Cross-Matching Multiple Spatial Observations and Dealing with Missing Data

Details Cross-Matching Multiple Spatial Observations and Dealing with Missing Data Cross-Matching Multiple Spatial Observations and Dealing with Missing Data

2007-01-26

arxiv.org/abs/cs/0701172v1

Computer Science

Databases

Scientific paper

Cross-match spatially clusters and organizes several astronomical point-source measurements from one or more surveys. Ideally, each object would be found in each survey. Unfortunately, the observation conditions and the objects themselves change continually. Even some stationary objects are missing in some observations; sometimes objects have a variable light flux and sometimes the seeing is worse. In most cases we are faced with a substantial number of differences in object detections between surveys and between observations taken at different times within the same survey or instrument. Dealing with such missing observations is a difficult problem. The first step is to classify misses as ephemeral - when the object moved or simply disappeared, masked - when noise hid or corrupted the object observation, or edge - when the object was near the edge of the observational field. This classification and a spatial library to represent and manipulate observational footprints help construct a Match table recording both hits and misses. Transitive closure clusters friends-of-friends into object bundles. The bundle summary statistics are recorded in a Bundle table. This design is an evolution of the Sloan Digital Sky Survey cross-match design that compared overlapping observations taken at different times. Cross-Matching Multiple Spatial Observations and Dealing with Missing Data.

Affiliated with

Also associated with

No associations

Rating

Cross-Matching Multiple Spatial Observations and Dealing with Missing Data does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Cross-Matching Multiple Spatial Observations and Dealing with Missing Data, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Cross-Matching Multiple Spatial Observations and Dealing with Missing Data will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-568225