FREE ESSAY ON SPATIAL DATA ACQUISITION

SPATIAL DATA ACQUISITION

Title of Lecture: Spatial data acquisition and system modeling: notes from the field 
and the lab.
Name of Lecturer: Philip Graniero
Department of Lecture: Earth Sciences
Date and Time of Lecture: January 13th, 2000 at 4:30pm
Purpose of Research Project:
The primary purpose of the project is to use model simulations to forecast spatial
patterns among various species in the environment. By comparing current situations with
test results, Graniero hopes to have the ability to predict spatial patterns for species
in the environment. This will give environmentalists and scientists alike the ability to
prevent specie disaster and to study such areas as future habitat.
Description of Research/Technology used:
Graniero's first step involved measuring the earth's topography, under the bedrock of the
surface. This experiment took place in Newfoundland, Canada. To do this he took a random
sampling scheme. These schemes were tested at a density of 40 points per hectare. In
order to bring the most precise and comprehensive data to the table, such technologies as
mobile computers and GPS systems were used. The field in which was being tested proved to
be very difficult to measure due to the changing system and the high demand of physical
resource. His objective still remained the same though, to take this data and run a model
that would enable him forecast spatial data on various species. The model he used was
known as Cellular Automation (CA). The models properties were as follows: a finite set of
discrete states and a state transition rule where the next state is determined by;
current cell state, states of the nearest neighbours, and the state of other layers. The
model worked in specific steps. First, a spatial structure was built. Second, data was
collected from it. Third, the simulation of different collection agencies were put forth.
Fourth, the model information was compared to the behaviour of actual systems. Fifth, the
model was repeated with random initial conditions. Thousands of trials were done at this
point. This model is often referred to as a "virtual lab". When the information was taken
at the conclusion of each test, it was sent to processing units where it was studied in
the form of a grid. These grids were then used to study the spatial patterns of various
species. Such future models will be more complex and more specific, thus showing species
habitats and migratory trends. Adjusting the variables in the model can allow scientists
to measure such activities as the population density of a species. Through the experiment
there were three experiment sets. These included populations, disturbances, and resource
mapping. The resource spatial structure also varied from uniform, smooth, and "patchy"
environments (soil and forest types). 
Conclusion:
This information is very valuable to environmentalists and society in general due to the
fact that it "looks-out" for species that may be in danger and monitors the move from one
territory to another over a given time frame. Allowing scientists to predict the habitat
and density of species in given areas with such models keeps humans aware of the impact
they may have. This helps protect the future of species and insures that humans don't
interfere with its habitat as well. In conclusion, the model is very useful and as it
grows and becomes more sophisticated it should prove to be a valuable resource to
environmental scientists.
Bibliography
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