asset risk report creation across multiple data layers

Introducing an Upgraded Spottitt MF 2.0: What’s New? Part 2.

We continue to introduce the major developments of the upgraded Spottitt Metrics Factory platform.

In the first part of this article, we presented new data sources, such as climate and weather datasets for monitoring and assessing the impact of climate patterns on asset resiliency. These datasets also enable more complex assessments of vegetation risks, such as fall-in and overgrowth hazards.

Additionally, we introduced the provision of digital elevation data, including slope and aspect characteristics, as well as the ability to build 3D models of individual conductors and their sag, and to calculate pylon and conductor vertical clearance distances using supplementary asset data.

In today’s second part of the article, we are introducing a new, more sophisticated yet streamlined approach to reporting.

Creating Reports Across Multiple Data Layer Types: A New Level of Flexibility

The upgraded Spottitt platform now empowers users to customize reports in a single step, using multiple data layer types, filters, and display preferences.

Layer Types

Layer types refer to the specific input data leveraged for a monitoring use case.

Depending on the source data purchased through Spottitt MF, the available layer types might include but are not limited to:

  • Optical Vegetation Classes: Define the specific type of vegetation you are interested in – there are seven options to choose from.
  • Optical Man Made Classes: Focus on buildings or man made surfaces, depending on your needs. 
  • Wind Classes: Access data on wind speeds and wind gusts at heights of either 10m or 100m above ground.
  • Precipitation Classes: Access data on precipitation amounts, rates and types.
  • Temperature Classes: Includes data on soil, sea and land surface temperatures.
  • SAR (Synthetic Aperture Radar) Land & Asset Motion Classes: Identify whether your assets are at risk due to subsidence or uplift.
  • Digital Elevation Data Classes: Provides elevation, slope and aspect data for terrain and infrastructure analysis.

Variety of Filters

Filters adapt to the chosen layer type, enabling users to match their current monitoring parameters and fine-tune their output reports to focus on the most critical risks. This flexibility allows Spottitt platform users to replicate—and go beyond—their most complex monitoring guidelines.

For example, users can filter for deciduous trees taller than 10 meters that are within 5 meters horizontal distance of power lines, have a vegetation health index (NDVI) below 0.28, and have been exposed to winds exceeding 15 m/s for more than 100 hours in 2019-2023.

The resulting report will allow a user to understand high-risk areas for tree fall in, helping prioritize vegetation clearance efforts.

Customizable Reports

Users have the flexibility to customise how their output analysis is displayed by showing or hiding various columns of data, rearranging the column sequence, ordering rows from largest to smallest or vice versa, and applying filters to refine outputs. Users can build reports containing as much or as little data as they need from the following groups of output metrics:

Asset Data Metrics: Includes information such as asset name, type, location, and more.

Raw and Calculated Metrics Associated with Each of Your Chosen Data Layers, for instance:

  • Number and location of identified risks
  • Risk area and estimated volume – handy for estimating vegetation cut volumes.
  • Length of asset impacted by the defined risk, both in percentage and absolute terms.
  • Minimum, maximum, and average hours of climate risk exposure.

Spottitt MF report creation wizard to select column visibility and order.

This is the resulting report shown in table view – only one asset with tall coniferous trees in poor health located near the line.

The good news is that no heavy winds were experienced by these assets from 2019 to 2023, inclusive.

Comparative View

This view enables platform users to compare and analyze changes in the same risks and metrics between one monitoring pass and another monitoring pass. It helps identify whether the % of the monitored corridor at risk is increasing/decreasing/remains stable.

If vegetation encroachment is the risk in question, a comparative view will estimate vegetation growth rates per asset section, or be used to audit vegetation management work completed by subcontractors.

Satellite-derived EO data, paired with automated AI-driven algorithms is an important addition to the toolbox of remotely sensed and field survey data and analytics available to asset managers looking to increase asset monitoring quality and frequency for infrastructure spread across large areas. It enables rapid, accurate, and safe risk detection and analysis, helping organizations take timely and informed actions. 

With the introduction of new data types, including climate variables and digital elevation models, regular algorithm retraining and upgrades for improved accuracy and reliability, and enhanced reporting capabilities, our upgraded Spottitt MF 2.0 platform sets a new standard for remote asset monitoring, empowering users to ensure their critical infrastructure remains safe and resilient.

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