Formato | |
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Bi-Dimensional_Vector_Data_Analysis_of_Positional_Accuracy_of_Landsat-8_Image_with_Pycircularstats.pdf | 1,5 MB | Adobe PDF | Descargar |
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