Verifiability of stock changes from ARD activities as required in Article 3.3 will require the ability to verify that the activities have taken place, as well as the ability to verify stock changes from those activities. The primary difficulty involves verification of the historical status of a resource that may no longer exist.
If an existing monitoring system uses accepted quality assurance/ quality control procedures and reports statistics about the quality of on-site estimates, independent validation of each estimate may be simplified. Certifying that the methodology used includes quality assurance and quality control within some specified standards may be sufficient.
An advantage of remotely sensed data is that archives of images collected over time are frequently available. This archiving enables third parties, without on-the-ground inspections, to verify land-cover status at prior points in time (to the extent that land-cover types are accurately identifiable on the imagery). Even with extensive archives of imagery, however, weather conditions (cloud cover), sensor operating status, and other factors may preclude observation of large portions of the earth at various times. Hence, there is no guarantee that imagery will be available on or near desired points in time. In addition, although remote sensing may have a role in verification, use of imagery still requires ground verification in areas where there is doubt, as well as verification or causes of perceived ARD.
Even in situations in which historical imagery of acceptable quality is available, verification will require assessment of carbon stocks, which will rely primarily on sample data taken at appropriate times and the ability to spatially reference the sample locations. When such data are not available, stock changes cannot be accurately verified. For example, a non-reported deforestation activity might be detected through the use of archived remotely sensed imagery. Yet the only recourse to estimate the carbon stock loss (in the absence of site-specific field data prior to deforestation) would be to use averages for carbon stock by forest type and/or size class. Conversely, an afforested area could be sampled to obtain forest carbon stock estimates, but previous stocks (such as soil carbon) would have to be estimated without the use of field data. Thus, stock-based forest definitions (e.g., Flexible scenario) will result in unique difficulties in verification.
With good analysis of error or uncertainty and reliable quality control procedures, verification could be limited to confirmation that methods were applied correctly. Most forest inventories include quality control and sometimes report statistics on data quality. This procedure could be extended to carbon inventory.
Establishing institutional procedures may be necessary to verify that reported estimates were made using a transparent methodology that includes quality assurance and control procedures. The methodology could be monitored (or certified) by an independent authority.
Remote sensing would be useful as one among other data sources in establishing the initial land use/land cover, to ensure that results are verifiable. It also helps in detecting, delineating, and measuring area changes and can provide objective information on whether land-use and forestry activities are human-induced.
The Kyoto Protocol anticipates that Parties will have in place national and, where appropriate, regional, forest inventory systems for annual estimation and reporting of human-induced emissions by sources and removals by sinks from ARD activities in a transparent and verifiable manner. We briefly reviewed the applicability of remote sensing and forest inventory techniques for establishing the data and for monitoring and verifying changes in ARD land and carbon stocks in a statistically reliable manner.
A National Forest Inventory system that is based on continuous forest inventory concepts is an important component for obtaining and verifying information on changes in carbon stocks. In addition, transparent and verifiable reporting of land-use changes calls for use of interdependent remote sensing techniques. Further gains in precision and reductions of costs might result from integrating successive surveys for forest area and volume in a common statistical framework. Models and special studies are needed to estimate carbon above and below ground. Finally, institutional capacity-building is vital to ensure a high degree of consistency between successive survey and interpretation procedures, as well as imagery products (sensors, season, quality, etc.).
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