Lidar has become the de facto source for elevation data for its accuracy and detailed surface models. Lidar data can be acquired from various platforms, ranging from high-altitude, fixed-wing, manned and unmanned aircraft to moving vehicles and stationary tripods. The USGS 3DEP programme offers semi-continental coverage of Lidar data for free.
DEMs are files that contain either points (vector) or pixels (raster), with each point or pixel having an elevation value. DEMs: digital elevation models represent the land or "bare earth" (no trees, buildings, etc.)
This project aims to create Lidar_3DEM python package that is used to extract data from Amazon s3 bucket and process it to get elevation and 3D visualization.
We have use USGS public dataset found here "https://s3-us-west-2.amazonaws.com/usgs-lidar-public/"
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Data_from_url : fetech data from the s3 bucket based on user input bound
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Dataframe_From_Bounds : Accepts list of bounds and returen year agergated points
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Input_dataframe : Accept bounds and return dataframe that contains elevation and Points
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Plots : Accepts dataframe that contains elevation and point will plot 3d projection of input data.
- Calculating TWI
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