Forests Sourcebook - HCV Resource Network

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Availability of reference data. Monitoring is effective
when reference data (for example, type of forest, boundary
of parks, roads, or populations) are available. The use
of reference data facilitates monitoring and thus decision-making
and enforcement processes. However, reference
data often do not exist or are of insufficient quality.
Human capital. Satellite imagery processing and interpretation
can be time consuming and often requires an
initial investment to set up the processing system.
Costs. Costs depend on the satellite used and the accuracy
needed. High-resolution imagery remains costly. Spatial
accuracy and ground verification, at least in the initial
stages to calibrate imagery interpretation, can add significant
expenses.
Limited information. Not everything can be detected with
RS. Tree species cannot be determined unless data is collected
at a very detailed scale. Spatial monitoring with
RS/GIS can add to, and should not compete with, a
detailed ground inventory.
OPERATIONAL ASPECTS
RS/GIS requirements. Forest monitoring using RS/GIS
requires the following:
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Technological capability to generate, store, and update
the RS/GIS data; this often requires high computer capabilities
and specialized software for imagery and GIS
analysis, interpretation, and manipulation.
Human capital to generate, manipulate, apply, and interpret
the data, as well as capability to translate data in
user-friendly format to end users.
Effective and functional forest monitoring. Effective
and functional forest monitoring involves the following:
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An initial assessment of existing information and identification
of data gaps to reconcile data with features of
interest: Forest change in a national park cannot be monitored
if there is no information on the boundaries of the
park. This assessment includes an evaluation of the quality
and accuracy of the data: Extraction of a valuable
species cannot be effectively monitored if the forest composition
data is inaccurate or outdated.
Filling out data gaps by creating the data needed (that is,
digitizing features from satellite imagery; purchasing
satellite imagery) or identifying and defining surrogate
indicators to assess features data (for example, using
incidence of fire as an indicator of human activities in
certain forest types).
Establishing a baseline of (i) the spatial distribution of
features of interest that are susceptible to change and (ii)
the boundaries against which change will be periodically
assessed.
Box 7.18
Using Geospatial Tools for LULUCF Projects
Geospatial tools can help shape LULUCF projects during
the conceptual stages, and beyond, in the following ways:
The tools can be used in demonstrating and justifying
the status of the land use before 31 December 1989
(deadline for the first LULUCF commitment period).
Imagery will provide information on current land cover,
and if past imagery is available then information about
the past land cover can be derived. Land cover maps can
then be drawn from these. Where digital information is
not available (for example, when using only old aerial
photographs), an old map can be digitized.
They can assess the changes taking place in forest
canopy over time. Such change could be a result of forest
restoration activity or tree removals (by logging,
fires, disease, and the like).
They can demarcate and survey carbon asset
boundaries in a project area. Such information, including
land ownership, soil typology, drainage, elevation,
and vegetation cover percentage, can then be stored
and managed in a GIS.
Because GPSs are affordable and portable in the field,
they can work in very remote areas and in difficult terrain.
Locations can be georeferenced (x and y coordinates of
the latitude and longitude), and coordinates can be
directly stored in a computer system.
Advancements in the technology now make it possible
to integrate geospatial information into a decision-making
tool. For instance, remotely sensed data
from an IKONOS spectral image can be analyzed
through a GIS platform into different layers as needed.
Such layers could include vegetation type, land with or
without tree cover, water bodies, ownership patterns,
roads, and so forth. This information then becomes a
product that can help inform decision making.
Source: Kaguamba 2004.
276 CHAPTER 7: MONITORING AND INFORMATION SYSTEMS FOR FOREST MANAGEMENT