EO Product for determination of (1) Recent forest coverage and (2) Historic forest coverage and (3) Forest change

Target group: Project-developers of forest carbon sink (ARD) projects 

Project phase: Design and implementation phase

Application area, scope and information requirements: 

Determination of Baseline
Art. 6.1b and 12.5c of the KP state that project’s activities must lead to carbon benefits that are additional to a “business-as-usual” scenario (=additionality). The quantification of the additional carbon benefits requires the development of a baseline scenario against which changes in carbon pools in the with-project case can be compared. In other words, it has to be estimated what would have happened in the absence of the project. This leads to one of the greatest challenges in the project design because land use change and changes in forest management practices are hard to predict. 

The difficulty to predict likely changes in land use and their corresponding carbon in the without-project cases depend on changing socio-economic, cultural and political conditions. Therefore, geo-spatial information on biophysical drivers and socio-economic variables as well as on land use and forest at different dates (recent and historic) is required to be combined by spatial modelling in order to simulate future trends. Generally speaking it is useful to consider two cases of baseline determination. In the first case the project has to be assessed in isolation from a broader economic system. In the second case, the project has to be integrally linked with a larger economic and environmental system, so that baseline determination must consider the entire system. 

Detailed information from EO data on forestry and land use within the project activity boundaries but also information outside is required in order to determine the negative or positive project side effects (=leakage). In this context leakage is used to determine positive (=spillover) but also negative project effects (e.g. increased fuelwood consumption outside a newly protected area). When however considering the typically project duration (30 to 99 years) the shortcomings of such static (=fixed) baseline assessments become obvious and it was for this reason that some projects have implemented a dynamic (=adjustable) baseline assessment. The latter requires knowledge on generalised land-use trends (change indices) and has a large credibility advantage over a static baseline because adjustments to new economical, ecological and political development trends can be made throughout the project duration.

Conventional method:
No standard methods exist for setting baselines. In a number of already existing demonstration projects different approaches for establishing baselines are in use. These are ranging from simple logical arguments based on adjusting observed trends or assuming the continuation of business-as-usual trends to spatial modelling. Quantification of carbon is mostly done in proxy areas within control plots. In some cases it is only based on literature. Such input data may lead to wrong assumptions at project registration and baseline calculation and thereby increase the financial risk of the project.

Potential EO sensors: 
MERIS, MODIS, WIFS, MSU-SK, MSS and TM

EO derived product advantages and innovation: 
EO is a proven source for forest/land-cover mapping, for producing statistics on land use and it is the only geodata source that provides comparable data from the Earth surface for the last decades. The data can contribute objective geo-spatially referenced information with a statistically assessed level of precision. The generalised knowledge of the project area can be used for further planning purposes and subsequent stratification. Where necessary, the generalised information can be combined with higher resolution information for estimation of the baseline/leakage.

Advantage for project-developer and cost benefit: 
The risk associated with project registration and conduction can be reduced due to sound available land cover/use input data. While the cost of EO with moderate and medium resolution data is relatively low (due to incommensurable results with conventional methods no direct cost comparison is made) it also allows for observation of large areas. On the performance side the information derived from EO for geo-spatial modelling adds a significant advantage for projecting the without-project baseline in a more objective way and leads in the case of adjustable baselines to more plausible off-set scenarios.
 
 
 
 

EO Product Examples:

The EO derived information is delivered in form of maps and statistics and serves as numerical input into spatial models for verifying the without-project baselines. Theoretically, the spatial extend of gathering data can be expanded to any size of a system area.
 

1) EO product for determination of recent forest coverage:
 

Generalised forest/land cover maps in and outside of the project accounting boundaries derived from moderate to medium ground resolution sensors.

If you are interested in this product please 
download the PDF product sheet to your hard disk by saving it with the right mouse button.
Downloading may take a minute 
due to the file size optimised for A4 printing. 
 
 
 
 

2) EO product for determination of historic forest coverage:
 

Forest non forest coverage map in- and outside the project accounting boundaries derived from moderate to medium ground resolution sensors

If you are interested in this product please 
download the PDF product sheet to your hard disk by saving it with the right mouse button.
Downloading may take a minute 
due to the file size optimised for A4 printing. 
 
 
 
 

3) EO product for determination of forest change: 
 

Generalised change maps showing increases and decreases of the forested area.

If you are interested in this product please 
download the PDF product sheet to your hard disk by saving it with the right mouse button.
Downloading may take a minute 
due to the file size optimised for A4 printing.