Forests play a critical role in conserving our environment.
They help preserve the ecosystem and biodiversity while also sequestering carbon dioxide (CO2) from the atmosphere. Deforestation and forest degradation releases carbon dioxide and other greenhouse gases into the atmosphere. It also affects the livelihoods of forest communities.
Sustainable forest management is therefore essential to improve the health of our environment. Such practices can also give rise to additional sources of income for forest communities. The increased amount of carbon their forests sequester can be traded as carbon credits on several carbon trading platforms active across the globe. One carbon credit is equal to one ton of CO2 emission.
As part of global net-zero initiatives, rules are being set to control the amount of CO2 corporates can release. If corporate operations are emitting more than their permitted amount of CO2, they need to offset the "extra" CO2 emission by “buying” carbon credits from projects that reduce/remove CO2 or other greenhouse gas emissions. Forest communities following sustainable forest management practices can potentially calculate the amount of CO2 their increasing forests are sequestering and "sell" that carbon stock as carbon credits to corporates.
Trading in carbon credits gives forest communities an opportunity to acquire an additional source of revenue and gives them an incentive to protect the forest.
Such an arrangement allows nature and forest communities to thrive while systematically controlling the amount of carbon emissions. However, calculating forest carbon stock is not easy. Moreover, such calculations require to pass through independent audits before registering them as carbon credits on trading platforms.
Despite remarkable advances in satellites and machine learning, credit calculations today still rely on costly, labor-intensive methods.
Presently, forest carbon stock assessments mostly rely on expensive and labor-intensive techniques where field managers manually measure trees in a forest, using a sampling method. While advancements in technology have paved the way for the use of satellite data, the accuracy of carbon measurement remains low.
A forest carbon credit issuance involves monitoring, reporting, and having these calculations verified by independent auditors – a process referred to as MRV (monitoring, reporting, and verification). All of this is tedious but critical.
High-quality, transparent, and scalable carbon stock reporting and verification requires digitization and automation to capture forest data points such as a tree’s diameter at breast height or DBH, canopy coverage etc.
A technology platform to track and measure carbon sequestration can bring efficiency and accuracy in issuing carbon credits to forest communities.
Well-conceived digital tools can precisely measure the amount of carbon stored in forests, making the monitoring process easier and more precise. This enables forest communities to engage in carbon credit trading, encouraging them to preserve their forests for environmental benefits.
A pilot program between TCS and the Indian School of Business (ISB) attempts to measure carbon stock using modern technologies, including artificial intelligence/machine learning. The pilot run in a district called Simdega, in the eastern Indian state of Jharkhand, seeks to empower forest communities by helping them measure and trade forest carbon stock.
TCS has been developing digital platforms for forestry, agriculture, and related areas through its digital food initiative – a dedicated group in TCS Research.
As part of the group, TCS has developed a unique ‘sky-and-earth’ convergence approach that leverages sky data sets such as weather and satellite imagery as well as ground data, comprising of tree images, foliage specifications etc. The TCS pilot in collaboration with ISB leverages this ‘sky-and earth’ convergence approach.
The TCS designed platform will use the ‘sky-and-earth’ convergence approach—the use of datasets from satellites above and analytics on the ground in terms of soil composition and tree cover—to automate carbon credit calculations and make carbon assessment more efficient and standardized.
To collect sample data for the pilot, TCS developed a mobile phone application to capture on-ground data (for example, to measure tree dimensions). The data collection was done by local students recruited by ISB. A key objective of the pilot is to indicate to forest communities and other stakeholders the total carbon stock of the forests in the region.
The larger goal is to use this ‘sky-and-earth’ convergence approach to automate carbon stock measurement and to make the assessment more efficient and standardized—free of data anomalies, discrepancies, and duplication.
Digitization to help accurately measure carbon sequestration and assess overall forest health.
The pilot intends to develop a comprehensive platform to measure not just forest carbon stock but also other aspects of the forest ecosystem, like forest health, its produce, and biodiversity. This will enable forest communities to help better manage their forest ecosystem and tackle climate change.
The larger platform will also help industries associated with forestry to identify, quantify, assess quality, and monetize forest products, such as timber, wood pulp, fruits, and honey, and assess overall forest health.