Please use this identifier to cite or link to this item:
http://hdl.handle.net/10662/19713
Title: | Bi-dimensional vector data analysis of positional accuracy of landsat-8 image with pycircularstats |
Authors: | Cuartero Sáez, Aurora Paoletti Ávila, Mercedes Eugenia Rey Presas, Andrea Haut Hurtado, Juan Mario |
Keywords: | Analysis data;Circular graphical statistics;Geospatial big data;Remote sensing;Análisis de datos;Estadísticas de gráficos circulares;Macrodatos geoespaciales;Teledetección |
Issue Date: | 2022 |
Publisher: | IEEE |
Abstract: | 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. |
Description: | 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. |
Appears in Collections: | DEXGR - Congresos, conferencias, etc. DTCYC - Congresos, conferencias, etc. |
Files in This Item:
File | Description | Size | Format | |
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IGARSS46834_2022_9883588.pdf | 1,49 MB | Adobe PDF | View/Open |
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