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 
236