Abstract

Abstract. Computerized path planning, not constrained to transportation networks, may be useful in a range of settings, from search and rescue to archaeology. This paper develops a method for general path planning intended to work across arbitrary distances and at the level of terrain detail afforded by aerial LiDAR scanning. Relevant information about terrain, trails, roads, and other infrastructure is encoded in a large directed graph. This basal graph is partitioned into strongly connected subgraphs such that the generalized diameter of each subgraphs is constrained by a set value, and with nominally as few subgraphs as possible. This is accomplished using the k-center algorithm adapted with heuristics suitable for large spatial graphs. A simplified graph results, with reduced (but known) position accuracy and complexity. Using a hierarchy of simplified graphs adapted to different length scales, and with careful selection of levels in the hierarchy based on geodesic distance, a shortest path search can be restricted to a small subset of the basal graph. The method is formulated using matrix-graph duality, suitable for linear algebra-oriented software. Extensive use is also made of public data, including LiDAR, as well as free and open software for geospatial data processing.

Highlights

  • The Detailed National Elevation Model, Norway’s biggest land surveying project, will by 2022 provide an airborne laser scanning (LiDAR) dataset covering the entire country with 2–5 measurements per m2 (Kartverket [Norwegian Mapping Authority], 2018)

  • Similar initiatives are found in, e.g., the UK, where the Environment Agency is carrying out LiDAR scanning of the entire country and publishing recorded data under an Open Government Licence via the data.gov.uk portal, the stated aim of which is transparency and innovation (Data.gov.uk, 2018)

  • We believe, render possible general path planning and mobility analysis covering any part of a land area, not just transportation networks; its wide range of applications including archeology (Herzog, 2014), public transit planning, physical exercise and hiking, forestry, and search and rescue operations (Ciesa et al, 2014)

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Summary

Introduction

The Detailed National Elevation Model, Norway’s biggest land surveying project, will by 2022 provide an airborne laser scanning (LiDAR) dataset covering the entire country with 2–5 measurements per m2 (Kartverket [Norwegian Mapping Authority], 2018). Similar initiatives are found in, e.g., the UK, where the Environment Agency is carrying out LiDAR scanning of the entire country and publishing recorded data under an Open Government Licence via the data.gov.uk portal, the stated aim of which is transparency and innovation (Data.gov.uk, 2018). Such data, we believe, render possible general path planning and mobility analysis covering any part of a land area, not just transportation networks; its wide range of applications including archeology (Herzog, 2014), public transit planning, physical exercise and hiking, forestry, and search and rescue operations (Ciesa et al, 2014). Land cover classification (e.g., tree species) using aerial LiDAR is currently an emerging field of research, and provides important information for mobility analysis

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