eld observations 
| areas do not 
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/ problematic for 
vo of the twelve 
n remnant trees 
irmed from plot 
iably distinguish 
and mangrove, 
jle for the latter 
n the different 
r priority for the 
on of important 
salt marsh and 
ould help both 
and ecotourism 
rts. 
most troubling 
ion concerned 
rops of manioc 
arly banana. A 
manioc is often 
small = plots. 
its classification 
om mixed pixel 
\s a subsistence 
uld usually be 
(ear other crops 
wy not seriously 
indications of 
lassifying banana 
t is understand- 
latively mature 
jven their high 
ht and cover. 
is an important 
f the current 
Janana is an 
p in the region, 
ated in large 
ear the ends of 
r proximity to 
Is may help in 
of conservation 
and remoteness 
require further 
future reclassi- 
S. 
es and Maps 
rages for each 
cover type must still be combined into a single 
unified coverage. This will require some cleanup 
steps. The photointerpretation process digitized each 
cover type as a separate coverage and left dense 
forest as the unclassified default condition. Slivers 
and overlap between the different photointerpreted 
cover types can occur and will need to be resolved. 
Rasterization of the final coverage will also need to 
be performed to facilitate data sharing and 
environmental modeling. 
The first graphical cover type map produced 
from the project has proven extremely informative 
about land cover and characteristics in the region. 
The combination of false color composite imagery 
overlain with pattern fills showing mangrove, 
restinga, humid soils, and planalto allows ready 
identification of interpreted cover types with 
minimal obscuring of the original imagery. Only 
beaches and the scattered exposed soil polygons are 
shown in solid fill, permitting most of the false color 
and topography to show through. Orientation is 
provided through localization maps, roads, and 
annotated place names. 
A second map showing false color 
composite for the broader region provides a useful 
broader adjunct to the classified image. However, for 
both of these maps their large size and use of full 
color limits their ease of production and duplication. 
Simpler versions are planned for broader 
distribution. 
5. DISCUSSION 
As a technology transfer project built around 
a case study of ecotourism and remote sensing, the 
project’s success can be judged in two ways: the 
utility of the resulting land cover classification and 
GIS database, and the improved skills and local 
capacities resulting from the effort. These are 
evaluated following discussion of some ways the 
work might have been improved. 
In hindsight we can suggest several ways the 
study might have been done better. Scheduling the 
field season to match the drier Brazilian winter 
would have been one such move, perhaps with two 
concurrent crews and GPS receivers. More field 
plots would certainly have helped deal with the large 
diversity within the region. 
A more interleaved sequence of field and lab work 
seems preferable to our sequential approach. A 
preliminary analysis of the satellite image could be 
done first, followed by establishment of field plots, 
then supervised classification, then followup ground 
truthing, and lastly critique by local experts. 
77 
Better on screen digitization procedures 
would have minimized gaps and overlap between the 
cover type polygons, although we are optimistic that 
improved classification methods may reduce the 
need for photointerpretation. 
In this next round of classification we plan to 
sequentially classify groups, mask them out, then 
classify the remainder. With the recently available 
coverages from IPARDES we can now test whether 
stratifying the image based on geomorphic properties 
aids classification accuracy. Anticipated upgrades to 
the Imagine software may also reduce some of the 
classification difficulties we encountered. 
A high priority for future work should be 
development of a DEM. It would help remove 
differential illumination problems with mountain 
shadows as well as contribute more directly to a wide 
range of environmental models and analyses. 
With the exception of banana the coverage 
succeeded in separating those places where human 
disturbance has been recent and severe from those 
where natural vegetation occurs largely intact. Given 
the relatively rapid changes that land uses in the 
region can undergo, such a distinction is extremely 
useful, particularly if it can be updated periodically 
to provide feedback on the effectiveness of forest 
protection policies. This mapping was accomplished 
with a spatial accuracy consistent with the 30 m 
pixels of the original imagery and the spatial scale of 
the desired features. 
The spatial land cover data from this project 
are being made available to other interested parties, 
and can now be analyzed together with other spatial 
data, allowing more timely, objective, and complex 
investigations of management alternatives than have 
been previously possible. 
The potential benefits of the mapping effort 
were demonstrated during Idrisi training near the 
conclusion of the project. Early versions of the 
coverage were used along with several from 
IPARDES in exercises demonstrating trail planning, 
conservation zoning, and deforestation assessment. 
The technology transfer objectives of the 
project favored development of local capabilities 
over reliance on more experienced facilities available 
elsewhere in Brazil or the United States. Building 
local expertise in remote sensing of natural resources 
and application of GIS offered long term benefits far 
beyond the direct benefits of the database itself, 
although it did differentiate the effort from more 
operational projects by requiring more flexible 
planning and greater attention to communication 
needs. 
Most of the individuals in the project are