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m applications 
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launched the 
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ving data from 
(TM) and the 
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to begin a 
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research and 
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Figure 2. The 
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to a Gandalf 
ts one to work 
al. The next 
2, a DEC VAX 
1.6 gigabytes 
:put subsystem 
on. There are 
¡ach with two 
speed graphics 
processing, there is a Graphics Processor. One can 
connect to a remote GIS through an automatic dial-up 
device. LDIASl and LDIAS2 are connected together 
via an Ethernet network, two dual-ported disks, and 
a dual-ported tape drive unit. The two computers 
are not clustered together because: a) this was not 
an available product from DEC when the project 
started; b) the two computers are at different oper 
ating system versions. The VMS operating system for 
LDIASl is changed with each release from DEC; that 
for LDIAS2 is changed with less frequent releases 
from Intergraph Corporation. 
The third computer in LDIAS is a DEC VAX 11/730 
which is the control computer for the Fast Multi 
dimensional Processing System (FMPS). FMPS is the 
batch production system for full scene analysis. 
Interactive analyses are conducted on LDIASl and 
LDIAS2. FMPS was developed for CCRS by Canadian 
Astronautics Limited (CAL). FMPS has an Aptech 24- 
megabyte-per-second bus with a mass memory of 3 
megabytes. Attached to this bus are the VAX 11/730, 
a 100-megaflop array processor (Star Technologies 
ST-100), a CAL Parallelepiped Preprocessor Unit 
(PPU), and two 256-megabyte disk drives which are 
dual-ported with LDIASl. FMPS also has an Ethernet 
connection to the other computers. 
Although not formally part of the LDIAS project, 
there are three DEC AI VAXstations connected to the 
same communications network. Each workstation has a 
71-megabyte disk, a tape cartridge unit, and a bit 
mapped display. These workstations use VMS as the 
operating system and support rapid development of 
expert systems in Prolog or Lisp. The expert sys 
tems discussed in section 5 make use of this 
hardware. 
The system architecture is intended to support the 
software functions briefly described below. 
2.3 Major Software Functions 
The LDIAS is used to support research and develop 
ment in remote sensing, computational vision, sensor 
development and GIS integration, and to support the 
development of applications for renewable and non 
renewable resources. This latter group use one of 
the two analysis workstations. A workstation 
consists of an image display, a map display, a 
digitizing tablet, and two terminals. The work 
station is operated for applications development by 
a team of two: a resource expert (user), and an 
analyst. The analyst is knowledgeable about the 
software, hardware, and analytical procedures. 
The primary remote sensing inputs to LDIAS are 
geocoded TM computer compatible tapes (CCTs) from 
the MOSAICS system (Link et al 1985). These geo 
coded products correspond to four 1:50,000 map 
sheets in the Universal Transverse Mercator (UTM) 
projection. The TM scan lines are oriented east- 
west with north at the top of the corrected image. 
The image has been resampled on a regular, 25m, UTM 
grid with a 16-point truncated sine function. 
Digital maps come from provincial agencies or from 
the Surveys and Mapping Branch of our department. 
The LDIAS software is run using a supervisor 
program. The user is presented with the Master Menu 
shown in Table 1. Each item in this Master Menu is 
itself a menu of tasks, or menus, or both. The user 
can obtain help in the form of on-line documentation 
at any step, even if he or she is in the middle of a 
program. All user responses to program queries can 
be recorded and subsequently used to produce an 
automatic sequence of task executions; that is, a 
batch command file. A man-machine interface was 
developed to support bilingual dialog (English and 
French), scrolling of user sessions on the terminal, 
interactive or batch modes, standard prompts, 
on-line help, and effective error recovery. An 
image data base structure, UNIDSK, was implemented 
to support images with 8000 by 8000 pixels, and 21 
channels, each of which could be quantized from one 
bit to 128 bits in integer or real formats. In 
order to support our research, flexibilty in the 
software was very important. LDIAS currently con 
tains more than one million lines of code, 
documented and debugged. 
TABLE 1 
LDIAS MASTER MENU 
Label Description 
A Input 
D Radiometric Corrections 
F FMPS - Fast Multidimensional 
Processing System 
G Geometric Corrections 
I Generate Spatial Texture 
J Acquire Spectral Signatures 
K Perform Segmentation 
L Classify and Cluster 
M Map Input/Output 
N Filter and Enhancement 
0 Diagnostics 
Q Accuracy Assessment 
S Classification Filtering 
U Utilities 
Z Output 
The structured design and analysis methodology of 
Gane and Sarson (1977) was used for linking 
research activities and software development. 
Logical data flow diagrams for all of the software 
are on-line. The software is managed through a 
central computer repository. A major part of the 
documentation is automatically extracted from 
software for on-line help and generation of 
technical memoranda. In this way, we avoid most 
incompatibilities between software versions and 
corresponding documentation versions. For some 
pixel processing operations, we have found a stan 
dard program shell or skeleton useful. This image 
processing skeleton is integrated with an editor 
with knowledge of the computing language, FORTRAN 
77. Through these techniques the LDIAS project 
team's software productivity has been greatly 
enhanced. 
An analysis project begins with the user specify 
ing their desired outputs. This specification 
establishes the most probable analysis procedure. 
The TM or MSS imagery are read in, together with 
digital terrain models if they exist. Corrections 
can be applied for radiometry, atmospheric effects, 
viewing geometry, image scale, and output project 
ions. Identification of training and test areas can 
be made on the display of the TM imagery, from paper 
maps or photographs, or from GIS files. For TM, it 
is essential to utilize spatial features, in 
addition to the spectral features. Segmentation can 
be performed using these spatial and spectral 
features. Parametric and non-parametric, supervised 
or unsupervised, classifiers can be used. The LDIAS 
supports up to 256 classes at any one time for 
remote sensing imagery. There is a wide range of 
enhancement tasks available. The outputs may be 
digital updates to the GIS, digital or paper maps, 
area summaries, or photographs. At each stage in 
the user session, the user or analyst can assess the 
accuracy. The theoretical estimate of the classifi 
cation accuracy to be achieved, for example,