In the ever-evolving landscape of Utility Vegetation Management (UVM), it should not be about choosing between LiDAR or satellite imagery.
The key is figuring out how to combine both, as these technologies are most potent when working in tandem. Here we further examine the unique strengths of each, and explore five strategic approaches to leverage this powerful synergy for a more robust utility vegetation management program.
5 Reasons to Combining Satellite Data and LiDAR for UVM
1. Enhance the accuracy of vegetation risk assessments
Satellite imagery excels in deriving vegetation location and mapping the surface of vegetation, known as a Digital Surface Model (DSM), through a process called photogrammetry. Despite this, certain limitations exist.
Currently, it does not allow for the detection of conductor locations and determining their 3D position from space. Additionally, optical satellite techniques face challenges in penetrating through vegetation to reveal details of the ground surface.
There are some satellite techniques, such as the use of radar, that can be utilized to create digital terrain models (DTMs) of the ground surface. However, these methods yield relatively lower resolution compared to aerial LiDAR.
As many utility companies employ a LiDAR program for their high-voltage assets, particularly NERC-rated transmission lines, these programs can be leveraged by using the high-resolution DTMs generated by LiDAR to enhance the accuracy of satellite-derived vegetation surface models. It doesn’t matter that the DTM may be several years old, as typically, the ground surface doesn’t change on a high cadence.
Moreover, utilities deploying LiDAR programs to generate digital twins of their network in the form of engineering models accurately depict conductor positions under maximum rated temperature and sway.
This calculated conductor position can be used to provide a basis on which clearances to satellite-derived vegetation location can be computed.
Considering that only 5% of a high voltage network undergoes facility changes each year (e.g., rerating, reconductoring, and rerouting), even fairly old digital twins like PLS-CADD models can be used to seed satellite-based analyses. The satellite-based analysis can therefore be thought of as an environmental twin to complement the digital twin.
2. Close the awareness gap
Traditional methods like LiDAR and ground patrols are typically conducted periodically on cycles due to the associated costs. Although these approaches provide high-fidelity analyses for the period in which the data was captured, they often leave an awareness gap that grows over time until the next inspection cycle is undertaken.
Cycle-busters, such as fast-growing species within the RoW, can and do occur mid-cycle, posing a threat to the infrastructure. With the changing weather patterns associated with climate change and the dynamic nature of vegetation, the likelihood of such unforeseen events is high. This leaves utilities vulnerable, further underscoring the limitations of a cycle-based approach.
Satellite techniques present a solution by providing frequent and consistent monitoring of assets, especially critical in the years when more expensive inspection methods are not deployed. This continuous surveillance helps mitigate the risk of cycle-busting events, ensuring a more comprehensive and up-to-date understanding of vegetation conditions surrounding utility assets.
3. Make off-RoW trees actionable
Electric transmission owners operating assets energized at 200 kV and above, or those that form part of an Interconnection Reliability Operating Limit (IROL) or a Major Western Electricity Coordinating Council (WECC) Transfer Path, are mandated to adhere to the vegetation management reliability standards outlined in NERC FAC-003-4.
Compliance is critical as it imposes penalties exceeding USD$1 million per violation per day on operators failing to maintain the Minimum Vegetation Clearance Distance (MVCD) without a sustained outage. The regulation requires that the movement of conductors under its Rating and all Rated Electrical Operating Conditions is taken into consideration.
The industry has adopted an aerial LiDAR and PLS-CADD workflow to accurately model high-voltage (HV) lines at maximum sag and sway, which aids in computing both grow-ins (Category 1a and 1b) and fall-ins, i.e., trees that are tall enough to fall into the conductor (Category 2a, 2b, and 3). The implementation of the technology and the enforcement of the FAC-003 regulation have significantly reduced outages (Fig. 2), such as the 2003 Northeast blackout.
However, the situation is different for fall-ins, as Category 3 outages remain persistently high, and in fact, show an upward trend (Fig. 3).
Addressing Category 2 and Category 3 risks remains challenging due to the nature of these threats. While LiDAR has the capability to flag thousands of hazardous trees along power lines in rural areas, the data is often not actionable.
This is due to the fact that utilities typically lack the necessary resources, public support, and/or rights beyond traditional transmission RoWs to remove such trees. Moreover, Category 3 outages mostly stem from Major Event Days such as weather events (Miller, 2020).
Consequently, there have been various efforts to make the threat more actionable, e.g., LiDAR vendors have used Near Infrared (NIR) imaging to create Normalized Difference Vegetation Index (NDVI) maps, and in some cases, HyperSpectral Imaging (HSI) and extensive ground control have been used to identify species.
However, the limited temporal resolution of LiDAR and associated imagery renders it ineffective in responding to dynamic changes in vegetation vitality and weather, with T&D operators obtaining species and health information at best annually and at high costs.
Satellite-based monitoring has emerged as a valuable complement to LiDAR, especially in monitoring transmission lines after spring flush and throughout growing seasons to detect fast-growing 'cycle busters' posing Category 1 threats.
Furthermore, it enables tree vitality to be tracked historically, and going forward, on a routine basis, allowing for the identification of warning signs associated with hazard trees, thus mitigating Category 2 and Category 3 risks. In essence, satellite technology overcomes the limitations of aerial LiDAR, providing an opportunity to prevent seemingly 'unpreventable' outages and enhance overall system reliability.
4. Prevent wildfires
In wildfire-prone regions, the synergy between satellite imagery and LiDAR proves particularly advantageous for utility companies. The combination of these two technologies offers a comprehensive approach to wildfire risk management.
Satellite imagery plays a crucial role in detecting early signs of dead or deteriorating vegetation that might serve as fuel for future wildfires. This early identification enables utilities to take preventive measures, mitigating potential fire hazards before they escalate. Simultaneously, LiDAR's precision comes into play by accurately assessing the proximity of identified vegetation to power lines.
By employing this integrated approach, utilities can significantly reduce the likelihood of wildfires caused by contact between vegetation and power lines.
Furthermore, the method minimizes the necessity for extensive manual inspections, resulting in considerable time and resource savings. Ultimately, this powerful combination enables power utility companies to not only enhance their wildfire prevention measures but also streamline their vegetation management strategies, contributing to a more efficient and resilient power grid.
5. Deploy Integrated Vegetation Management
In the United States, Europe, and various other locations, there is a growing trend towards employing biological controls to manage RoWs.
Simply put, these initiatives promote the growth of compatible species—those that do not reach levels that would interfere with power lines—while simultaneously removing incompatible species, such as fast-growing varieties or those that would interfere with the conductor's height.
Utilities adopting Integrated Vegetation Management (IVM) and Ecological Vegetation Management (EVM) techniques stand to gain numerous benefits, including a marked reduction in cost per hectare, as depicted in Figure 5.
This approach also positively contributes to Environmental, Social, and Governance (ESG) goals in a number of ways, for instance, initiatives such as carbon sequestration along the Right-of-Way, the use of RoWs as pollinator superhighways, and the creation of green spaces for use by the public.
The successful deployment of IVM/EVM methods hinges on managing clearances tightly compared to more drastic clear-cutting techniques. This necessitates the use of inspection technologies like satellites that can be performed on a high cadence, alongside benchmarking of species information, which can be derived at scale through satellite-based analyses.
Satellite-derived species analysis can then be supplemented by ground-level assessments, providing a robust starting point for creating a detailed inventory of vegetation in the RoWs. LiDAR also plays a crucial role by enabling precise 3D mapping of vegetation structures, offering utilities unparalleled insights into the composition, density, and health of vegetation surrounding power lines and other infrastructure.
With a comprehensive view of the state of vegetation provided by this integrated approach, utility companies can proactively plan targeted vegetation management strategies, minimizing the need for excessive and indiscriminate trimming or removal of vegetation.
In Part 3, we will delve into a compelling case study showcasing the practical application of merging LiDAR and satellite data to enhance vegetation risk assessments for an Australian utility company. We will also explore the benefits of synergizing these advanced technologies for a more robust Utility Vegetation Management (UVM) program.
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