Spatial Analysis for Climate Change

Opportunity | Various applications of technology for the betterment of the planet

Combining my passion for climate and finance, I am motivated to use GIS technology and spatial data along with other data approaches (Disclosures, Asset Level Data, NLP) to provide grounded insight into sustainability-related risks/opportunities for companies and other Initiatives. These Include:

• Measuring environmental Impacts such as deforestation, land degradation or pollution, linked to the supply chain of companies, resource exploitation, and project expansion.
• Gauging the Impact of green projects / Initiatives such as renewable energy, forest restoration, plastic reduction effort, and regenerative farming.
• Assessing social issues such as human rights, contamination of natural resources by factories affecting livelihood and ethical sourcing linked to suppliers’ labour practices.
• Using NLP to scrape data points of companies on semantic databases that reflect on their ESG progress, metrics and Scope 3 emissions.

Approach | How we can implement the solution

Once the location of a green project or a company’s asset or their suppliers’ assets are geolocated (‘Asset Data’), these locations or areas will be compared or modelled with ‘Observational Data’ — datasets that might provide insights into variables such as a factory’s heat profile as a proxy for power usage, GHG emissions, or direct impacts to the natural world such as by considering overlays with protected areas, deforestation.

We’ll start by conducting a case study on a particular use case eg. ‘Studying the Impact of Green Projects’. Satellite data paired with reported data sets will enable precise yet broad monitoring of these field-level activities. We’ll collect the dataset of a green project eg. afforestation project and compare it using GIS software (ArcGIS) against vector layers: boundaries, protected areas, key areas and raster layers: human disturbance, forest gain, flood risk etc. Then we’ll run our analysis (Analysis pipeline given in detail in the image below) to study the impact of the green projects over time and generate reports in the form of observations and graphs that can be used to provide insight into progress, risks and improvement strategies. The insights thus created can then be exhibited on an online platform that aggregates them for everyone to understand the details regarding these green projects. It can also be supplemented with additional metrics scraped from online sources using natural language processing toolkits. Data acquired from GDELT (an Open-source project collecting all the data points created on the internet in a semantic web) can be extracted to learn the data points that were created on the internet (Social Media, Disclosures etc.) concerning these green projects such as controversies, news, reports etc.

Hence, a platform providing analysis of such projects and later on companies can be of immense value as discussed in the following paragraph ~ “Future”.

WWF’s Report on SpatialESG shows the process to use the data for analysis

Future of this Concept

Leveraging the knowledge base acquired after building this platform, we can further delve into specific use-cases in various domains such as agriculture, manufacturing or even extractive industries and provide the stakeholders with tailored insights like an early assessment of ESG impacts and risks, Intuitive visualisation of supply chains, scalable risk assessments to support reporting activities, cost-effective monitoring of compliance against internal policies, green initiatives can gain access to environmental markets and verifiable datasets that will allow for a transparent verification of environmental impacts whilst reducing risks of greenwashing.