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i have been looking around in gisarea.com especially in RS-GIS Area Sharing Section, sometimes i found a programs/tutorial with many link (part by part). i think we can start to upload a torrent for any file, we can start with public torrent maybe we can upload in TPB or Kickass torrent, its look like more easy to share via p2p, single link and file can be eternal in internet (if have seeder). anyway sharing via p2p we can resume our donwload anytime. this is just a suggestion because some of book/program in RS-GIS Area Sharing is difficult to find.

i have been looking around in gisarea.com especially in RS-GIS Area Sharing Section, sometimes i found a programs/tutorial with many link (part by part). i think we can start to upload a torrent for any file, we can start with public torrent maybe we can upload in TPB or Kickass torrent, its look like more easy to share via p2p, single link and file can be eternal in internet (if have seeder). anyway sharing via p2p we can resume our donwload anytime. this is just a suggestion because some of book/program in RS-GIS Area Sharing is difficult to find.

Hi, I'm using Idrisi Selva to do an unsupervised (ISOCLUST) classification of Landsat TM images. My study area is at the juncture of two Landsat scenes and it spans two UTM zones. I radiometrically corrected each band of each image in R, then mosaicked each band in ArcGIS v10, then clipped the mosaicked bands to the boundary of my study area. I exported the data to ASCII, then imported three bands (R, NIR, MIR) to Idrisi Selva. Using ISOCLUST, I specified that I wanted 10 classes with a minimum class size of 30 pixels. The problem is that every few minutes, I would get an error that said "Variance/covariance matrix is singular. Check for perfectly correlated variables or variables with zero variance." This message was immediately followed by: "Inverse matrix process failed." I found that if I sat there and clicked through the errors when they popped up every few minutes, the classification worked (at least from a quick visual assessment). My questions are: 1- Why is this error occurring? 2- How is the variance/covariance matrix generated? 3- Did the unsupervised classification work in spite of the error messages? Any help would be really appreciated.