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covering forest, range, and agricultural sites, 4x enlargements of black-
and-white composite satellite photography, 1:62,500 scale contour maps,
and computer generated and corrected LANDSAT alphanumeric data maps.
This paper presents a synoptic overview of the methodology, data anal-
ysis, results, and the application of results of an ongoing operational
land classification survey.
THE STUDY
Probably one of the leading reasons for failure of LANDSAT systems to
result in desired or accurate classification of surface resources is due
to falldown in quality of "ground-truth" data. A common fallacy is the
belief that the satellite data is not detailed enough for resource plan-
ning, and any use of the satellite can be accomplished with a minimum
knowledge of "ground-truth."
The satellite system, in fact, can provide detailed resource planning
data, often more detailed than desired. Clustering of this data requires
intimate knowledge of the surface resource situation on selected examples
of the resource groupings which are to be inventoried.
The use of low flight color infrared photography to enhance knowledge of
"ground-truth" as presented here originated with a problem which is
typical of many resource planning efforts; that is, a lack of sufficient
funds to do the thorough job of inventorying which the decisions to be
made warrant. Two project areas were included in this effort—the Goose
Lake Basin Study and the Five Columbia Counties Nonpoint Basin 8tudy,
both in the State of Oregon, USA.
The Goose Lake Basin Study was a recently completed project of USDA
agencies. Inventory of the surface resources included identification of
10 forest types, 8 range types, 14 cropland types, and water. The se-
lected categories were based upon the Study objective of identifying
irrigation needs and flooding, erosion, and sediment problems.
