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The use of geospatial data to inform business decisions dates back to the 1960s. Using computers and computational geography, businesses were able to leverage some of the earliest geospatial data available to determine resourcing opportunities and the potential for geographic expansions. In 2022, this technology has dramatically evolved, enabling businesses to leverage AI to further analyze available geographic information systems (GIS) data to uncover trends and predictions otherwise unavailable. With the increase of data available, businesses are also using GIS to help inform their Environmental, Social, and Governance (ESG) initiatives.
Every business is deeply intertwined with environmental, social, and governance (ESG) matters. As the climate change crisis continues to worsen and both consumers and employees demand more transparency at every level, the importance of a business having strong ESG initiatives has never been more important. In fact, studies have already shown that companies with a strong ESG proposition are linked to higher value creation. While the US does not have mandatory ESG disclosures at the federal level, the SEC requires all public companies to disclose information that may be material to investors, including information on ESG-related risks. Consumers are also demanding more transparency from companies, as climate impact is top of mind for many people. While standardized reporting and metrics don’t exist in the US yet around ESG reporting, businesses are already taking the first step to accelerate these reporting requirements. When ESG initiatives are evaluated with the right data, companies can score themselves against energy use, usage and stewardship of natural resources, cybersecurity, conservation practices, and the treatment of employees.
This is where AI-supported geospatial data can be useful for many businesses reporting on their ESG initiatives. ESG reports informed by geospatial AI can help businesses validate and back into their initiative’s claims with reproducible, material proof. This additional level of insight, captured in real-time and rich with detail, can help investors correlate financial capital spending to a company’s social and natural capital. In short, this data will serve to help investors and consumers hold businesses accountable for their actions as they relate to global economic and environmental stability. Understanding how geospatial data can inform ESG reporting is one step in helping companies establish their initiatives and create clear plans of action to maintain transparency and accountability for these efforts.
The impact of geospatial AI on environmental reporting
Geospatial data supported by AI is the next evolution of data for businesses and organizations trying to truly understand the environmental impact of their commercialization. One example of this that we’ve seen at iMerit Technology comes from a project involving training AI algorithms to detect abandoned mines. While satellite imagery of these locations exists, it is nearly impossible and extremely time-consuming for researchers to scan thousands of images to identify abandoned mines while comparing them against historical data of what the land or region looked like before, during, and after mining operations. Oftentimes, researchers, government agencies, and companies may not even have access to historical data to drive this research, which leaves large gaps in factual reporting. This is where AI comes in. In this example, AI algorithms can be trained to comb through high volumes of satellite data and detect abandoned mines using high-quality GIS training data, and this information can then be used to evaluate the ongoing changes to the environment caused by the mines, even long after they have been out of use. This information can help governments, companies, and organizations make more informed decisions about future mining operations and measure the impact mines have on the environment when they are no longer functional. The global metals and mining industry contributes to approximately 8% of the global carbon footprint. When thinking about establishing proactive environmental initiatives, geospatial data can inform industries about the impact of resourcing. This information will ultimately drive companies to make more sustainable decisions that protect the environment.
Geospatial AI can hold companies socially accountable to their ESG initiatives
Geospatial data isn’t the first source of information that comes to mind for executives when determining how to measure and evaluate social impact. However, these datasets can help companies monitor their supply chain from beginning to end via satellite imagery that’s supported by AI analysis. Using this data, companies have the purview to see every stage of their supply chain cycle from resourcing to shipping, and can look even further to ensure that ethical labor practices are maintained. This level of precision enables organizations and companies to hold partners accountable and have viable data to do so.
By using AI algorithms, companies can get instant alerts on violations in their supply chain cycle and act quickly. This can be extremely critical in the case of illegal deforestation or human trafficking. In 2015, the Environmental Justice Foundation leveraged geospatial data to help inform their evidence of illegal human trafficking and enslavement of Thai fishermen. Other groups like the Humanitarian OpenStreetMap Team use geospatial data to work on multiple projects, including water and sanitation, gender equality, poverty elimination, disaster response, and numerous others. With the next iteration of GIS and AI, these organizations can use algorithms to detect these injustices at scale and get information quickly to assemble appropriate solutions.
Governance supported by standardized geospatial AI
Evaluating performance on ESG initiatives is no longer a nice to have for companies. As mentioned earlier, this reporting is becoming standard for the public and regulators. When it comes to governance factors, companies need to ensure that reports are backed by material data. In the case of geospatial data, reporting should include not only satellite imagery or GIS databases, but the practical action and company circumstances that lead to the conditions reported. With AI, companies can leverage algorithms to draw richer insights and conclusions from satellite imagery or other remote-sensing datasets to illustrate how company objectives directly impact the environment.
This may include reviewing geospatial data against customer satisfaction, production performance, retention, and capital spending. Geospatial data can also support the development of predicted scenarios that can help companies mitigate climate risks. Because geospatial is tangible and traceable data, companies are empowered to make concrete decisions from the insights obtained. This is especially helpful in the use of digital twins, a method used by companies to replicate a virtual model of their facilities. The additional information developed from AI-driven geospatial data allows them to strategize and plan through scenarios to prepare for worst and best case situations.
It’s not a matter of if ESG reporting will become reliant on geospatial AI, but rather a matter of time before all companies leverage this technology to inform their ESG reporting. The level of detail and insights provided from AI-powered datasets will position companies in the most proactive position possible to seriously address climate change. Geospatial information alone provides only some of the insights companies need to formulate stronger ESG initiatives. When adding AI to the mix, we can truly address the gaps within information and even uncover information that will impact climate and social change.
Mallory Dodd is a senior solutions architect at iMerit.
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Author: Mallory Dodd, iMerit