FAQs

Founded in 2010, RS Metrics captures data from satellite and aerial imagery to provide insights, trends and market signals. Our patented AI platform uses state-of-the-art computer vision and machine learning to get accurate, near real-time information to you.

Data is purchased and generated through stable, long-term contracts with satellite and aerial imagery suppliers operating under the laws and guidelines of the US Commercial Remote Sensing Policy.

MetalSignals coverage includes approximately 500 metal smelters, electrolysis plants, storage sites, ports, and terminals for aluminum, copper, zinc, iron ore, and steel rebar. This year we are adding coverage of bauxite, alumina, coal, and more steel coverage including hot rolled coil (HRC), and cold rolled coil (CRC).

We currently cover base metals: aluminum, copper, iron ore, steel, and zinc. We will be adding more metals shortly into our coverage.

RS Metrics tracks all regions globally and breaks out the data by individual location, country, and continent.

Locations are added based on:

  1. Information from our partner PRAs (Price Reporting Agencies) such as Metal Bulletin and Platts; consulting firms; and indices
  2. Client demand
  3. Market research

There are no restrictions globally for satellite imagery other than a government mandated minimum resolution of 35 centimeters. This excludes personal identifiers such as faces or license plates from imagery.

  • Resolution: satellites are 35cm-1m, airplanes are 10-30cm, drones are 5cm or better
  • Flexibility: drone and aerial images can be taken any time of day while most satellites can only do between 11am-1:30pm
  • Legal Restrictions:  drones can only be flown over land with permission from the property owner
  • Reach: satellites can image anywhere while drones and airplanes are not allowed in many countries, such as China

More information can be found here: https://insights.rsmetrics.wpengine.com/choosing-satellite-or-aerial-imagery

Data observations are provided in UTC time and converted to local time.

  • Metal stockpile area (m2)
  • Concentrates stockpile area (m2)
  • Copper anodes area (m2)
  • Copper cathodes area (m2)
  • Semi-trailers
  • Cars
  • Dump trucks / tippers
  • Collection date time
  • Location Type
  • Metal Type

  • Price and inventory forecasting and hedging: Forecast LME and CME price direction 1, 2, and 3 months out with 70-80% accuracy and LME and CME inventory direction 1, 2, and 3 months out with over 80% accuracy.
  • Macro forecasting and analysis: Forecast commodity-cycle macro impacts based on under or oversupply of base metals globally or by region or country.
  • Equity forecasting and analysis: Forecast stock price direction for equities, FX, and indices with metals-exposure (e.g. AA, GLEN, RIO, COPX).
  • Market analysis: See real time inventory production and storage trends for approximately 400 global base metal smelters and storage sites, and iron ore terminals. Adding locations for Steel, Bauxite, and Alumina.
  • Sales, business and competitive intelligence: See who is increasing or decreasing their inventory and where. See if customers are increasing or decreasing production at key factories.

A: ESGSignals® currently covers Scope 1 direct emissions. Below are the GHG emissions currently under coverage and historical data goes back to 2017. We are also working with satellite data providers like MethaneSAT, GHGSat, and JAXA to add methane and CO2 to our coverage. Current frequency is biweekly.

Carbon monoxide (CO) is a major atmospheric pollutant. Main sources of CO are combustion of fossil fuels, and biomass burning.

Nitrogen dioxide (NO2) enters the atmosphere because of fossil fuel combustion and biomass burning, as well as natural processes such as microbiological processes in soils, wildfires, and lightning.

Sulphur dioxide (SO2) is emitted by the burning of fossil fuels — coal, oil, and diesel — or other materials that contain sulfur. Sources include power plants, metals processing, and smelting facilities, and vehicles.

The Aerosol Index (AI) is for tracking the evolution of episodic aerosol plumes from dust outbreaks, volcanic ash, and biomass burning.



ESGSignals® platform is not limited to the metals industry and it also covers other sectors such as energy, utilities, and industrials. The platform also includes the metrics listed below at the asset-level and, in addition, it can track activity and inventory details at the locations where gypsum and sand is either sourced or stored.

 

For a complete list of metrics we cover refer to this ​data description document and our environmental metrics for S​FDR reporting​.

 

Scope 1 GHG emissions are measured and reported in CO2 equivalent

  • Carbon Monoxide (CO)
  • Nitrogen Dioxide (NO2)
  • Sulfur Dioxide (SO2)
  • Methane (CH4)
  • Aerosol Index
Land usage and proximity measured in square meters
  • Land Usage
  • Land cover type classification
  • Asset proximity to IUCN areas
  • Asset proximity to biodiversity hotspots
Water stress
  • Water stress score based on meteorological variables, aqueduct and surface water datasets
  • Basin water risk
  • Proximity to the nearest water stress location if applicable

All the environmental impact metrics (emissions, land usage, and water stress) are linked to the SASB materiality map (GHG emissions, Air quality, water management and ecological impacts) while the climate physical risks we cover (wildfire, hurricane, flood, and sea level rise) are aligned with TCFD.

Weekly, monthly, and annual basis depending on the resolution and metric covered. For example, emissions are updated weekly, and land-usage is updated on an annual basis.

Asset managers are using ESGSignals® datasets for identifying the best-in-class companies within a sector and systematic groups are integrating asset-level datasets to improve investment outcomes through deeper insights at the asset-level.
 
In addition, asset managers focusing on thematic investments are using ESGSignals® datasets as a screening tool in addition to other third-part datasets. An example of this is a Dutch asset management firm focusing on water stress. Using ESGSignals® water stress datasets for engagement with companies and for top-down analysis of their portfolio.
 
Overall users can use our data sets to create models and run their own analyses.  If needed, we also provide data-science consulting services. and a data-science starter package with 10, 50 or 100 hours of data science support.

ESGSignals®  platform’s bottom-up approach is based on monitoring and measuring environmental impact and climate physical risk metrics at the asset-level and rolling it up to a company/country/region level. The platform is essential in evaluating the risks faced by various facilities within the supply chain as we have noticed in our metals & mining case study. Below are some of the risks uncovered using the platform:
 
Elevated water stress levels observed at assets owned by Rio Tinto. The majority of these locations are based in Australia.
 
  • A higher proportion of locations owned by Rio Tinto are closer to tree cover (forest, herbaceous/grassland) which poses a risk to biodiversity. 
  • Alcoa Group’s aluminum operations average land usage is 768 sq meters lower than peers and the industry average of 1310 sq meters despite being one of the largest producers of aluminum, resulting in reduced environmental impact. 
  • Rio Tinto’s operating assets are closer to biodiversity hotspots significantly increasing impact on environment and exposure to reputation and operational risks – a recent incident involving destruction of aboriginal sites resulted in the CEO stepping down (Rio Tinto CEO and other top executives to step down after Australia cave blast review by CNBC).
 
Alcoa’s air quality score which is based on carbon monoxide and nitrogen dioxide is slightly higher compared to competitors.

An example of the value we bring to executives of country-wide networks of companies would be our supply chain and Custom Event Driven Monitoring (CEDM) and GREAT (Global Real-Time Monitoring and Alert System) that are both described in detail with supporting examples and real use cases in our Solutions page. These both offer bespoke solutions for executives looking for real-time alerts using satellite data in cases of accidents and environmental disasters to track spread of damage and influence on the environment around. See some use cases below that help illustrate the advantage that these solutions provide:
 

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