Forests Sourcebook - HCV Resource Network
Forests Sourcebook - HCV Resource Network
Forests Sourcebook - HCV Resource Network
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Assessment (www.millenniumassessment.org). Another<br />
good framework, although still being piloted and not yet<br />
implemented at regional and global levels, is the “Manual<br />
for Environmental and Economic Accounts” (FAO 2004).<br />
Using existing and new methodologies. Advancements<br />
in methodology and technology are a constant phenomenon<br />
in forest monitoring, as evidenced by the advancements<br />
in remote sensing, a particularly useful tool for studying forest<br />
change comprehensively and uniformly across time and<br />
space. Remote sensing multiplies the value of field-plot data<br />
and permits complete, wall-to-wall analyses. Spatial images<br />
from Landsat have been a workhorse for scientists interested<br />
in measuring changes in the distribution and condition of<br />
forests. A number of satellites have come online since Landsat,<br />
several of which are useful for monitoring forests<br />
(USDA 2007). Other advancements in forest monitoring<br />
approaches have been based on imaging radar data, which<br />
works in all weather conditions. Methodological advancements,<br />
too, such as simplifying and automating mapping of<br />
forest disturbances (USDA 2007), have been important.<br />
Older technologies, such as mobile data loggers and<br />
mobile communication, could be more effectively used for<br />
monitoring forest activities. Mobile telephone communication<br />
can serve two purposes: It can increase the safety of<br />
field crews by giving them access to communication in cases<br />
of emergency, while also enabling online data entry to a central<br />
database. Advancements in software, such as GIS 2 , also<br />
offer many possibilities for presentation of results and<br />
improved access to information.<br />
The use of some of the newer technologies is not without<br />
shortcomings. For example, the availability of reference data<br />
for digital image analysis or visual interpretation is one of<br />
the key problems in remote sensing–aided surveys. The<br />
parameters that can be estimated using remote-sensing surveys<br />
often depend on the intensity of the field sampling.<br />
Area of forests, other wooded land, and other land types, as<br />
well as their changes, can be adequately measured with<br />
available remote sensing–aided surveys. In contrast, tree<br />
stem volume and biomass, which are critical variables in<br />
determining the status of the world’s forests, require thorough<br />
field measurements for their estimation. Such limitations<br />
are constantly being dealt with.<br />
Cost of monitoring. Cost is often an important driver in<br />
designing monitoring systems. A frequently asked question<br />
is when and whether satellite imagery–based forest cover<br />
mapping can substitute for forest inventory. Mapping studies<br />
cost less than field work (if the necessary hardware and<br />
software are available); need less planning, smaller teams,<br />
and less broad expertise; are partly independent of weather;<br />
and provide maps as the major product, which are usually<br />
more easily accepted and “marketed” than statistics and<br />
tables with error specifications.<br />
The type of analysis required often influences the cost.<br />
High-resolution images are notably more expensive than<br />
coarse images. Tomppo and Czaplewski (2002) estimated<br />
costs for remote sensing under different resolutions and<br />
sampling options for regional and global surveys using<br />
remote sensing and field data (see tables 7.2 and 7.3). The<br />
costs have since changed significantly, but this information<br />
provides an indication of the differences in costs.<br />
Selection of indicators. Assessing all benefits from<br />
forests over time is complicated, and only feasible if simplifications<br />
and approximations, such as indicators, are<br />
accepted. Several international processes have developed<br />
criteria and indicators for sustainable forest management.<br />
Table 7.2<br />
Example of Number of Images and Estimated Costs for a Remote-Sensing Survey with<br />
Different Resolution and Sampling Options<br />
Number of images needed<br />
Imaging cost (US$ thousand)<br />
MODIS Landsat Ikonos Ikonos Landsat Ikonos Ikonos<br />
full 10% 0.1% 1% 10% 0.1% 1%<br />
Region coverage coverage coverage coverage coverage coverage coverage<br />
Africa 6 97 331 3,309 58 951 8,992<br />
Asia 6 100 343 3,428 60 986 9,315<br />
Europe 4 73 251 2,511 44 722 6,824<br />
North and Central America 4 69 237 2,374 42 683 6,453<br />
Oceania 2 28 94 943 17 271 2,564<br />
South America 3 57 195 1,950 34 561 5,299<br />
Total 25 424 1,451 14,515 255 4,174 39,447<br />
Source: Tomppo and Czaplewski 2002.<br />
Note: MODIS and Landsat are NASA satellite imaging programs; Ikonos is is a commercial Earth observation satellite.<br />
254 CHAPTER 7: MONITORING AND INFORMATION SYSTEMS FOR FOREST MANAGEMENT