Abstract
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.
Highlights
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
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 built into Nansat
This paper describes a new tool to handle the interpretation and processing of geospatial data from satellite images and numerical models.Typical operations on such data include visualization for human perception of spatial patterns, extraction of geophysical values, pixel-per-pixel or contextual calculation of new geophysical variables based on one or several input datasets, re-gridding to another coordinate system, co-location of several datasets on one spatial grid, subsetting in space, and automatic recognition and description of objects
Summary
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. 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 built into Nansat. GDAL provides low-level access to the data, and a scientific user is often required to perform several complicated operations in order to eventually fetch the values of the required geophysical variable at a given resolution and region of interest.
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