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<div class="section" id="reading-raster-files-with-gdal">
<h1>Reading raster files with GDAL<a class="headerlink" href="#reading-raster-files-with-gdal" title="Permalink to this headline">¶</a></h1>
<p>With GDAL, you can read and write <a class="reference external" href="http://www.gdal.org/formats_list.html">several different raster formats</a> in Python. Python automatically registers all known GDAL drivers for reading supported
formats when the importing the GDAL module. Most common file formats include for example <a class="reference external" href="http://www.gdal.org/frmt_gtiff.html">TIFF and GeoTIFF</a>,
<a class="reference external" href="http://www.gdal.org/frmt_various.html#AAIGrid">ASCII Grid</a> and <a class="reference external" href="http://www.gdal.org/frmt_hfa.html">Erdas Imagine .img</a> -files.</p>
<p><a class="reference external" href="http://landsat.gsfc.nasa.gov/landsat-8/landsat-8-bands/">Landsat 8</a> bands are stored as separate GeoTIFF -files in the original package.
Each band contains information of surface reflectance from different ranges
of the electromagnetic spectrum.</p>
<p>Let’s start with inspecting one of the files we downloaded:</p>
<div class="code python highlight-default"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">osgeo</span> <span class="k">import</span> <span class="n">gdal</span>
<span class="n">filepath</span> <span class="o">=</span> <span class="s2">r"LandsatData/LC81910182016153LGN00_sr_band4.tif"</span>
<span class="c1"># Open the file:</span>
<span class="n">raster</span> <span class="o">=</span> <span class="n">gdal</span><span class="o">.</span><span class="n">Open</span><span class="p">(</span><span class="n">filepath</span><span class="p">)</span>
<span class="c1"># Check type of the variable 'raster'</span>
<span class="nb">type</span><span class="p">(</span><span class="n">raster</span><span class="p">)</span>
</pre></div>
</div>
<div class="section" id="read-raster-file-properties">
<h2>Read raster file properties<a class="headerlink" href="#read-raster-file-properties" title="Permalink to this headline">¶</a></h2>
<p>The satellite image is now stored as a GDAL Dataset object in the variable <code class="docutils literal"><span class="pre">raster</span></code>. Let’s have a closer look at the properties of the file:</p>
<div class="code python highlight-default"><div class="highlight"><pre><span></span><span class="c1"># Projection</span>
<span class="n">raster</span><span class="o">.</span><span class="n">GetProjection</span><span class="p">()</span>
<span class="c1"># Dimensions</span>
<span class="n">raster</span><span class="o">.</span><span class="n">RasterXSize</span>
<span class="n">raster</span><span class="o">.</span><span class="n">RasterYSize</span>
<span class="c1"># Number of bands</span>
<span class="n">raster</span><span class="o">.</span><span class="n">RasterCount</span>
<span class="c1"># Metadata for the raster dataset</span>
<span class="n">raster</span><span class="o">.</span><span class="n">GetMetadata</span><span class="p">()</span>
</pre></div>
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</div>
<div class="section" id="get-raster-bands">
<h2>Get raster bands<a class="headerlink" href="#get-raster-bands" title="Permalink to this headline">¶</a></h2>
<p>In our case, all bands of the Landsat 8 scene are stored as separate files. <code class="docutils literal"><span class="pre">rasterCount</span></code> is 1 as we have only opened one GeoTiff containing Landsat 8 band 4.
However, different bands of a satellite images are often stacked together in one raster dataset in which case <code class="docutils literal"><span class="pre">rasterCount</span></code> would be greater than one.</p>
<p>In order to have a closer look at the values stored in the band, we will take advantage of the <a class="reference external" href="http://gdal.org/python/osgeo.gdal.Band-class.html">GDAL Band API</a>.</p>
<div class="code python highlight-default"><div class="highlight"><pre><span></span><span class="c1"># Read the raster band as separate variable</span>
<span class="n">band</span> <span class="o">=</span> <span class="n">raster</span><span class="o">.</span><span class="n">GetRasterBand</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
<span class="c1"># Check type of the variable 'band'</span>
<span class="nb">type</span><span class="p">(</span><span class="n">band</span><span class="p">)</span>
<span class="c1"># Data type of the values</span>
<span class="n">gdal</span><span class="o">.</span><span class="n">GetDataTypeName</span><span class="p">(</span><span class="n">band</span><span class="o">.</span><span class="n">DataType</span><span class="p">)</span>
</pre></div>
</div>
<p>Now we have a GDAL Raster Band object stored in the variable band.</p>
<p>Data type of the band can be interpreted with the help of GDAL documentation on <a class="reference external" href="http://www.gdal.org/gdal_8h.html#a22e22ce0a55036a96f652765793fb7a4">Pixel data types</a>.
Unsigned integer is always equal or greater than zero and signed integer can store also negative values. For example, an unsigned 16-bit integer can
store 2^16 (=65,536) values ranging from 0 to 65,535.</p>
</div>
<div class="section" id="band-statistics">
<h2>Band statistics<a class="headerlink" href="#band-statistics" title="Permalink to this headline">¶</a></h2>
<p>Next, let’s have a look at the values that are stored in the band. You might need to calculate statistics for the raster before being able to print out any information.</p>
<div class="code python highlight-default"><div class="highlight"><pre><span></span><span class="c1"># Compute statistics if needed</span>
<span class="k">if</span> <span class="n">band</span><span class="o">.</span><span class="n">GetMinimum</span><span class="p">()</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">or</span> <span class="n">band</span><span class="o">.</span><span class="n">GetMaximum</span><span class="p">()</span><span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">band</span><span class="o">.</span><span class="n">ComputeStatistics</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Statistics computed."</span><span class="p">)</span>
<span class="c1"># Fetch metadata for the band</span>
<span class="n">band</span><span class="o">.</span><span class="n">GetMetadata</span><span class="p">()</span>
<span class="c1"># Print only selected metadata:</span>
<span class="nb">print</span> <span class="p">(</span><span class="s2">"[ NO DATA VALUE ] = "</span><span class="p">,</span> <span class="n">band</span><span class="o">.</span><span class="n">GetNoDataValue</span><span class="p">())</span> <span class="c1"># none</span>
<span class="nb">print</span> <span class="p">(</span><span class="s2">"[ MIN ] = "</span><span class="p">,</span> <span class="n">band</span><span class="o">.</span><span class="n">GetMinimum</span><span class="p">())</span>
<span class="nb">print</span> <span class="p">(</span><span class="s2">"[ MAX ] = "</span><span class="p">,</span> <span class="n">band</span><span class="o">.</span><span class="n">GetMaximum</span><span class="p">())</span>
</pre></div>
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