Key Words: Remote Sensing, Resource
Management, Environmental Management, Earth
Information Lifecycle, Satellite Sensors,
Airborne Sensors, Data Extraction Tools.
Application Readiness of Remote Sensing
Technologies
Historically, we have seen relatively limited
effective application of remote sensing to
the ever more acute resource and environment
management problems. Subsequent sections of
this paper examine the main factors that have
limited the acceptance of remotely sensed
data and identify the improvements
anticipated over the next few years. The key
factors causing these limitations include:
• Availability, resolution and quality of
source data;
• Availability of affordable digital data
products;
• Availability of cost-efficient tools to
populate and update data bases with
geographic information extracted from
imagery;
• Availability of data base structures to
efficiently manage locationally related
raster, vector and attribute data; and
• Availability of affordable computer
technology to store, access, process and
share the vast amounts of data.
While individually each of these factors has
contributed in rendering certain applications
of remote sensing economically or technically
less feasible, the compounded effect has
constrained the utility of remotely sensed
data as a whole (see Figure 2). However,
significant advances are taking place in all
of the above areas, to the extent that
substantially increased applications of
remote sensing to large scale resource and
environmental management issues are to be
expected.
POTENTIAL
REMOTE
SENSING
APPLICATIONS
DATA
SOURCE
1
I ,
I
DATA I
DISTRIBUTION
TOOLS
EFFECT IF ALL FACTORS
ARE REDUCED BY 507.
L
1
DATA
BASE
COMPUTATION
AFFORDABILITY
AC IUAL
APPLICATIONS
Data Sources - Satellite Sensors
For many years now weather satellites such as
TIROS-N, GOES, Meteosat and GMS, have proven
to be a stable source of meteorological data
for operational applications.
Looking at earth resource satellites,
however, as recently as 1989 the number of
accessible remote sensing satellites actively
imaging the earth's surface was still rather
limited (e.g., Landsat-5, SPOT-1, MOS-1). Of
these satellites, Landsat was under threat of
cancellation, SPOT-1 was the only satellite
offering substantially better than 30 m
resolution, and none of these sensors can
penetrate cloud cover. In addition, when one
combines coverage frequency of these
satellites with the cloud cover
characteristics, the average elapsed time
between two useful images of the same region
can be considerable. This combination of
factors does not generally encourage policy
makers to embark on resource management
programs which rely heavily on satellite
remote sensing.
However, this situation is changing rapidly.
First, the Landsat program is surviving and
Landsat-6 is scheduled for launch in mid-
1991. Second, SPOT-2 was launched in January
1990 and plans for SPOT-3 and SPOT-4 are well
underway. And third, a wave of radar
satellites (Europe: ERS-1 and -2, Japan:
JERS-1, Canada: Radarsat, USSR:
Radarsatellite) are expected to be launched
over the next four years. Because of the
increasing number of satellites, the cloud
penetration characteristics of radar, and the
spread in political nature of the countries
controlling the satellites, the combined
effect dramatically increases the effective
coverage frequency and data accessibility for
all regions of the earth, and improves back
up possibilities if a satellite fails.
In addition, the parts of the spectrum sensed
by these new instruments collectively will
accommodate a broader variety of
applications. Programs now on the drawing
board, such as the U.S. Earth Observations
System, the European Polar Orbiting Platform,
and the Canadian Earth Environment Satellite
Initiative (EESI) indicate this trend towards
more data sources is likely to continue.
Data Sources - Airborne Sensors
While the spatial resolution of resource
satellites imagery (generally 10-30 m) is
sufficient for applications at the global and
national level, and certain applications at
the regional level, it becomes less suitable
as the cultural density increases towards the
local level.
99-5651-D2R1\CD
Figure 2 Factor Impact on Remote Sensing
Data Utility
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