17 items found for ""
- Satellite Data Analysis Maximizes Mid-Cycle Inspection Efficiency
Utility asset and vegetation inspection workflows are often conducted on a multi-year cyclical basis using several methods to assess the conditions of assets and vegetation within a service territory. One method is to walk the entire system every few years, which gains the most granular level of spatial detail, but the data is subject to degradation since the temporal frequency is low. That is to say, the asset health and vegetation presence at the starting point is likely to change significantly from the time it is first inspected to the next walking inspection several years later. Drive-by inspections are done on a more frequent basis where vehicle access is possible. This increases temporal inspection frequency, but the level of detail is not as precise since the assets and vegetation are looked at from farther away. Aerial fly-bys can cover the entire system more often, but again spatial resolution is lost for the same reason as drive-by inspections. To compensate for this loss, lidar inspections and high-resolution imagery provide more granular spatial accuracy, but their temporal frequency is still reduced due to the high costs of these types of data gathering. This begs the question: Is there a way to maximize the efficiency of all these types of inspections with continuous monitoring of an entire service territory or wildland-urban interface (WUI)? At Raster Report, we believe there is through our satellite-based analysis. Our satellite data does not focus on high resolution images of poles and structures, or of vegetation encroachment into a right-of-way. Instead, we conduct a weekly to monthly rolling analysis of vegetation conditions in an entire utility service territory, which identifies specific areas that are more susceptible to combustion. With pole data for a transmission or rural distribution system, we can show the exact poles/structures that fall within the higher fire danger areas in an easy-to-read map. From there, utilities can dispatch ground crews to those structures and rights-of-way to inspect the conditions of the assets and vegetation in the vicinity. If dispatching crews for mid-cycle site inspections is not feasible, the option to use high spatial resolution data is still there, except the data can be focused on specific areas instead of the entire system, lowering data acquisition costs. Our process makes mid-cycle inspections more efficient since they are driven by temporally frequent data that identifies specific assets within increased fire danger areas. There is no need to implement or integrate costly inspection management, asset management or vegetation management systems that requires considerable training and organizational change management, just a map that shows where increased fire danger areas are located. On the same principle, our analysis can assist fire managers with monitoring of fire breaks around municipalities as well WUI areas. By identifying specific places of increased combustion probability, crews can be sent to thin out vegetation, reducing the potential rate of spread and severity of a fire if it occurs within or near the WUI. Again, a simple map is provided on a regular basis that shows managers and crews where increased combustion probability is identified. There is no additional training necessary or adoption of software, hardware, or any integrations with additional systems. This makes inspection processes more efficient on Day 1, and not months down the road after debugging systems and teaching team members how to use those systems. More efficient inspection processes provide two obvious advantages for utilities and managers of the wildland-urban interface: Vegetation identified in high fire dangers can be trimmed, reducing the chances of ignition in that area as well as providing a potential fire break if a fire that originates elsewhere spreads to that area. Assets that may have known failure conditions or unknown conditions can be repaired or replaced, strongly reducing the chances of utility caused fires. To find out how Raster Report can help you and your inspection processes, please contact us for a free demo. #wildland-urbaninterface #assetdeterioration #seasonalvariability #mid-cycleinspections #workflowefficiency
- The Fire Triangle - Wildland fire and its interaction with utilities
This is a concept well known to many folks, but it’s important to understand the fundamentals of the components of wildland fire and its interaction with the wildland-urban interface (WUI), including utility rights-of-way and natural areas surrounding rural municipalities. For combustion to happen three contributors are necessary – fuel, heat and oxygen. The oxygen part is ever present on modern day Earth, so that leg of the triangle is self-explanatory. The fuel leg consists of anything that can burn including vegetation and, unfortunately, homes and other buildings as well as utility structures (particularly wood structures). Oxygen and fuel are constantly present, but combustion cannot occur without a heat source. In a fire caused by nature, the heat source is typically a lightning strike, but only 10 to 20% of wildland fires are caused by nature. Humans account for the other 80-90% of wildland fire ignitions, and those causes are endless. For a more detailed discussion on protecting rights-of-way and wildland-urban interfaces, please reach out to us at firstname.lastname@example.org.
- Lidar, High Resolution Photos and Multispectral Imagery for Utilities
There are many remote sensing approaches to vegetation management, including high-resolution photographs and lidar data. Let’s look at some attributes and advantages of each of these methods and explore how to put them to best use! High Spatial Resolution Photography This is probably the most well-known form of remote sensing for many folks. A satellite, aircraft or drone flies a utility line and takes very high-resolution imagery of assets and vegetation. The level of spatial detail is impressive, and the beauty of the photograph is almost artistic. These images are useful in vegetation management because they can identify tree encroachment into a right-of-way and tree height can be calculated with a scalable reference. The level of detail, combined with knowledge of local vegetation species, can also be used to execute supervised classifications for land cover analysis. Lidar – Light Detection and Ranging We’ve all heard of Radar (Radio Detection and Ranging), and lidar has also become a commonly heard term these days. Lidar and radar are both active sensors, meaning they generate a signal that bounces off a target, returns to the scanner, and produces an image. Lidar uses laser pulses in the ultraviolet, visible and near infrared bands of the electromagnetic spectrum to generate point clouds of its targets, which creates high-resolution 3D images. This application is beneficial for utilities because it can create granular detailed representations of assets in the field like poles, structures and substations, and it can show tree height and canopy density of vegetation that may be encroaching into a utility right of way. If ground penetrating radar is used, underground utilities can also be detected. How Can These Methods be Applied Most Efficiently? Both lidar and High-Resolution Imagery provide near-granular level optical detail of vegetation encroachment in utility rights-of-way. While it is important to identify a specific tree growing in a right-of-way, that does not address vegetation management comprehensively. Utilities can have hundreds to thousands of miles of transmission and rural distribution lines, and lidar and high-resolution imagery costs add up quickly, depending on the size of the target area and frequency of data acquisition. What if there are 10 trees identified as encroachers in a right-of-way? Or 100 trees? Or 1,000 trees in rights of way, spread out over hundreds of miles? How do you prioritize their trimming or removal? What if the service territory land cover is mostly grassland, which ignites much more easily than trees? Raster Report uses satellite data for analysis on large spatial scales to identify areas of increased combustion probability, aka high fire danger areas. To supplement that, we identify specific assets within these fire danger areas to prioritize inspections based on real data, and not ad-hoc inspections. This deliverable then gives utilities the options to make use of lidar or high spatial resolution imagery, or to deploy ground crews to inspect the identified areas of fire danger. By making vegetation management and asset inspection processes more streamlined, utilities are then able to reduce O&M costs, which keeps customers safer and happier! To see how the Raster Report team can help you, please reach out to us anytime! #remotesensing #wildfiremitigation #utilities #forests #satellites #vegetationmanagement #assetmanagement #ai #artificialintelligence #drones
- Utility wildland fire mitigation solutions | Lowering your enterprise expenditures | Raster Report
Protecting lives, assets and resources with geospatial analytics Request Demo > No upgrades No integrations No new training Saving you O&M costs from Day one Strengthening your grid reliability We provide a robust supplemental line of defense for your electrical transmission and distribution systems that reinforces safe and reliable energy delivery. Identifying precise locations of increased fire danger for electric utilities Providing weekly updated results for prioritized right of way inspections and T&D circuit patrols. Learn more > An easy to read map deliverable means there is no need to implement new software or reconfigure your inspection workflows , which minimizes the growing pains of organizational change management. Making your energy delivery safer Our services focus on early and precise detection of increased fire danger areas , providing you an opportunity to prioritize your vegetation and asset inspections. Lowering your enterprise expenditures Proven geospatial analytics, combined with our extensive wildland fire science and utility experience, enable your asset and vegetation inspection cycles to be more cost effective. See how Raster Report can work for you Raster Report identifies precise areas of increased fire danger earlier than traditional methods, giving you more time to take mitigative action. To see how Raster Report can help your organization, contact us for an in-person or remote demonstration of our services. Request Demo > For industry insights check out our blog >
- About | Raster Report | Identifying exact locations of pre-wildfire conditions
Meet Raster Report WOMAN OWNED BUSINESS Our Vision The primary objective at Raster Report is to save lives, property and resources by identifying specific areas of higher combustion probability as far in advance as possible before an ignition event. By merging remote sensing, wildland fire ecology and utility experience with the latest analytics processes, we deliver an additional line of defense to your Right-of Ways and Assets. By identifying areas of potential higher combustion probability, providing you advanced warning to take mitigative action. We understand that not all fires are preventable, and some fires are natural and even necessary, but we aim to mitigate disastrous and unnecessary effects that can happen from fire. Our Story Raster Report was built from the necessity to take a more proactive approach to wildland fire mitigation. As wildland fire frequency and severity continue to increase, more lives are at stake as well as assets and resources. Our intricate understanding of fire ecology and its variables at local and regional scales, combined with GIS, Remote Sensing, Gas and Electric Utility experience, provide the optimal combination of industry knowledge, technical aptitude and vision to help utilities adapt immediately, while also preparing for the future. Our Technology High temporal frequency data from the constellation of Earth facing sensors is processed and analyzed to model areas of potential fire danger. Human insight, combined with artificial intelligence and machine learning, provides the most comprehensive way to protect the Wildland Urban Interface (WUI). Learn more For industry insights check out our blog
- Satellite Informed Vegetation Management | Raster Report
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