Accessing and Visualizing Digital Elevation Models with Python

<p><strong>Digital Elevation Models (DEMs)&nbsp;</strong>represent a 3D surface model of the terrain. It represents a continuous topographic elevation surface through a series of cells where each cell represents the elevation (Z) of a feature at its location (X and Y). Digital Elevation Models only contain information about the elevation of geological features, such as valleys, mountains, and landslides, and do not include any elevation data concerning features such as vegetation or buildings.</p> <p>Accurate high-resolution DEM data is important for hazard mapping because it provides a detailed representation of the terrain which is essential for assessing potential risks posed by natural hazards. This data can better inform predictive models of how climate change will affect various land surfaces, by allowing scientists to measure the effects of changing temperature, precipitation, and other climate-related factors on land surfaces of different elevations. DEM data can also be used to identify areas that are at risk of flooding, landslides, and other extreme weather events, which can help inform policy decisions about how to mitigate the impacts of climate change. Additionally, DEM data helps to create detailed maps which can be used to create evacuation plans, alert systems, and other risk-management strategies.</p> <p><a href="https://towardsdatascience.com/accessing-and-visualizing-digital-elevation-models-with-python-f4fd7f595d46">Read More</a></p>