Peijun
I presume by the "pseudo" cross semi-variogram, you mean the 'non co-located' cross semi-variogram as opposed to the more traditional co-located cross semi-variogram?
If so, the difference between the sill of your model and the nugget effect at zero is simply the classical covariance between your two variables. This is one way to calculate the covariance or correlation when you do not have co-located data for a more traditional statical calculation.
Interestingly, this cross semi-variogram is the only one which actually takes a non-zero value at zero distance!
Personally, I dislike the term "pseudo" which suggests that this is some sort of approximation to the "real" thing. Both approaches to co-kriging have strengths and weaknesses. So long as you are aware of these, you can gain valuable insight into your cross-relationships.
Isobel
Dear Dr. Goovaerts,
Thanks for reply.
I compute the pseudo cross variogram from bi-temporal images for change
detection. I found that when lag h=0, the pseudo cross variogram image
obtained highlights the change in the image. So, I would like to understand
why it happens.
Peijun
Peijun Li
Institute of Remote Sensing and GIS
Peking University, Beijing 100871
P R China
_____
From: Pierre Goovaerts [mailto:[EMAIL PROTECTED]
Sent: Thursday, September 21, 2006 2:15 AM
To: Peijun Li; [email protected]
Subject: RE: AI-GEOSTATS: pseudo cross variogram: h=0
Hi,
It just represents half the average squared difference between the values of
the two variables
measured at the same location.. I don't know why you compute the pseudo
cross-variogram
but, personally, I don't like this statistic, mainly because of the lack of
interpretation...
for example, it cannot take negative values, hence you can't differentiate
between positive and negative correlations. It is useful mainly when the two
variables have
not been measured at the same locations.
Pierre
Pierre Goovaerts
Chief Scientist at BioMedware Inc.
Courtesy Associate Professor, University of Florida
President of PGeostat LLC
Office address:
516 North State Street
Ann Arbor, MI 48104
Voice: (734) 913-1098 (ext. 8)
Fax: (734) 913-2201
http://home.comcast.net/~goovaerts/
_____
From: [EMAIL PROTECTED] on behalf of Peijun Li
Sent: Wed 9/20/2006 12:35 PM
To: [email protected]
Subject: AI-GEOSTATS: pseudo cross variogram: h=0
Dear List,
I recently use the pseudo cross variogram (PCV) for remote sensing
applications. However, I don't know what does the PCV reflect when lag h=0?
As we know, when lag h=0, the (univariate) variogram reflects the nugget
effect. Is there any similar meaning for PCV? Could you give me some
references related to PCV?
Thanks in advance for reply.
Peijun Li
Peking University
