WebGIS | GeoAI | EO

Role of Geospatial technology in gaining ESG insights

What is ESG?

ESG stands for Environmental (E), Social (S), and Governance (G). It refers to a set of criteria used to evaluate a company’s performance and societal impact beyond just financial metrics.

  • Environmental: This aspect focuses on how a company manages its environmental footprint, including its impact on climate change, resource use, pollution, and conservation efforts.
  • Social: This dimension examines how a company interacts with and impacts society, including its relationships with employees, customers, communities, and other stakeholders. It encompasses issues such as human rights, labour practices, diversity and inclusion, and community engagement.
  • Governance: Governance refers to the systems and processes by which a company is directed and controlled. It involves factors such as corporate governance practices, board diversity, executive compensation, transparency, and ethical business practices.


ESG criteria are used by investors, analysts, and other stakeholders to assess the sustainability and ethical impact of companies, and they are increasingly considered important indicators of long-term financial performance and risk management. Companies that perform well on ESG factors are often seen as more resilient, responsible, and attractive to investors and customers.

What is Geospatial ESG?

Geospatial ESG involves leveraging geospatial data to derive ESG insights for a particular commercial asset, company, portfolio, or geographical region. Through diverse geospatial methodologies, it is possible to evaluate assets against observational data, offering insights into potential environmental impacts, along with pertinent social and governance factors.

Environment specific approaches

The intricacy of natural systems and the varied nature of commercial activities have posed significant challenges in establishing clear metrics to define environmental impact and dependencies. While ground-based measurement of environmental variables is effective, it is labour-intensive, costly, and impractical on a large scale. These challenges have compounded, making it exceedingly difficult to assess environmental impact at a company scale or above. Previous efforts to address this issue have yielded numerous climate, nature, and biodiversity standards, methods, and tools. Despite these endeavours, widespread adoption of a single approach or standard remains elusive. Satellite remote sensing emerges as a promising solution, offering consistent and globally relevant ESG insights for millions of commercial assets.

Geospatial ESG uses the most comprehensive means we have for tracking global-scale changes to the environment — satellite imagery.

The growing emphasis on assessing environmental impacts and risks aligns with advancements in satellite technology and machine learning. However, the intricate nature of natural systems and the varied operations within commercial sectors present challenges in establishing precise metrics to define environmental impact and dependencies.

ESG analysts seek ready-to-use, frequent, and comparable insights. Satellite remote sensing, complemented by machine learning, offers consistent, independent, and repeatable environmental insights globally. This trend suggests a shift where entities’ disclosures of environmental impact will be less pivotal, as geospatial ESG methods, coupled with AI advancements, unravel data trails to offer robust insights regardless of the actor.

Geospatial ESG methods are scalable across both numbers of assets and sectors. It is relatively easy, with minimal technical know-how, to identify companies operating in highly sensitive biodiversity areas. Site-specific geospatial ESG methods and metrics, especially at the local level, are required to maximize insights. However, several constraints, such as temporal consistency, spatial resolution, accuracy, data interdependencies, and relevancy, arise when utilizing publicly available environmental observational datasets for geospatial ESG applications.

Geospatial ESG methodologies

In this article, we will discuss a few quantitative geospatial ESG methodologies,

  • Carbon Footprint Mapping: Utilizing geospatial data, companies can map and quantify their carbon emissions across their operations, supply chains, and product life cycles. This methodology helps identify emission hotspots, set reduction targets, and track progress towards carbon neutrality.
Increase in Carbon monoxide content in air after the Hawaiian wildfire in 2023
  • Habitat and Biodiversity Assessment: Geospatial analysis enables the assessment of habitat loss, fragmentation, and biodiversity hotspots. By quantifying changes in land cover and species distribution, companies can evaluate their impact on ecosystems and prioritize conservation efforts.
There was an observed increase in chlorophyll concentration from 2010 (left) to 2020 (right), along the coastline of Palghar district in Maharashtra.
  • Water Risk Mapping: Geospatial technology allows for the mapping of water scarcity, pollution, and stress levels in regions where companies operate. Quantitative assessments of water risk help companies understand their exposure to water-related challenges and implement water stewardship initiatives.
  • Supply Chain Transparency: Geospatial analysis can be used to map supply chains and assess the environmental and social risks associated with raw material sourcing, manufacturing, and transportation. Quantitative metrics such as distance travelled, carbon emissions, and deforestation rates provide insights into supply chain sustainability.
  • Land Use Change Monitoring: Geospatial data enables the monitoring of land use changes such as deforestation, urbanization, and agricultural expansion. Quantitative analysis helps companies assess their impact on land resources, biodiversity, and ecosystem services, informing land management strategies.
Extent of damage to vegetation caused by 2023 floods in the Bilaspur district of Himachal Pradesh in India
  • Climate Risk Assessment: Geospatial technology facilitates quantitative assessment of climate-related risks such as extreme weather events, sea-level rise, and temperature changes. Companies can use this methodology to quantify their exposure to climate risks and develop adaptation strategies.

These are a few of the quantitative geospatial ESG methodologies that provide companies with valuable insights into their environmental and social performance.  These methods allow them to identify risks, prioritize actions, and track progress towards sustainability goals.

How can GISKernel help in ESG reporting?

GISKernel offers specialized services and consulting to support Geospatial ESG reporting, aiding organizations in understanding and mitigating their environmental impact while maintaining profitability. Our expertise in harnessing the power of GIS enables us to provide comprehensive solutions tailored to your specific needs.

We utilize a range of advanced geospatial and remote sensing techniques to deliver accurate environmental monitoring services, including:

  • Assessment of environmental indicators such as vegetation health, land use, and land cover changes.
  • Mapping and monitoring of biodiversity hotspots and sensitive ecosystems.
  • Analysis of carbon sequestration potential
  • Assess soil health, erosion, and desertification to guide sustainable land management practices and soil conservation efforts.
  • Identifying areas prone to natural disasters
  • Analyze water bodies for indicators of pollution
  • Using thermal imagery to assess urban heat island effects
  • Monitoring changes in land use over time

By leveraging geospatial capabilities, we offer detailed insights into environmental dynamics, allowing you to make informed decisions about sustainable practices and ESG compliance.

Leave a Reply

Your email address will not be published. Required fields are marked *