identified and corrected, a mosaic was produced which exactly overlaid 
the data base when images printed by a Versatec electrostatic plotter 
were visually compared. It was found that the mosaicking process was 
very sensitive to "bad" control points, where the automatic correlation 
procedure had selected the wrong matching point. These matching points 
have to be located by comparing mean residuals and correlations of 
pairs of points, using subjectively-determined criteria. Inclusion of 
bad points resulted in local errors in the overlay. 
8. COSTS 
It is estimated that the direct cost of producing a half-state (six- 
frame) mosaic of approximately 5250 lines by 6100 elements would be on 
the order of $8,000, of which approximately $3,000 are computer costs 
at University user rates. This estimate excludes the cost of the data. 
While the cost of producing the mosaic is significant, the advantages 
of having current Landsat data in geographically-corrected form and 
registered to past data are also significant, particularly in reducing 
the cost of subsequent processing. 
9. ANTICIPATED USES 
The immediate application of the layered mosaic is for state-wide 
annual assessments of defoliation of forests (Williams et al. , in manu 
script.) We anticipate that the data will be of interest and value to 
a wide variety of land management and monitoring agents throughout the 
state, as well. Possible applications include: 
1. Monitoring of forest change. Two-thirds of Pennsylvania is 
covered in forest and much of the timber is approaching commercial ma 
turity. Together with increased mortality due to insect attacks, in 
creased mineral, coal and oil exploitation, and increased competition 
from other land uses, large scale changes in Pennsylvania forests are 
occurring and can be monitored by Landsat. We have research under way 
to determine optimum change-detection procedures using the data base 
as the mid-date in three-date analyses. 
2. Soil mapping. The value of Landsat data for improving existing 
soil maps in Pennsylvania is under investigation. Digitized soil maps 
can be easily overlaid on the data base and comparisons made without 
further rectification. 
3. Updating existing land use data bases. Techniques have been de 
veloped at ORSER for interfacing the Landsat data base (or derived data) 
with existing geographic information systems (GIS's). This involves 
the user defining a grid or polygon pattern (such as the grid-cell pat 
tern of an existing GIS). Classified Landsat data can then be extract 
ed through this pattern and area statistics summarized by polygons. 
Since most existing land-use data bases are at the same map projection 
as the Landsat data base, further expensive geometric correction should 
be unnecessary. 
4. Adding existing digitized topographic data, road networks, state 
forest boundaries, etc. It is known that several types of digitized 
data, either in raster form (e.g., digital terrain data) or in line or 
polygon form (e.g., roads, jurisdictional boundaries), are currently 
available. Many are already stored at the PSU Computation Center. 
Most of these are in projections conformant with the data base and 
could be added as data layers, if desirable. 
5. Constructing special purpose land cover maps. The cost of pro 
ducing land cover maps for small geographic areas such as watersheds,