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Software
Published in Rémi Cresson, Deep Learning for Remote Sensing Images with Open Source Software, 2020
There are many types of geospatial images processing software, of which many are powerful open source programs like GRASS, SAGA, GDAL, and the Orfeo ToolBox.1 The Orfeo ToolBox, also known as OTB ref to figure 2.1, is an open source library for remote sensing image processing developed by the French spatial agency (CNES). It contains about a hundred user-oriented applications including geometric and radiometric corrections, image manipulation, statistics, etc. It is suited for large-scale remote sensing image processing, offering a great number of functions and algorithms [16]. It is based on the Insight ToolKit2 (ITK), a widely used open source library for medical image computation, and the Geospatial Data Abstraction Library3 (GDAL). Additional optional libraries enrich the features of OTB (OpenCV, Shark ML, etc.).
Geographic data I/O
Published in Robin Lovelace, Jakub Nowosad, Jannes Muenchow, Geocomputation with R, 2019
Robin Lovelace, Jakub Nowosad, Jannes Muenchow
GDAL (which should be pronounced “goo-dal”, with the double “o” making a reference to object-orientation), the Geospatial Data Abstraction Library, has resolved many issues associated with incompatibility between geographic file formats since its release in 2000. GDAL provides a unified and high-performance interface for reading and writing of many raster and vector data formats. Many open and proprietary GIS programs, including GRASS, ArcGIS and QGIS, use GDAL behind their GUIs for doing the legwork of ingesting and spitting out geographic data in appropriate formats.
Unsupervised Classification
Published in Stacy A. C. Nelson, Siamak Khorram, Image Processing and Data Analysis with ERDAS IMAGINE®, 2018
Stacy A. C. Nelson, Siamak Khorram
Next select, GDAL/OGR | [GDAL] Extraction | Clip raster by extent. GDAL refers to the Geospatial Data Abstraction Library for raster and vector geospatial data formats. Whereas, OGR refers to the OpenGIS Simple Features Reference Implementation, which allows some writing and reading of vector file formats and is a part of the GDAL library.
A prototype web-based analysis platform for drought monitoring and early warning
Published in International Journal of Digital Earth, 2020
Mattijn van Hoek, Jie Zhou, Li Jia, Jing Lu, Chaolei Zheng, Guangcheng Hu, Massimo Menenti
The ingestion-service component functions as a bridge between raw datasets and the array Database Management System (array DBMS). PyMODIS (Delucchi and Neteler 2013) is adopted to retrieve MODIS HDF/XML files. The RasImport tool and Web Coverage Service-Transactional (WCS-T) (Baumann 2016) are used to import or update retrieved multi-dimensional (meta)data into the array DBMS. To introduce consistency among the ingested datasets, Geospatial Data Abstraction Library (GDAL/OGR contributors 2018) (GDAL) was used for conversion and transformation of different raster geospatial formats. All the raw datasets involved in the system were automatically retrieved from their online source and ingested in the array DBMS using a regular tiling scheme.