2020-09-23 23:39:49 +08:00
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# GDAL Raster GeoTIFF Workflow
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```
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Build Tools: CMake/Ninja
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OS: Linux
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```
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2020-09-24 02:35:19 +08:00
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### For installing GDAL:
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`sudo apt-get install python3.6-dev`
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`sudo add-apt-repository ppa:ubuntugis/ppa && sudo apt update`
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`sudo apt-get install gdal-bin`
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`sudo apt-get install libgdal-dev`
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### Dependencies:
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PNG: `sudo apt-get install libpng-dev`
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PCRE: `sudo apt-get install libpcre3 libpcre3-dev`
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PROJ: `sudo apt-get install libproj-dev`
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### Initializing GDAL submodule:
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`git submodule add https://github.com/OSGeo/gdal/tree/master/gdal`
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2020-09-24 02:43:21 +08:00
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### Building GDAL statically
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GNUmakefile from gdal/gdal can handle building the static library.
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`cd gdal/gdal && make static-lib`
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`cd ../.. && mkdir lib`
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`cp gdal/gdal/libgdal.a lib/`
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OBS: The file is huge! It may take a while.
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2020-09-24 02:35:19 +08:00
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2020-09-23 23:39:49 +08:00
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### For testing:
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`mkdir build && cd build`
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`cmake .. -G Ninja`
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`ninja`
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2020-09-24 02:35:19 +08:00
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`./raster <your_absolute_tiff_file_path>`
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2020-09-23 23:39:49 +08:00
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## About the project
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2020-09-24 02:35:19 +08:00
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GDAL is a translator library for raster and vector
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geospatial data format.
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The project consist in rastering a GeoTIFF file format
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using GDAL functionalities and sandboxed methods.
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2020-09-23 23:39:49 +08:00
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## Implementation
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*Sandboxing...*
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The purpose of sandboxing is to limit the permissions
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and capabilities of library’s methods, in order to
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secure the usage of them. After obtaining the sandbox,
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the functions will be called through an Sandbox API
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(being called api in the current test) and so, the
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operations, system calls or namspaces access may be
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controlled.
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*Raster process...*
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From gdal.h header useful methods are added to sapi
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library builded with CMake.
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One .tiff file is manipulated with GDALOpen
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functionality, which extracts a pointer to the data set
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containg a list of raster bands, all pertaining to the
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same area.
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Metadata, a coordinate system, a georeferencing
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transform, size of raster and various other information
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are kept into the data set that corresponds to the image.
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To create an array containing the image information, the
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dimentions needed are extracted using some specific
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GDAL(X/Y)Size functions applied to the block.
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GDALRasterBand function takes care of data type conversion, one more step following: placing the
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converted data (with RasterIO method) into the created
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and well allocated structure.
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