Forests are vital for our planet. They help fight climate change by absorbing a lot of carbon dioxide from the air, acting as major carbon sinks. They store large amounts of carbon in biomass and soil, estimated to absorb about 30% of human-caused CO2 emissions annually worldwide.
However, scientists and project managers must track forest health. They need to know how much carbon forests store. This helps ensure that efforts to protect or grow forests are effective. This is called measuring, monitoring, reporting, and verifying forest carbon, often shortened to MMRV.
Eyes in the Sky: How Remote Sensing Sees Forests Differently
Measuring carbon in forests is tricky and expensive. Usually, people go out into the forest and measure trees by hand, which takes a lot of time and effort. It’s hard to do this over large areas, especially in dense or remote forests.
This is where remote sensing comes in.
Remote sensing is a way to gather information about forests without going there in person. It uses satellites, airplanes, or drones equipped with cameras and sensors. This technology can take pictures and collect data. It helps scientists learn how tall trees are, how dense the forest is, and how much carbon it might store.
There are different kinds of remote sensing data:
- Optical imagery: like normal photos taken from space or planes, showing the tops of trees and land features.
- Radar: which uses radio waves and can see through clouds and work at night.
- Lidar: which uses lasers to map the exact height and shape of trees in 3D.
The Challenge with Remote Sensing Data
Each data type has strengths and weaknesses. Optical images are good and widely available, but they can’t see through clouds and only show forest surfaces. Radar can see through clouds but has trouble measuring details in dense forests. Lidar is very accurate but expensive and covers less area.
To get the best info, scientists combine different types of data using artificial intelligence (AI) and machine learning techniques. Machine learning helps computers find patterns in huge amounts of data to make better estimates.
Meta’s Canopy Height Map: AI-Powered Forest Intelligence
Meta developed a unique AI model that merges high-resolution satellite images with lidar data. This model maps tree canopy heights globally with great detail—less than one meter per pixel. This means it can see individual trees in many places.

The map and the AI model are open-source and freely available, so anyone can use them to help forest projects. They enable better planning, monitoring, and verification of forest carbon projects. Reza Rastegar, Senior Manager of Research Science at Meta, stated:
“When applied thoughtfully, we believe AI research and remote-sensing tools, particularly those that are open source, have the potential to revolutionize the transparency and accessibility of the carbon market.”
Meta’s model has been validated with mean absolute errors of 2.8 meters in U.S. forests and 5.1 meters in Brazil. This reflects a promising improvement in estimating canopy height at fine scales. These advanced datasets and models are helping to track natural regeneration, selective logging, and forest degradation more accurately, which is vital for credible MMRV of carbon credits.
What’s special about this model?
- It works globally with very fine detail.
- It can help identify important areas to protect or restore.
- It can make new maps for different times if good images are available.
- It helps detect small changes in forests, like selective logging (cutting some trees but not all).
- It supports methods from carbon credit standards. This is important for those who need dynamic baselining or updating project baselines with real data from nature.

RELATED: Meta and Microsoft Secured Long-Term Carbon Credit Deals to Support Olympic Rainforest
From Pixels to Carbon Credits: Turning Data into Climate Action
Forest carbon projects use different official methods to create and verify forest carbon credits. The three main methods Meta focuses on are:
- Verra VM0045 – for improved forest management (IFM).
- Verra VM0047 – for afforestation, reforestation, and revegetation (ARR).
- American Carbon Registry (ACR) IFM – a US-based improved forest management method.
Here’s how Meta’s canopy height map and AI model fit into these methods:
- In project planning, the map helps find good parcels of forest to include, determine project boundaries, and understand forest structure.
- For dynamic baselining, especially in ARR and ACR’s IFM methods, the AI model can help update baselines based on real forest growth or loss over time.
- For reversals monitoring (tracking if carbon gains are lost, e.g., due to fire or logging), the map gives better details to detect forest disturbances.
The Fine Print: What Meta’s Model Gets Right—and Where It Struggles
Many traditional satellite products can’t reliably measure forest height or biomass in dense forests or small areas. Meta’s model, because it uses very high-resolution images, helps overcome this.
Monitoring small or fragmented forests, river corridors, or areas with selective logging is crucial. These places are difficult to track using low-resolution data.
Meta’s canopy height model is a powerful tool for estimating forest structure, but it comes with limitations. It works best with high-quality imagery at 0.5–1 meter resolution. The global canopy height map uses images from 2009 to 2020. This means it might not show current forest conditions. So, there’s a need for updated maps.
Accuracy may also drop in underrepresented forest types, so local validation with field or lidar data is advised. Using the model requires significant computing power and technical expertise, which may limit adoption.
For forest carbon projects, remote sensing offers great promise but faces barriers. There is no universal agreement among registries, buyers, and developers on acceptable methods or datasets.
In addition, technical skills, computational capacity, and access to affordable, high-quality datasets remain limited. Uncertainty around accuracy—and lack of consensus on acceptable error levels—make trust and comparability difficult.
For the identified barriers, the report authors recommend the following:

Closing the Gap Between Innovation and Impact
Experts want clearer standards for how datasets can be used. They also seek better reporting on uncertainty and clearer rules for issuing carbon credits. A global benchmarking database with verified data and a central portal for quality datasets could help boost adoption.
Moreover, easier AI tools would make this process smoother. Integrating advanced models like Meta’s into accessible platforms, alongside collaborative standard-setting, will be crucial to scaling reliable forest carbon monitoring and verification.
Examples of New and Exciting Uses of Meta’s Model
- Counting trees in agroforestry projects to monitor performance.
- Mapping old-growth forests and biodiversity hotspots.
- Detecting subtle forest degradation, like selective logging.
- Monitoring reversals (losses of carbon stored) with greater accuracy.
- Supporting more accurate estimates of above-ground biomass.
Forests are vital to fighting climate change by storing carbon, but measuring how much carbon they hold and how this changes over time is tough. New technologies like remote sensing are making this easier, faster, and cheaper.
Meta’s AI-powered canopy height map is a cutting-edge tool offering very detailed, global forest height data that can help in planning, monitoring, and verifying forest carbon projects.
The post Meta’s AI Forest Map: The Game-Changer for Carbon Tracking appeared first on Carbon Credits.
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How Climate Change Is Raising the Cost of Living
Americans are paying more for insurance, electricity, taxes, and home repairs every year. What many people may not realize is that climate change is already one of the drivers behind those rising costs.
For many households, climate change is no longer just an environmental issue. It is becoming a cost-of-living issue. While climate impacts like melting glaciers and shrinking polar ice can feel distant from everyday life, the financial effects are already showing up in monthly budgets across the country.
Today, a larger share of household income is consumed by fixed costs such as housing, insurance, utilities, and healthcare. (3) Climate change and climate inaction are adding pressure to many of those expenses through higher disaster recovery costs, rising energy demand, infrastructure repairs, and increased insurance risk.
The goal of this article is to help connect climate change to the everyday financial realities people already experience. Regardless of where someone stands on climate policy, it is important to recognize that climate change is already increasing costs for households, businesses, and taxpayers across the United States.
More conservative estimates indicate that the average household has experienced an increase of about $400 per year from observed climate change, while less conservative estimates suggest an increase of $900.(1) Those in more disaster-prone regions of the country face disproportionate costs, with some households experiencing climate-related costs averaging $1,300 per year.(1) Another study found that climate adaptation costs driven by climate change have already consumed over 3% of personal income in the U.S. since 2015.(9) By the end of the century, housing units could spend an additional $5,600 on adaptation costs.(1)
Whether we realize it or not, Americans are already paying for climate change through higher insurance premiums, energy costs, taxes, and infrastructure repairs. These growing expenses are often referred to as climate adaptation costs.
Without meaningful climate action, these costs are expected to continue rising. Choosing not to invest in climate action is also choosing to spend more on climate adaptation.
Here are a few ways climate change is already increasing the cost of living:
- Higher insurance costs from more frequent and severe storms
- Higher energy use during longer and hotter summers
- Higher electricity rates tied to storm recovery and grid upgrades
- Higher government spending and taxpayer-funded disaster recovery costs
The real debate is not whether climate change costs money. Americans are already paying for it. The question is where we want those costs to go. Should we invest more in climate action to help reduce future climate adaptation costs, or continue paying growing recovery and adaptation expenses in everyday life?
How Climate Change Is Increasing Insurance Costs
There is one industry that closely tracks the financial impact of natural disasters: insurance. Insurance companies are focused on assessing risk, estimating damages, and collecting enough revenue to cover losses and remain financially stable.
Comparing the 20-year periods 1980–1999 and 2000–2019, climate-related disasters increased 83% globally from 3,656 events to 6,681 events. The average time between billion-dollar disasters dropped from 82 days during the 1980s to 16 days during the last 10 years, and in 2025 the average time between disasters fell to just 10 days. (6)
According to the reinsurance firm Munich Re, total economic losses from natural disasters in 2024 exceeded $320 billion globally, nearly 40% higher than the decade-long annual average. Average annual inflation-adjusted costs more than quadrupled from $22.6 billion per year in the 1980s to $102 billion per year in the 2010s. Costs increased further to an average of $153.2 billion annually during 2020–2024, representing another 50% increase over the 2010s. (6)
In the United States, billion-dollar weather and climate disasters have also increased significantly. The average number of billion-dollar disasters per year has grown from roughly three annually during the 1980s to 19 annually over the last decade. In 2023 and 2024, the U.S. recorded 28 and 27 billion-dollar disasters respectively, both setting new records. (6)
The growing impact of climate change is one reason insurance costs continue to rise. “There are two things that drive insurance loss costs, which is the frequency of events and how much they cost,” said Robert Passmore, assistant vice president of personal lines at the Property Casualty Insurers Association of America. “So, as these events become more frequent, that’s definitely going to have an impact.” (8)
After adjusting for inflation, insurance costs have steadily increased over time. From 2000 to 2020, insurance costs consistently grew faster than the Consumer Price Index due to rising rebuilding costs and weather-related losses.(3) Between 2020 and 2023 alone, the average home insurance premium increased from $75 to $360 due to climate change impacts, with disaster-prone regions experiencing especially steep increases.(1) Since 2015, homeowners in some regions affected by more extreme weather have seen home insurance costs increased by nearly 57%.(1) Some insurers have also limited or stopped offering coverage in high-risk areas.(7)
For many families, rising insurance costs are no longer occasional financial burdens. They are becoming recurring monthly expenses tied directly to growing climate risk.
How Rising Temperatures Increase Household Energy Costs

The financial impacts of climate change extend beyond insurance. Rising temperatures are also changing how much energy Americans use and how utilities plan for future electricity demand.
Between 1950 and 2010, per capita electricity use increased 10-fold, though usage has flattened or slightly declined since 2012 due to more efficient appliances and LED lighting. (3) A significant share of increased energy demand comes from cooling needs associated with higher temperatures.
Over the last 20 years, the United States has experienced increasing Cooling Degree Days (CDD) and decreasing Heating Degree Days (HDD). Nearly all counties have become warmer over the past three decades, with some areas experiencing several hundred additional cooling degree days, equivalent to roughly one additional degree of warmth on most days. (1) This trend reflects a warming climate where air conditioning demand is increasing while heating demand generally declines. (4)
As temperatures continue rising, households are expected to spend more on cooling than they save on heating. The U.S. Energy Information Administration (EIA) projects that by 2050, national Heating Degree Days will be 11% lower while Cooling Degree Days will be 28% higher than 2021 levels. Cooling demand is projected to rise 2.5 times faster than heating demand declines. (5)
These projections come from energy and infrastructure experts planning for future electricity demand and grid capacity needs. Utilities and grid operators are already preparing for higher peak summer electricity loads caused by rising temperatures. (5)
Longer and hotter summers also affect how homes and buildings are designed. Buildings constructed for past climate conditions may require upgrades such as larger air conditioning systems, stronger insulation, and improved ventilation to remain comfortable and energy efficient in the future. (10)
For many households, this means higher monthly utility bills and potentially higher long-term home improvement costs as temperatures continue to rise.
How Climate Change Affects Electricity Rates
On an inflation-adjusted basis, average U.S. residential electricity rates are slightly lower today than they were 50 years ago. (2) However, climate-related damage to utility infrastructure is creating new upward pressure on electricity costs.
Electric utilities rely heavily on above-ground poles, wires, transformers, and substations that can be damaged by hurricanes, storms, floods, and wildfires. Repairing and upgrading this infrastructure often requires substantial investment.
As a result, utilities are increasing electricity rates in response to wildfire and hurricane events to fund infrastructure repairs and future mitigation efforts. (1) The average cumulative increase in per-household electricity expenditures due to climate-related price changes is approximately $30. (1)
While this increase may appear modest today, utility costs are expected to rise further as climate-related infrastructure damage becomes more frequent and severe.
How Climate Disasters Increase Government Spending and Taxes
Extreme weather events also damage public infrastructure, including roads, schools, bridges, airports, water systems, and emergency services infrastructure. Recovery and rebuilding costs are often funded through taxpayer dollars at the federal, state, and local levels.
The average annual government cost tied to climate-related disaster recovery is estimated at nearly $142 per household. (1) States that frequently experience hurricanes, wildfires, tornadoes, or flooding can face even higher public recovery costs.
These expenses affect taxpayers whether they personally experience a disaster or not. Climate-related recovery spending can increase pressure on public budgets, emergency management systems, and infrastructure funding nationwide.
Reducing Climate Costs Through Climate Action
While this article focuses on the growing financial costs associated with climate change, the issue is not only about money for many people. It is also about recognizing our environmental impact and taking responsibility for reducing it in order to help preserve a healthy planet for future generations.
While individuals alone cannot solve climate change, collective action can help reduce future climate adaptation costs over time.
For those interested in taking action, there are three important steps:
- Estimate your carbon footprint to better understand the emissions connected to your lifestyle and activities.
- Create a plan to gradually reduce emissions through energy efficiency, cleaner technologies, and more sustainable choices.
- Address remaining emissions by supporting verified carbon reduction projects through carbon credits.
Carbon credits are one of the most cost-effective tools available for climate action because they help fund projects that generate verified emission reductions at scale. Supporting global emission reduction efforts can help reduce the long-term impacts and costs associated with climate change.
Visit Terrapass to learn more about carbon footprints, carbon credits, and climate action solutions.
The post How Climate Change Is Raising the Cost of Living appeared first on Terrapass.
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Carbon credit project stewardship: what happens after credit issuance
A carbon credit purchase is not a transaction that closes at issuance. The credit may be retired, the certificate filed, and the reporting box ticked. But on the ground, in the forest, in the field, and in the community, the work continues. It endures for years. In many cases, for decades.
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