The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Voi XXXVII. Part B4. Beijing 2008 
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4. GRADED PRODUCTS 
The image service can be dynamically updated. Imagery can be 
added, and various processes and parameters can be changed 
without stopping the published image services. This is 
important for the use of the system in time-critical applications, 
and also enables the creation of a graded product. In this 
method, a preliminary image service is created based on the 
best available parameters and when the parameters and models 
are refined, they are updated within the image service definition. 
This provides a preliminary product as soon as the imagery is 
available on a server. For example, an image service can be 
created based on imagery from a digital camera as soon as the 
data is available. The initial orientation for orthorectification 
may come from preliminary orientation parameters available 
from the GPS/IMU. The initial radiometric processing could be 
default values. Such image services can be created as soon as an 
aircraft has landed and made available to users—when the value 
of the imagery is highest for applications, such as emergency 
response. As different steps in the orthoimage production flow 
are performed, the processes and the parameters in the image 
service definition are updated. For example, after performing an 
aerial triangulation the orientation parameters may be updated 
increasing accuracy. After updating the DTM the accuracy 
further increases. Similarly, the radiometric processing or pan- 
sharpening parameters can be updated as improved values 
become available. The initial product may not use seamlines 
and after the system has generated the seamlines this can be 
used to create a more seamless product. Thereby the graded 
product improves over time. 
5. QUALITY CONTROL 
The methodology of ArcGIS Image Server not only enables use 
of the imagery sooner which increases the value of the imagery, 
but it is also used for efficient quality assurance processes and 
is an integral part of Quality Control (QC). 
In most production workflows, QC becomes a major component 
of the total workflow. Some of the QC can be performed in an 
automated manner, for example, in analyzing the histograms of 
the output images, while other steps must be viewed by 
operators to check the accuracy of control points or the 
junctions of seamlines. If these QC processes require the final 
product to be produced, then the processing must be repeated if 
any errors are found. Since the processing with ArcGIS Image 
Sever is performed on the fly, the QC steps can be performed 
prior to the extensive processing. Corrections can be updated in 
the database the corrections quickly reviewed. The integration 
of ArcGIS Image Server into multiple GIS client applications 
further enables the implementation of geospatially enabled QC 
processes. With the ability to serve both the imagery and QC 
tasks on the web, QC can be checked by the end user of the 
product prior to production and delivery. 
Such dynamic image services with on-the-fly processing have 
significant advantages over image servers that only serve pre 
generated and mosaicked static imagery. Dynamic imagery 
servers that are driven from such databases and generate 
products directly from the base imagery can be expected to 
quickly augment the traditional static image servers that require 
the pre-generation of large images or lots of individual tiles. 
ArcGIS Image Server can easily be scaled to serve hundreds of 
simultaneous users. To scale to very large numbers of 
simultaneous users map caches are used. Web applications that 
provide interactive display capabilities make requests to servers 
using predefined tiles that are assumed to be static. Such static 
tiles can be stored on the web servers as small static image files. 
Such static tiles can be easily distributed on the Web and are 
utilized by edge servers to reduce server requests, data transfers 
and speed so up applications. Many web applications also cache 
tiles locally to further reduce requests to the server and provide 
faster interaction in areas that the user has already visited. Such 
static tiles can be generated in advance and stored on the Web 
server, but for large project would require extensive processing 
that can take a long time. With ArcGIS Server 9.3, such tiles 
need not be pre-generated. Instead they can be generated on 
demand when a user first accesses an area at a specified 
resolution. As the majority of high resolution requests to servers 
repeatedly cover only a small percentage of the full area, the 
high performance is maintained without the need to pre 
generate high resolution caches for the complete area. Such 
caching can be driven directly from ArcGIS Image Server, 
where the cache is generated directly from the original image 
data. Caches therefore have significant advantages over 
solutions that utilize large static files that can not utilize web 
caching infrastructures and need to be pre-generated. 
7. ORTHOIMAGE PRODUCTION 
Although dynamic serving of imagery directly from the source 
and using on-demand caches have many advantages, there is 
currently a demand to create orthoimages as tiles that conform 
to a specific grid or map sheet layout. Many large orthoimage 
mapping projects currently specify the creation of image 
products as tiles in a range of formats including TIFF, NITF, 
and JPEG 2000. It can be expected that the requirement to 
deliver such pre-generated tiled products will continue as this 
delivery mechanism is required by many organizations and 
provides a clearly defined product that conforms to the pre 
defined standards. Therefore, the need will remain for 
companies to produce large sets of tiled products. With the size 
and number of these projects increasing, production companies 
are being challenged to create very large numbers of such tiled 
images. 
With ArcGIS Image Server, the actual processing of the pixels 
is performed on demand as required for a user’s specified area 
of interest, resolution, and projection. This processing can be 
performed in near-real-time for screen sized requests as a user 
zooms into a specific area. Large image requests, that define the 
extent of a map sheet or large format plot at high resolution, can 
also be made. This feature can be used to process and extract 
large tiles of imagery from the server. The output can be written 
to a number of formats such as GeoTIFF or JPEG 2000. As 
with the smaller requests, the important image level metadata 
can also be derived as output. This metadata is extensive and 
includes the mosaic polygons that define which part of the 
output comes from which input raster, as well as the processing 
performed and metadata from the original imagery. 
8. PRODUCTION SCALING 
An important scalability feature of ArcGIS Image Server is its 
ability to process multiple requests simultaneously and spread 
the processing load over multiple service providers. The server