sandboxed-api/oss-internship-2020/gdal

GDAL Raster GeoTIFF Workflow

Build Tools: CMake/Ninja
OS: Linux

For installing GDAL:

sudo apt-get install python3.6-dev

sudo add-apt-repository ppa:ubuntugis/ppa && sudo apt update

sudo apt-get install gdal-bin

sudo apt-get install libgdal-dev

Dependencies:

PNG: sudo apt-get install libpng-dev

PCRE: sudo apt-get install libpcre3 libpcre3-dev

PROJ: sudo apt-get install libproj-dev

OBS! You may need to set export LD_LIBRARY_PATH=/lib:/usr/lib:/usr/local/lib. It is required for libproj.so to be found into /usr/local/lib/. You can also fix this by typing locate libproj.so which will give you <the_absolute_path_of_libproj.so> and then cp <the_absolute_path_of_libproj.so> /usr/local/lib/.

Initializing GDAL submodule:

git submodule add https://github.com/OSGeo/gdal/tree/master/gdal

Building GDAL statically

GNUmakefile from gdal/gdal can handle building the static library.

cd gdal/gdal && make static-lib

cd ../.. && mkdir lib

cp gdal/gdal/libgdal.a lib/

OBS! The file is huge! It may take a while.

For testing:

mkdir build && cd build

cmake .. -G Ninja

ninja

./raster <your_absolute_tiff_file_path>

About the project

GDAL is a translator library for raster and vector geospatial data format. The project consist in rastering a GeoTIFF file format using GDAL functionalities and sandboxed methods.

Implementation

Sandboxing...

The purpose of sandboxing is to limit the permissions and capabilities of library’s methods, in order to secure the usage of them. After obtaining the sandbox, the functions will be called through an Sandbox API (being called api in the current test) and so, the operations, system calls or namspaces access may be controlled.

Raster process...

From gdal.h header useful methods are added to sapi library builded with CMake.

One .tiff file is manipulated with GDALOpen functionality, which extracts a pointer to the data set containg a list of raster bands, all pertaining to the same area. Metadata, a coordinate system, a georeferencing transform, size of raster and various other information are kept into the data set that corresponds to the image.

To create an array containing the image information, the dimentions needed are extracted using some specific GDAL(X/Y)Size functions applied to the block. GDALRasterBand function takes care of data type conversion, one more step following: placing the converted data (with RasterIO method) into the created and well allocated structure.