{"id":12456,"date":"2023-09-07T08:05:39","date_gmt":"2023-09-07T08:05:39","guid":{"rendered":"https:\/\/www.digitaldesignjournal.com\/?p=12456"},"modified":"2023-09-15T07:55:25","modified_gmt":"2023-09-15T07:55:25","slug":"python-elevation-profile-with-example","status":"publish","type":"post","link":"https:\/\/www.digitaldesignjournal.com\/python-elevation-profile-with-example\/","title":{"rendered":"Python Elevation Profile With Example"},"content":{"rendered":"\n<p>To create an elevation profile in Python, you can use various libraries and data sources. Here, I&#8217;ll provide a simple example using Python and the Matplotlib library to visualize elevation data along a path. We&#8217;ll also use the SRTM (Shuttle Radar Topography Mission) dataset, which provides elevation data for most of the Earth&#8217;s landmasses.<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>Install required libraries: First, you need to install the following libraries if you haven&#8217;t already:<ul><li>Matplotlib: for plotting.<\/li><li>Numpy: for numerical operations.<\/li><li>OpenTopography API (optional): for downloading elevation data. You can also use other sources or local elevation data.<\/li><\/ul>You can install them using pip:<\/li>\n<\/ol>\n\n\n<pre class=\"wp-block-code\" aria-describedby=\"shcb-language-1\" data-shcb-language-name=\"Python\" data-shcb-language-slug=\"python\"><span><code class=\"hljs language-python\">pip install matplotlib numpy opentopography-py<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-1\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">Python<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">python<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre>\n\n\n<ol class=\"wp-block-list\" start=\"2\">\n<li>Create a Python script to generate an elevation profile:<\/li>\n<\/ol>\n\n\n<pre class=\"wp-block-code\" aria-describedby=\"shcb-language-2\" data-shcb-language-name=\"Python\" data-shcb-language-slug=\"python\"><span><code class=\"hljs language-python\"><span class=\"hljs-keyword\">import<\/span> numpy <span class=\"hljs-keyword\">as<\/span> np\n<span class=\"hljs-keyword\">import<\/span> matplotlib.pyplot <span class=\"hljs-keyword\">as<\/span> plt\n<span class=\"hljs-keyword\">import<\/span> opentopography\n\n<span class=\"hljs-function\"><span class=\"hljs-keyword\">def<\/span> <span class=\"hljs-title\">get_elevation_data<\/span><span class=\"hljs-params\">(latitude, longitude, distance_km)<\/span>:<\/span>\n    <span class=\"hljs-comment\"># You can replace this with your own elevation data source or API.<\/span>\n    <span class=\"hljs-comment\"># Here, we are using OpenTopography to download data.<\/span>\n    elevation_data = opentopography.get_elevation(&#91;longitude], &#91;latitude], meters=<span class=\"hljs-literal\">True<\/span>, sources=<span class=\"hljs-string\">\"SRTM1\"<\/span>)\n    elevation_profile = elevation_data&#91;<span class=\"hljs-number\">0<\/span>]&#91;<span class=\"hljs-string\">\"elevationProfile\"<\/span>]\n\n    <span class=\"hljs-comment\"># Convert the distance to kilometers.<\/span>\n    distances_km = np.linspace(<span class=\"hljs-number\">0<\/span>, distance_km, len(elevation_profile))\n    \n    <span class=\"hljs-keyword\">return<\/span> distances_km, elevation_profile\n\n<span class=\"hljs-function\"><span class=\"hljs-keyword\">def<\/span> <span class=\"hljs-title\">plot_elevation_profile<\/span><span class=\"hljs-params\">(distances_km, elevation_profile)<\/span>:<\/span>\n    plt.figure(figsize=(<span class=\"hljs-number\">10<\/span>, <span class=\"hljs-number\">5<\/span>))\n    plt.plot(distances_km, elevation_profile)\n    plt.title(<span class=\"hljs-string\">\"Elevation Profile\"<\/span>)\n    plt.xlabel(<span class=\"hljs-string\">\"Distance (km)\"<\/span>)\n    plt.ylabel(<span class=\"hljs-string\">\"Elevation (meters)\"<\/span>)\n    plt.grid()\n    plt.show()\n\n<span class=\"hljs-keyword\">if<\/span> __name__ == <span class=\"hljs-string\">\"__main__\"<\/span>:\n    <span class=\"hljs-comment\"># Replace with your desired latitude, longitude, and path distance.<\/span>\n    latitude = <span class=\"hljs-number\">37.7749<\/span>  <span class=\"hljs-comment\"># Example: San Francisco, CA<\/span>\n    longitude = <span class=\"hljs-number\">-122.4194<\/span>\n    path_distance_km = <span class=\"hljs-number\">10<\/span>\n\n    distances_km, elevation_profile = get_elevation_data(latitude, longitude, path_distance_km)\n    plot_elevation_profile(distances_km, elevation_profile)\n<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-2\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">Python<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">python<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre>\n\n\n<ol class=\"wp-block-list\" start=\"3\">\n<li>Replace the <code>latitude<\/code>, <code>longitude<\/code>, and <code>path_distance_km<\/code> values with your desired location and path distance. This script will download elevation data using OpenTopography (you can use other sources) and then plot the elevation profile.Make sure you have an active internet connection when running this script, as it fetches data from a remote source (OpenTopography in this case).<\/li>\n<\/ol>\n\n\n\n<p>Remember that there are many sources of elevation data, and you may need to adapt the data retrieval part of the code to match your specific requirements or data sources if needed.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Visualize digital elevation models in 3D using python<\/h2>\n\n\n\n<p>Visualizing Digital Elevation Models (DEMs) in 3D using Python can be achieved using libraries like Matplotlib and mayavi. In this example, I&#8217;ll show you how to visualize a DEM in 3D using Matplotlib:<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Install Dependencies:<\/strong> First, make sure you have the necessary libraries installed. You can install them using pip:<\/li>\n<\/ol>\n\n\n<pre class=\"wp-block-code\" aria-describedby=\"shcb-language-3\" data-shcb-language-name=\"Python\" data-shcb-language-slug=\"python\"><span><code class=\"hljs language-python\">pip install numpy matplotlib<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-3\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">Python<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">python<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre>\n\n\n<ol class=\"wp-block-list\" start=\"2\">\n<li><strong>Load DEM Data:<\/strong> You should have a DEM file in GeoTIFF or similar format. Use the GDAL library (as mentioned in the previous response) to load the DEM data into a NumPy array.<\/li>\n\n\n\n<li><strong>3D Visualization with Matplotlib:<\/strong><\/li>\n<\/ol>\n\n\n<pre class=\"wp-block-code\" aria-describedby=\"shcb-language-4\" data-shcb-language-name=\"Python\" data-shcb-language-slug=\"python\"><span><code class=\"hljs language-python\"><span class=\"hljs-keyword\">import<\/span> numpy <span class=\"hljs-keyword\">as<\/span> np\n<span class=\"hljs-keyword\">import<\/span> matplotlib.pyplot <span class=\"hljs-keyword\">as<\/span> plt\n<span class=\"hljs-keyword\">from<\/span> mpl_toolkits.mplot3d <span class=\"hljs-keyword\">import<\/span> Axes3D\n\n<span class=\"hljs-comment\"># Load your DEM data into a NumPy array<\/span>\n<span class=\"hljs-comment\"># Replace 'elevation_array' with your actual DEM data<\/span>\n<span class=\"hljs-comment\"># For example, elevation_array = dataset.ReadAsArray()<\/span>\n\n<span class=\"hljs-comment\"># Create a grid of coordinates for the DEM<\/span>\nx, y = np.meshgrid(np.arange(<span class=\"hljs-number\">0<\/span>, elevation_array.shape&#91;<span class=\"hljs-number\">1<\/span>]), np.arange(<span class=\"hljs-number\">0<\/span>, elevation_array.shape&#91;<span class=\"hljs-number\">0<\/span>]))\n\n<span class=\"hljs-comment\"># Create a 3D figure<\/span>\nfig = plt.figure()\nax = fig.gca(projection=<span class=\"hljs-string\">'3d'<\/span>)\n\n<span class=\"hljs-comment\"># Plot the surface using Matplotlib's plot_surface function<\/span>\nsurf = ax.plot_surface(x, y, elevation_array, cmap=<span class=\"hljs-string\">'terrain'<\/span>, rstride=<span class=\"hljs-number\">1<\/span>, cstride=<span class=\"hljs-number\">1<\/span>, linewidth=<span class=\"hljs-number\">0<\/span>, antialiased=<span class=\"hljs-literal\">False<\/span>)\n\n<span class=\"hljs-comment\"># Add a color bar which maps values to colors<\/span>\nfig.colorbar(surf, shrink=<span class=\"hljs-number\">0.5<\/span>, aspect=<span class=\"hljs-number\">5<\/span>)\n\n<span class=\"hljs-comment\"># Set labels and title<\/span>\nax.set_xlabel(<span class=\"hljs-string\">'X'<\/span>)\nax.set_ylabel(<span class=\"hljs-string\">'Y'<\/span>)\nax.set_zlabel(<span class=\"hljs-string\">'Elevation (meters)'<\/span>)\nax.set_title(<span class=\"hljs-string\">'3D DEM Visualization'<\/span>)\n\n<span class=\"hljs-comment\"># Show the plot<\/span>\nplt.show()\n<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-4\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">Python<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">python<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre>\n\n\n<p>In this code:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>We create a grid of x and y coordinates that correspond to the rows and columns of the DEM data.<\/li>\n\n\n\n<li>We use Matplotlib&#8217;s <code>plot_surface<\/code> function to create the 3D surface plot.<\/li>\n\n\n\n<li>The <code>cmap='terrain'<\/code> argument specifies a colormap for the elevation data, which gives a terrain-like appearance.<\/li>\n\n\n\n<li>Finally, we set labels, a title, and display the 3D plot using <code>plt.show()<\/code>.<\/li>\n<\/ul>\n\n\n\n<p>Make sure to replace <code>elevation_array<\/code> with your actual DEM data loaded from the file. You can further customize the visualization by adjusting parameters like colormap, lighting, and viewpoint.<\/p>\n\n\n\n<p>Note that this is a basic example of 3D DEM visualization. Depending on your specific needs and data, you can explore more advanced visualization techniques and libraries like Mayavi for more interactive 3D visualizations.<\/p>\n\n\n\n<p><strong>Read More;<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/www.digitaldesignjournal.com\/python-cprofile-to-csv-with-example\/\">Python cProfile to CSV With Example<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/www.digitaldesignjournal.com\/python-profile-to-file-with-examples\/\">Python Profile to File With Examples<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/www.digitaldesignjournal.com\/python-profile-memory-usage\/\">Python Profile Memory Usage<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/www.digitaldesignjournal.com\/python-cprofile-snakeviz-with-example\/\">Python cProfile Snakeviz With Example<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/www.digitaldesignjournal.com\/data-profiling-in-python-using-pandas\/\">Data Profiling in Python Using Pandas<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/www.digitaldesignjournal.com\/python-profiling-vscode-with-example\/\">Python Profiling vscode With Example<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/www.digitaldesignjournal.com\/python-profiling-flame-graph-with-example\/\">Python Profiling Flame Graph With Example<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/www.digitaldesignjournal.com\/python-cprofile-docker-with-example\/\">Python cProfile Docker With Example<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/www.digitaldesignjournal.com\/python-cprofile-graphviz-with-example\/\">Python cProfile Graphviz With Example<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/www.digitaldesignjournal.com\/python-eda-profiling-with-example\/\">Python eda Profiling With Example<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/www.digitaldesignjournal.com\/python-cprofile-limit-depth-solution\/\">Python cProfile Limit Depth<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/www.digitaldesignjournal.com\/python-cprofile-to-html\/\">Python cProfile to HTML With Example<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>To create an elevation profile in Python, you can use various libraries and data sources. Here, I&#8217;ll provide a simple &#8230; <a title=\"Python Elevation Profile With Example\" class=\"read-more\" href=\"https:\/\/www.digitaldesignjournal.com\/python-elevation-profile-with-example\/\" aria-label=\"More on Python Elevation Profile With Example\">Read more<\/a><\/p>\n","protected":false},"author":12,"featured_media":12458,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[92],"tags":[150],"ppma_author":[148],"class_list":["post-12456","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-python","tag-python-profiling","author-abdullah-walied-allama"],"authors":[{"term_id":148,"user_id":12,"is_guest":0,"slug":"abdullah-walied-allama","display_name":"Abdullah Walied Allama","avatar_url":{"url":"https:\/\/www.digitaldesignjournal.com\/wp-content\/uploads\/2023\/08\/Abdullah-Walied-Allama.jpg","url2x":"https:\/\/www.digitaldesignjournal.com\/wp-content\/uploads\/2023\/08\/Abdullah-Walied-Allama.jpg"},"0":null,"1":"","2":"","3":"","4":"","5":"","6":"","7":"","8":""}],"_links":{"self":[{"href":"https:\/\/www.digitaldesignjournal.com\/wp-json\/wp\/v2\/posts\/12456","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.digitaldesignjournal.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.digitaldesignjournal.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.digitaldesignjournal.com\/wp-json\/wp\/v2\/users\/12"}],"replies":[{"embeddable":true,"href":"https:\/\/www.digitaldesignjournal.com\/wp-json\/wp\/v2\/comments?post=12456"}],"version-history":[{"count":5,"href":"https:\/\/www.digitaldesignjournal.com\/wp-json\/wp\/v2\/posts\/12456\/revisions"}],"predecessor-version":[{"id":12651,"href":"https:\/\/www.digitaldesignjournal.com\/wp-json\/wp\/v2\/posts\/12456\/revisions\/12651"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.digitaldesignjournal.com\/wp-json\/wp\/v2\/media\/12458"}],"wp:attachment":[{"href":"https:\/\/www.digitaldesignjournal.com\/wp-json\/wp\/v2\/media?parent=12456"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.digitaldesignjournal.com\/wp-json\/wp\/v2\/categories?post=12456"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.digitaldesignjournal.com\/wp-json\/wp\/v2\/tags?post=12456"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/www.digitaldesignjournal.com\/wp-json\/wp\/v2\/ppma_author?post=12456"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}