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; ai-geostats@jrc.it 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: ai-geostats@jrc.it 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
<<attachment: winmail.dat>>
