Remote Sensing for Carbon Project Disturbance Modeling
Carbon offset project areas, like all forests, are regularly impacted by a myriad of natural disturbances. These disturbances include but are not limited to wildfires, hurricanes, tornadoes, droughts and floods. In a world where forests are increasingly vulnerable to natural disturbance, it is of the utmost importance that disturbance events are properly monitored and accounted for. The Climate Trust carefully monitors all disturbance events to ensure that landowners are protected from the financial impacts of natural events.
An Overview of Remote Sensing
Remote sensing can be used to efficiently and cost-effectively monitor and assess disturbance events. Remote sensing is the process of gathering information about Earth’s surface without physically being there, in this case, using satellites. It works by emitting radiation and measuring the returned reflectance to create images that highlight features of Earth’s surface (1). This technology can be essential for monitoring carbon offset projects that are impacted by natural disturbances because it can allow the project manager to see clearly the state of the forest before the disturbance and after the disturbance. By allowing project managers to assess damage from afar, remote sensing helps inform decisions on how to respond to disturbance events effectively.
Steps to Remotely Monitor the Impacts of a Disturbance Event
1. Acquire Sentinel-2 Imagery: The first step in the process is to download Sentinel-2 satellite imagery from before and after the disturbance event. Ideally, post-event images should be collected 2 to 4 months after the disturbance to allow time for dead vegetation to clear. Pre-event images should be taken one year prior to the post-event images to minimize seasonal differences in the analysis.
2. Compute EVI: Once the pre-event and post-event imagery is downloaded, the next step is to calculate the Enhanced Vegetation Index (EVI) for each image to assess vegetation health. EVI is a spectral index that identifies the presence of healthy vegetation through identifying canopy structure variations (2). EVI values range from -1 to 1, with healthy vegetation typically falling between 0.20 and 0.80 (3).
3. Detect Changes in Vegetation: After computing the EVI for both images, the next step is to calculate the difference between the two EVI images. This step helps identify hotspots of potential damage to vegetation in the project area.
4. Paired-t Test: The final step in the analysis is to conduct a paired t-test to assess whether there is a statistically significant difference between the pre-event and post-event EVI images. The paired-t test compares the EVI value of each pixel in the pre-event image with the corresponding pixel in the post-event image. This test is used to ensure that the difference between the two images is statistically significant (4).
This, or similar processes, enable The Climate Trust and other project developers and managers to assess whether a project area has undergone significant change before and after a natural disturbance. If a significant difference is detected, the analysis helps project managers identify where to establish new plots and conduct on-the-ground damage assessments. Remotely monitoring project areas is essential for proactive carbon credit project management and reducing project costs.
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