3.4.2. Monitoring Land-Cover Change
Scenarios that create ARD land on the basis of a wide range of activities,
including harvest/regeneration cycles and natural disturbances followed by regeneration
(as in Land Cover or FAO scenarios), will result in a much larger area of ARD
land. The data requirements for area determination under such scenarios may
be met through approaches that are based on monitoring land-cover change, such
as remote sensing. Forest definitions with a high canopy cover threshold likely
would lead to more accurate identification of ARD activities with remote sensing
than definitions with a low canopy cover threshold because sparse forest conditions
are more frequently confused with some types of agriculture or scrub/shrub ecosystems
in assessments based on the use of remotely sensed imagery. For the same reason,
if regenerated areas with minimal crown cover are considered forest (e.g., FAO
scenario), remote-sensing techniques would be unable to reliably detect them.
If the forest definition is dependent on a biomass assessment (which is possible
in the Flexible scenario), forest areas could not be accurately estimated with
current remote sensing systems. In this case, field inventory would almost certainly
be required. Table 3-8 summarizes the potential of current
remote-sensing systems to detect ARD activities.
Table 3-8: Potential of current remote sensing
systems to detect ARD activities.
|
|
Definitional
Scenario |
Ability to
Detect ARD
|
Notes
|
|
FAO |
Low
|
a
|
IPCC |
Low
|
a
|
Land Use |
Low
|
|
Land Cover |
Moderate
|
a
|
Flexible |
Low
|
b
|
Degradation/Aggradation |
Low
|
c
|
Biome |
Moderate
|
a,d
|
|
a Considerable misclassification may exist between sparse or young forest
and agriculture or other vegetation types, leading to errors when forest cover
thresholds are low.
b Biomass estimates will be of low accuracy.
c Transitions from one cover class at maturity to another within forest are
difficult if not impossible to assess accurately.
d Highly variable, depending on defined threshold.
|
|
When ARD activities are defined as a change between forest and non-forest,
most such activities will be readily discernible using forest/non-forest classifications
at least in 1990 and 2012. Some definitions of ARD, however, could mean that
land that is in forest status in both 1990 and 2012 might still be included
in Article 3.3 (Section 3.4.1), so simple forest classification
at the two endpoints would be insufficient to determine ARD land. Thus, information
beyond a forest/ non-forest classification at different points in time is required.
This information could be gathered through combinations of remote sensing and
ground-based sampling. The information-gathering process includes two main tasks:
- Identification of land use/land cover in 1990 to serve as the baseline
- Monitoring of ARD activities between 1990 and 2012.
In many countries, reliable data on forest area, age, and species distribution
result from detailed forest inventories. These inventories are usually conducted
on periods of 10 to 20 years, however. Thus, assessment of changes between 1990
and 2012 will require application of approximation procedures that yield estimates
based on assumptions or auxiliary information about the continuation or alteration
of a trend.
|