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

Journal of Open Research Software

Asuka Yamakawa¹  Anton A. Korosov¹  Aleksander Vines¹  Morten W. Hansen¹  Knut-Frode Dagestad²  Maik Riechert³ 

[1] Nansen Envirnmental and Remote Sensing Center;Norwegian Meteorological Institute;University of Reading;

关键词: Python, Nansat, GDAL, geospatial data, satellite remote sensing, data synergy, data handling;   

DOI  :  10.5334/jors.120

来源: DOAJ

【 摘 要 】

Nansat is a Python toolbox for analysing and processing 2-dimensional geospatial data, such as satellite imagery, output from numerical models, and gridded in-situ data. It is created with strong focus on facilitating research, and development of algorithms and autonomous processing systems. Nansat extends the widely used Geospatial Abstraction Data Library (GDAL) by adding scientific meaning to the datasets through metadata, and by adding common functionality for data analysis and handling (e.g., exporting to various data formats). Nansat uses metadata vocabularies that follow international metadata standards, in particular the Climate and Forecast (CF) conventions, and the NASA Directory Interchange Format (DIF) and Global Change Master Directory (GCMD) keywords. Functionality that is commonly needed in scientific work, such as seamless access to local or remote geospatial data in various file formats, collocation of datasets from different sources and geometries, and visualization, is also built into Nansat. The paper presents Nansat workflows, its functional structure, and examples of typical applications.

【 授权许可】

Unknown