Environmental Engineering Reference
In-Depth Information
be carefully calibrated prior to use, and laboratory results should be checked for consist-
ency. QA/QC sample results should also be compared to coni rm data quality.
Another challenge is to attempt to sample the range of conditions that may be present or
may occur. For example, is sampling primarily conducted when river l ows are low? Did
sampling catch storm-related runoff or merely base l ow? Do soil tests rel ect the entire
range of variation in soil properties? It is important to recognize that samples represent a
tiny fraction of the whole and, accordingly, it is highly unlikely that maximum or mini-
mum values of any parameter would be found.
Yet another aspect to consider is whether the analytical method is sufi ciently sensitive
to detect levels of concern. Time of sampling may also be important. Could the time of day
the sample was taken affect results? Is sampling always being carried out at the same time
of the day? Streams and rivers fed by glaciers or snow melt vary diurnally in their dis-
charge and quality. Also, dissolved oxygen in surface water is typically lowest in the morn-
ing and highest in the late afternoon.
8.6 THE USE OF REMOTE SENSING TECHNIQUES AND
GEOGRAPHIC INFORMATION SYSTEMS
Remote sensing is the interpretation of airborne or satellite imagery to provide a picture
of selected aspects of physical geography, such as topography, habitat distribution, settle-
ments, or mangrove forest areas. Geographic information systems (GIS) are computer
systems that can store, integrate, analyze, and display spatial data. Two important develop-
ments have helped to reduce the complexity of spatial analysis and to allow remote sensing
techniques and GIS to become standard applications in environmental assessment. First,
due to advances in computer and software technology, GIS have become powerful, user-
friendly, and affordable. Second, due to improvements in remote sensing technologies, the
availability and quality of digital data sets have increased exponentially. The current state
of computer technology and available existing data sets (commercially available satellite
imagery such as Landsat, Spot, Aster, IKONOS, or Quickbird) allows the EIA practition-
ers to apply remote sensing techniques and GIS on a routine basis.
GIS offers a unique platform for dealing with the spatial properties of a mining project.
Most environmental baseline data have a spatial attribute, and they lend themselves to
be analyzed using GIS and presented in maps. Maps are powerful analytical tools if used
appropriately. The i rst GIS evolved in the late sixties, and entered EIA applications in the
mid seventies. In 1972 computerized overlays of spatial data were i rst used in the siting of
power lines and roads (Munn 1975). One of the i rst full-scale GIS was applied to the envi-
ronmental assessment of a dam on the river Thames (Grifi th 1980).
While GIS is now widely applied, its use often remains limited to some basic functions
such as map production, classic overlay or buffering (Joao 1996). Standard application of
GIS analysis include mapping of topography (elevation and slopes), habitats, in particular
mangrove areas, surface water bodies (rivers, lakes, and wetlands), coral reefs and other
shallow marine habitats, settlement areas, and road networks. Implementation of GIS,
however, does not always fully utilize the analytical capacities that GIS offers, possibly
because the spatial analysis and modelling requires a higher level of expertise, than is nor-
mally found among EIA practitioners.
Although use of GIS and the resulting maps can be very powerful both in their pres-
entation as well as an analytical tool, EIA practitioners need to recognize potential con-
straints and pitfalls associated with GIS application, examples of which are illustrated in
GIS have become powerful, user-
friendly, and affordable.
Most environmental baseline
data have a spatial attribute,
and they lend themselves to be
analyzed using GIS.
 
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