A Complete Environmental Intelligence System for LiDAR-Based Vegetation Management in Power-Line Corridors

Abstract

This paper presents the first complete approach to achieving environmental intelligence support in the management of vegetation within electrical power transmission corridors. Contrary to the related studies that focused on the mapping of power lines, together with encroaching vegetation risk assessment, we realised predictive analytics with vegetation growth simulation. This was achieved by following the JDL/DFIG data fusion model for complementary feature extraction from Light Detection and Ranging (LiDAR) derived data products and auxiliary thematic maps that feed an ensemble regression model. The results indicate that improved vegetation growth prediction accuracy is obtained by segmenting training samples according to their contextual similarities that relate to their ecological niches. Furthermore, efficient situation assessment was then performed using a rasterised parametrically defined funnel-shaped volumetric filter. In this way, RMSE≈ 1 m was measured when considering tree growth simulation, while a 0.37 m error was estimated in encroaching vegetation detection, demonstrating significant improvements over the field observations.

CACTUS: Content-Aware Compression and Transmission Using Semantics for Automotive LiDAR Data

“…The idea of sharing LiDAR PC data and processing them in a collaborative and distributed fashion has been recently investigated in many applications ranging from cultural and natural preservation [ 2 , 29 , 30 ] to automotive applications [ 31 , 32 ].…”

“…Sensing technologies have been recently boosted by the availability of versatile 3D acquisition devices that have proved to be capable of generating accurate models of the surrounding scene at a reasonable cost and in a limited time. Within these scenarios, LiDAR technology has played a leading role considering its widespread application in several fields including (but not limited to) land sensing and reconstruction, robotics, cultural heritage, and monitoring [ 1 , 2 , 3 ]. With respect to automotive applications, LiDAR PCs allow a real-time 3D modeling and semantic understanding of the environment [ 4 ] which enable smart applications such as autonomous driving, traffic monitoring, and path planning, to mention some of them.…”

Literature Review of Unmanned Aerial Systems and LIDAR with Application to Distribution Utility Vegetation Management

“…While shortening pruning cycles, and therefore decreasing the time frame of the risk assessment, has been found to both decrease the number of interruptions and decrease the time and cost to prune individual trees, UVM. Despite this, there are growing related fields of research in UAS-based LIDAR for forest inventories (Jaakkola et al 2010;Wallace et al 2012;Wallace et al 2014;Wallace et al 2016;Staley 2022) and airborne LIDAR for electrical transmission-level system monitoring (Ituen et al 2008;Ko et al 2012;Kim and Sohn 2013;Chen et al 2018;Siranec et al 2021;Mongus et al 2021). Walker and Dahle (2022) noted that the application of remote sensing and UAS technology could advance the UVM industry in terms of managing tree risk, especially for off-ROW trees.…”

Geo-Spatial Context Provision for Digital Twin Generation

“…[15]). Depending on the intended DT use, the produced geo-spatial context needs to be potentially integrated with other information to serve a specific purpose (see the DT created in [16], which incorporates data from different auxiliary sources). In the context of CPS, the produced geo-spatial data needs to be linked with other information, e.g., be embedded with other sensor data, since one of the core added value propositions of DTs lies in making use of linked information [10].…”