Forests Sourcebook - HCV Resource Network

Box 7.19
Selecting the Appropriate Approach and Tools (continued)
Deforestation (1997–2000)
Selective logging (1999–2000)
Source: Asner and others 2006 (copyright 2006 National Academy of Sciences, U.S.A.).
Note: This program is coordinated by Gregory P. Asner, Department of Global Ecology, Carnegie Institution of Washington,
Stanford, CA, USA. This program required about US$2.5 million to develop the areas of signal processing, super-computing,
canopy physics, and field ecology necessary to make such monitoring feasible.
Spatial and temporal scale. Forest monitoring using
RS/GIS can be carried out on different spatial and temporal
scales depending on the features of interest for monitoring
and the goal of the monitoring exercise. Forest monitoring
using RS/GIS can include clear cuts, intensive selective logging,
log yards, fires, road building, habitat fragmentation,
biomass, and productivity. The monitoring of these features
often requires different time steps and detail. A national
overview of deforestation usually requires a one to five year
time frame, while monitoring of fires in national parks may
need more frequent updates (several satellites can detect
fires in the forests, see box 7.20).
Forest monitoring methods. A number of different
applications and methods for forest monitoring exist, and
the choice of which to use will depend on the purpose of the
monitoring and the desired spatial and temporal scales.
Table 7.4 lists the existing satellite remote sensors, and their
applications and limitations for specific purposes. Table 7.5
lists currently available global forest maps.
An emerging RS/GIS application that merits special consideration
is the MODIS-derived data set of percentage of
tree coverage, produced by researchers at the University of
Maryland and South Dakota State University. The new maps,
based on the MODIS sensor operated by NASA, provide a
consistent overview of the global distribution of percentage
of tree coverage in a continuous gradient (0 to 100 percent).
This allows flexibility so that the gradient can be adapted to
different forest definitions. The MODIS satellite provides free
global data coverage daily, allowing information to be compiled
and processed in a relatively speedy manner. The speed
of data availability, the relative low cost, and the flexibility to
adapt to different forest definitions offer huge opportunities
for international and global forest monitoring efforts.
278 CHAPTER 7: MONITORING AND INFORMATION SYSTEMS FOR FOREST MANAGEMENT