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Nansat: a Scientist-Orientated Python Package for Geospatial Data Processing Cover

Nansat: a Scientist-Orientated Python Package for Geospatial Data Processing

Open Access
|Oct 2016

Figures & Tables

Figure 1

Schematic flowchart of Nansat instantiation. Details of the process are explained in the text.

Figure 2

UML diagram of the Nansat package including the most important class methods. White boxes describe third party classes.

Figure 3

Example of a simple application of Nansat to collocate and visualize synchronous observations acquired by MODIS and Sentinel1A on 25 May 2011. (A) An RGB image from a MODIS/Aqua acquisition over the Norwegian Sea, (B) a grayscale SAR image from Sentinel-1A, and (C) the data coverage.

Figure 4

Comparison (A) of Sea Surface Temperature (SST) and Chlorophyll-A (Chl-A) from transect (B) across the Barents Sea (the data is retrieved using Nansat, and the figure is generated using Matplotlib and Basemap).

Figure 5

Map of Sea Surface Temperature (SST), sea ice concentration, and sea ice drift streamed from the Norwegian Meteorological Institute, collocated over the Greenland, Barents, and Arctic Seas. The land mass in the centre of the image is Svalbard.

DOI: https://doi.org/10.5334/jors.120 | Journal eISSN: 2049-9647
Language: English
Submitted on: Feb 16, 2016
Accepted on: Sep 27, 2016
Published on: Oct 24, 2016
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2016 Anton A. Korosov, Morten W. Hansen, Knut-Frode Dagestad, Asuka Yamakawa, Aleksander Vines, Maik Riechert, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.