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Proceedings of Symposium on Remote Sensing and Photo Interpretation

the decision model used by the USDI Fisheries and Wildlife Service. The
model shown is, at present, conceptual and represents the work of FWS
personnel. ERIM and FWS are working jointly (under NASA funding from
ERTS and Skylab programs) to develop remote sensing inputs to this model.
Figure 3 shows at the left, inputs to the user model. Astrisks indicate
those types of information obtained from low altitude aircraft-borne observers
(supplemented by ground observations), and data potentially derivable from
remote sensing techniques. The goal of the user model is to estimate the fall
population of mature and immature birds. Old birds are estimated by low
altitude aerial survey and ground counts of nesting pairs on a sampled basis.
Estimates of summer mortality are also made from ground observations and past
experience. The number of breeding pairs, coupled with the May and June pond
numbers are used to estimate the number of new ducks. This information is
augmented by the number of broods obtained on a sampled basis from ground
Hunting regulations are defined based on the population size, the
estimate of harvesting of ducks in Canada, and the carrying capacity of the
habitat. Remote sensing has an impact in assessing capacity of habitat,
especially in the assessment of quantities and distribution of natural
As an example of the annual production equation, Figure 4 shows a linear
equation in several variables which FWS personnel have derived to predict new
production of mallard ducks. The coefficients of the model are derived on
the basis of historical experience. If similar models can be constructed
for other species, then the general user-decision model of Figure 4 can
become more operational.
My assessment of current multispectral processing equipment systems to
meet the needs of keeping pace with multispectral data acquisition which
occurs typically at rates of hundreds of kilopixels/sec or megapixels/sec is
given below:
1. Sensor capability exceeds processing capability by large factors.
2. Digital and analog implementations of present techniques will not
keep pace with the needs of most operational-prototype informa
tion systems.
3. Multiple digital computer approach is probably too costly
4. Implementation of special purpose parallel processing with improved
techniques appears promising from both throughput and cost aspects
but requires development.
Despite work on faster techniques, presently available conventionally
organized digital computers are too slow (with current algorithms) by
orders of magnitude so that even many computers per sensor are still