Preprint Article Version 1 This version is not peer-reviewed

Open-Sourced Remote Sensing Data Management with the Irish Earth Observation (IEO) Python Module

Version 1 : Received: 30 May 2018 / Approved: 31 May 2018 / Online: 31 May 2018 (11:12:27 CEST)

How to cite: Serbin, G.; Green, S. Open-Sourced Remote Sensing Data Management with the Irish Earth Observation (IEO) Python Module. Preprints 2018, 2018050470 (doi: 10.20944/preprints201805.0470.v1). Serbin, G.; Green, S. Open-Sourced Remote Sensing Data Management with the Irish Earth Observation (IEO) Python Module. Preprints 2018, 2018050470 (doi: 10.20944/preprints201805.0470.v1).

Abstract

Many remote sensing analytical data products are most useful when they are in an appropriate regional or national projection, rather than globally based projections like Universal Transverse Mercator (UTM) or geographic coordinates, i.e., latitude and longitude. Furthermore, leaving data in the global systems can create problems, either due to misprojection of imagery because of UTM zone boundaries, or because said projections are not optimised for local use. We developed the open-source Irish Earth Observation (IEO) Python module to maintain a local remote sensing data library for Ireland. This pure Python module, in conjunction with the IEOtools Python scripts, utilises the Geospatial Data Abstraction Library (GDAL) for its geoprocessing functionality. At present, the module supports only Landsat TM/ETM+/OLI/TIRS data that have been corrected to surface reflectance using the USGS/ESPA LEDAPS/ LaSRC Collection 1 architecture. This module and the IEOtools catalogue available Landsat data from the USGS/EROS archive, and includes functions for the importation of imagery into a defined local projection and calculation of cloud-free vegetation indices. While this module is distributed with default values and data for Ireland, it can be adapted for other regions with simple modifications to the configuration files and geospatial data sets.

Subject Areas

remote sensing; python; data management; landsat; open-source

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