Automating LiDAR Dataset Retrieval and Geodesic Viewshed Generation with Python

Data collection is often the most time-consuming part of a GIS research project. For a viewshed analysis this involves identifying the coverage areas and selecting the exact grid squares required by the study area. The goal of this tool is to save the end-user time by automating the LiDAR download and viewshed calculation. This tool is run via the ArcGIS Pro geoprocessing GUI through a custom python tool in a custom toolbox. This tool is specifically designed to retrieve LiDAR data from Pennsylvania Lidar Navigator hosted by Pennsylvania Spatial Data Access, or PASDA. The tool generates a polygon around the target site which is used to select LAS grid squares that were imported via REST URL. These LAS grid squares are then used to download their linked LAS datasets, merged into one universal LAS dataset, and then used to run a geodesic viewshed. The completion of this script produces a viewshed layer with automatic symbolization of green: land visible up to eighty feet above ground level, blue: land visible from eighty feet to one hundred twenty feet above ground level, and no fill color for anything above one hundred twenty feet above ground level. Testing with this tool has resulted in successful viewshed calculations with distances between observer and target features ranging from three statute miles to twenty-six statute miles. With the tool successfully downloading and generating viewsheds this tool allows end-users to multitask while this tool runs in the background, effectively saving the end-user time.

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Publication Details

Journal
UA Campus Repository (The University of Arizona)
Published
2025-01-01
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
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article

Automating LiDAR Dataset Retrieval and Geodesic Viewshed Generation with Python

UA Campus Repository (The University of Arizona)
Remote Sensing and LiDAR Applications
article

Automating LiDAR Dataset Retrieval and Geodesic Viewshed Generation with Python

article en

Abstract

Data collection is often the most time-consuming part of a GIS research project. For a viewshed analysis this involves identifying the coverage areas and selecting the exact grid squares required by the study area. The goal of this tool is to save the end-user time by automating the LiDAR download and viewshed calculation. This tool is run via the ArcGIS Pro geoprocessing GUI through a custom python tool in a custom toolbox. This tool is specifically designed to retrieve LiDAR data from Pennsylvania Lidar Navigator hosted by Pennsylvania Spatial Data Access, or PASDA. The tool generates a polygon around the target site which is used to select LAS grid squares that were imported via REST URL. These LAS grid squares are then used to download their linked LAS datasets, merged into one universal LAS dataset, and then used to run a geodesic viewshed. The completion of this script produces a viewshed layer with automatic symbolization of green: land visible up to eighty feet above ground level, blue: land visible from eighty feet to one hundred twenty feet above ground level, and no fill color for anything above one hundred twenty feet above ground level. Testing with this tool has resulted in successful viewshed calculations with distances between observer and target features ranging from three statute miles to twenty-six statute miles. With the tool successfully downloading and generating viewsheds this tool allows end-users to multitask while this tool runs in the background, effectively saving the end-user time.

UA Campus Repository (The University of Arizona)
National Geographic Society (US)
Openalex Percentile: Top 54%
Remote Sensing and LiDAR Applications
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Automating LiDAR Dataset Retrieval and Geodesic Viewshed Generation with Python · UA Campus Repository (The University of Arizona) (2025) | TGRS Research Map | TGRS