A brief history of forest monitoring technologies (satellite-based remote sensing remains the most cost-effective method)

• Ground measurements: Forests were initially measured using ground-based measurement of "national forest inventory." This was highly time and resource intensive, so inventories would only be updated once every 5 years
• Landsat satellite: The golden age of forest monitoring started in 2008, when the "US Geological Survey opened all data from its Landsat satellite to the public for free, which offers 30-meter resolution data dating back to 1972." This was a 70x improvement over previously available MODIS satellite data.
  • The Landsat archive and available time-series methods provide a good opportunity to understand land use history and establish forest reference and emissions levels, against which to monitor change and determine the relevant time-scales over which degradation occurs. Landsat imagery can help locate and map out logging transportation networks, and identify burn scars where clearing has taken place - it is typically used to distinguish between forest and non-forest land cover, and to monitor land-use changes.
• ESA satellite and radar: "In 2013, the European Commission and European Space Agency (ESA) decided to openly license data from the Sentinel satellites (ESA 2013), complementing Landsat with freely available, 10-meter data, as well as radar satellites that can see through cloud cover, smoke, and haze (Reiche et al. 2016)."
• Private satellites: "An increasing number of commercial satellite companies (e.g., Planet, TerraSar) offer high spatial resolution data that—while costly for large-scale systematic analyses—can be valuable for validation, calibration, and verification." Planet Labs offers 3-5 meter imagery, available anywhere in the world.
• Other tools: Forest monitoring from Brazil’s space institute, INPE, has been influential in reducing the country’s deforestation rate. Tools such as the Global Forest Watch of World Resources Institute use near real-time satellite data to provide current information about deforestation threats around the world.

Planet Labs asserts that the public versus commercial access gap is closing. The main issue is political, not technological

• Europe's Sentinel-1 is the first radar satellite that provides freely available data, updated every 12 days regardless of weather conditions (radar can see through clouds)
• Europe's new Sentinel-2 satellite freely offers 10-meter resolution optical imagery every 4 days
• Planet Labs now displays monthly 5-meter cloud-free mosaic images. Planet's other commercial offerings (e.g., 3-meter readings, daily readings) are more expensive
• There are now freely available alerts with datasets, updated weekly, showing 30m by 30m pixels of likely forest loss. Alerts may yield thousands, even millions, of raw data points (pixels) on a regular basis and can quickly become overwhelming, especially at larger scales. It's possible to prioritize alert data to focus on protected areas, indigenous territories, etc.
• Read here about a five-step near–real-time deforestation-monitoring protocol designed primarily for government and civil society. This comprehensive protocol, based on recent monitoring initiatives in the Amazon and insights from the international Global Forest Watch partnership, is particularly aimed at tropical countries that are designing strategies to confront deforestation.

Within the last few years, there is optimism that Sentinel satellites can be used to estimate above-ground biomass

• A number of researchers including from Australia, China, and Indonesia have released promising papers showing the ability to estimate above-ground biomass using Sentinel satellites
  • Australian study: "Multi-criteria evaluations showed the use of the two independent and fundamentally different Sentinel satellite systems were able to provide robust estimates (R2 of 0.62, RMSEof 32.2 t.C.ha-1) of aboveground forest biomass, with each sensor compensating for the weakness (cloud perturbations and spectral saturation for Sentinel 2, and sensitivity to ground moisture for Sentinel 1) of each other."
  • Indonesian study: "We used 45 sample plots and 7 vegetation indices to evaluate the ability of Sentinel-2 in estimating AGB on private forests. Normalised difference index (NDI) 45 exhibited a strong correlation with AGB compared to other indices (r = 0.89; R2 = 0.79). Stepwise linear regression fitted for establishing the model between field AGB and vegetation indices (R2 = 0.81). Overall, vegetation indices from Sentinel-2 multispectral imagery can provide a good result in terms of reporting the AGB on private forests."
  • Mongolian study: "Comparison of the model (using Sentinel 1B and Sentinel 2 data) and ground truth measurements for above ground biomass have a good agreement"
• A number of papers published just in 2017 describe shortcomings with satellite-based approaches
  • Estimation of above-ground biomass (AGB) is difficult at national scale and current methods using satellite data do not meet the level of precision required for REDD+ reporting. An interim solution might involve LiDAR-assisted sampling or using L-band SAR data to gain an overview of biomass strata in low biomass and degraded forests. Novel techniques are being developed using InSAR and LiDAR data and looking at change in vertical structure and volume
  • "Certain types of land cover and land use dynamics remain difficult to discern from space. These include detecting changes in tropical dry forests, the extent and timing of forest regrowth, land use characteristics and impacts (e.g., shifting cultivation cycles), and estimating forest variables such as height, biomass, and structure. Several technologies exist to map these values, such as drones or airborne Light Detection and Ranging (LiDAR) instruments, but they are not yet cost-effective enough to deploy over large areas."

Monitoring is strict for CA Tropical Forest Standard (TFS) projects

• For TFS projects, monitoring must include “transparent, high-quality, spatially explicit mapping data for above-ground biomass using remote sensing technology that has been calibrated to the implementing jurisdiction against ground-level measurements from within the jurisdiction.” Must be capable of recognizing native versus non-native forest.