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TitleMulti-temporal scene analysis: a tool to aid in the identification of cartographically significant edge features on satellite imagery
 
AuthorGuindon, B
SourceCanadian Journal of Remote Sensing vol. 14, no. 1, 1988 p. 38-45, https://doi.org/10.1109/IGARSS.1988.569620
Year1988
Alt SeriesEarth Sciences Sector, Contribution Series 20040676
Alt SeriesRESORS 1065208
PublisherIEEE
Documentserial
Lang.English
Mediapaper; on-line; digital
File formatpdf
Subjectsgeneral geology; geophysics; remote sensing; satellite imagery; satellites; cartography; computer mapping; mapping techniques; remote sensing
Illustrationssketch maps; Landsat images; equations
AbstractAutomated cartographic mapping is a potentially important use of high resolution satellite imagery. In such an application, it is necessary to extract edge and line features and then identify those of cartographic significance. This process is complicated because individual images contain a myriad of transient features, such as surface-cover texture. In addition, features of significance, such as road networks, may appear intermittent because they traverse areas that exhibit comparable reflectance.
On the positive side, those features of cartographic interest can be expected to exhibit a level of invariance when viewed in a temporal sequence of scenes. In this paper, it is proposed that multi-temporal analysis be considered as an auxiliary tool. In such a scenario, comparison, of the edge and line feature content of coregistered image sets would be undertaken with a view to retaining only those features possessing a predefined level of scene-to-scene consistency.
A modified version of the edge detection algorithm of Nevatia and Babu (1980) has been developed and implemented. This approach is of particular value since each edge is characterized by two attributes, namely, magnitude and direction. In addition, spatially contiguous edge pixels can be logically linked together to form chains. Two multi-temporal editingmodes are proposed and evaluated, one based on per pixel comparisons between scenes and one based on the degree of chain coincidence. Both perform well in suppressing transient feature when applied to a Thematic Mapper data set covering a portion of southwestern Ontario. However, chain editing has two distinct advantages: a robustness to image registration errors; and an ability to overcome some of the intermittency problems in linear features, such as roads.
GEOSCAN ID217478

 
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