280
A. Simms
The soft-shell clam biology, water quality, and landuse data are stored as
points. The clam biology database represents clam samples taken at the center of each
grid. Individual clams were measured (length and width) and weight. For each clam, the
data was stored as a single record in the point database. This meant that a single location
has more than one record. However, the points represent a sampled area of
approximately 0.25m sq. However, before any descriptive analysis or mapping can be
performed on this point data the information must be converted to densities or counts
for each polygon in the 100 x 100m grid. The water quality points are permanent sample
stations (Fig. 2) that will be used for environmental monitoring. These data are stored as
x, y coordinates and as an ArcView™ polygon vector shape file. Raster Thiessen
polygons are formed by a proximal mapping function in Spatial Analyst 1.0 (ESRI,
1996), and the shape of the polygon is determined by the distribution of the points. A
polygon is formed around a point by constructing boundaries halfway between a point
and its nearest neighbor. The result is a series of irregular shape polygons (converted to
vector shape files) that can be used to map water quality within a vector data structure
(refer to Fig. 4). The reason for this approach is twofold; first there are some
observations missing from the database that would make the point distribution too
sparse for contouring by spatial interpolation algorithms. Second, if the database is
transferred to a system without the capability to build Thiessen polygons or create a
continuous surface by interpolation the existing polygons could be used for mapping
water quality attributes.
A GIS Approach to Aquaculture Site Assessment
The data collected on clam biology, hydrology, landuse, and water quality as well as the
inclusion of aerial photography and a digital topographic map provides the information
required for an aquaculture site assessment. This evaluation should address issues on the
suitability of the environment, potential competing landuse, and the sustainability of the
soft-shell clam resource. The following sections present a preliminary analysis of the
field data whereby a GIS approach is used to map and analyze the data in terms of:
1)
2)
the physical site characteristics and landuse
water quality
and
3) the soft-shell clam resource
The clam resource will be evaluated in terms of spatial variability in the density of
various size class distributions and population characteristics.
A. Simms
The soft-shell clam biology, water quality, and landuse data are stored as
points. The clam biology database represents clam samples taken at the center of each
grid. Individual clams were measured (length and width) and weight. For each clam, the
data was stored as a single record in the point database. This meant that a single location
has more than one record. However, the points represent a sampled area of
approximately 0.25m sq. However, before any descriptive analysis or mapping can be
performed on this point data the information must be converted to densities or counts
for each polygon in the 100 x 100m grid. The water quality points are permanent sample
stations (Fig. 2) that will be used for environmental monitoring. These data are stored as
x, y coordinates and as an ArcView™ polygon vector shape file. Raster Thiessen
polygons are formed by a proximal mapping function in Spatial Analyst 1.0 (ESRI,
1996), and the shape of the polygon is determined by the distribution of the points. A
polygon is formed around a point by constructing boundaries halfway between a point
and its nearest neighbor. The result is a series of irregular shape polygons (converted to
vector shape files) that can be used to map water quality within a vector data structure
(refer to Fig. 4). The reason for this approach is twofold; first there are some
observations missing from the database that would make the point distribution too
sparse for contouring by spatial interpolation algorithms. Second, if the database is
transferred to a system without the capability to build Thiessen polygons or create a
continuous surface by interpolation the existing polygons could be used for mapping
water quality attributes.
A GIS Approach to Aquaculture Site Assessment
The data collected on clam biology, hydrology, landuse, and water quality as well as the
inclusion of aerial photography and a digital topographic map provides the information
required for an aquaculture site assessment. This evaluation should address issues on the
suitability of the environment, potential competing landuse, and the sustainability of the
soft-shell clam resource. The following sections present a preliminary analysis of the
field data whereby a GIS approach is used to map and analyze the data in terms of:
1)
2)
the physical site characteristics and landuse
water quality
and
3) the soft-shell clam resource
The clam resource will be evaluated in terms of spatial variability in the density of
various size class distributions and population characteristics.