Download Document 75402

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project

Document related concepts

Map database management wikipedia, lookup

Geographic information system wikipedia, lookup

GIS and environmental governance wikipedia, lookup

Distributed GIS wikipedia, lookup

Transcript
International Archives of Photogrammetry and Remote Sensing, Vol. 34, Part 4/W5
“Challenges in Geospatial Analysis, Integration and Visualization“, Athens, Georgia, USA 29-31 October, 2001
EVALUATION OF REMOTELY SENSED IMAGES FOR THE
DEVELOPMENT OF COASTAL ZONE DATABASES
Roy Welch and E. Lynn Usery
Center for Remote Sensing and Mapping Science
Department of Geography
The University of Georgia
Athens, Georgia, USA 30602
[email protected]
[email protected]
KEY WORDS: image data, coastal zone databases, GIS, feature extraction
ABSTRACT
The Center for Remote Sensing and Mapping Science and the Department of Geography at The University of
Georgia, Athens, Georgia are working with the National Imagery and Mapping Agency to develop
methodologies for using remotely sensed data in conjunction with existing map information in a GIS
environment for littoral warfare data (LWD) and related database applications. High priority features that can be
extracted from sensor data will be identified using a combination of interactive and automated feature extraction
techniques to prepare LWD products in a time-critical GIS environment. As part of this study, a matrix is being
prepared that will provide probabilities for extracting LWD features from image/map sources in individual,
multiple and fused forms. A goal of this research is to develop LW databases in conjunction with a knowledge
base and rules that will permit the features extracted from remotely sensed imagery to be retrieved and
represented in the appropriate manner on cartographic products of 1:5,000 to 1:50,000 scale. It is anticipated
that the methods developed using data for known test sites will be applicable to unknown sites around the world.
80