All,

I will like to get your input in a project that I am working on. In

advanced thank you so much for all your comments.

So, I am trying to develop some linear models that explain some water

quality parameters, using the input from different remote sensing

satellites, in a lagoon that approximately has surface area of

approximately 19000 m2. For that purpose, I collected some in-situ

measurements at 12 randomly selected locations inside the lagoon. I did

some ordinary kriging to calculate what is happening inside the pond (given

the fact that I only collected data at 12 points inside the pond). Now I am

at the stage where I can start developing those linear models.

Based on that, my question is the following - Should the linear models be

constructed using only the collected data, or should I develop those models

also considering the interpolated data. If the last scenario is the most

preferable option, should I perform a point value extraction using the

centroid of a grid?

Here is some (not all) of the literature that I been reading to complete

this project.

Giardino, C., Pepe, M., Brivio, P.A., Ghezzi, P., and Zilioli, E.,

“Detecting Chlorophyll, Secchi Disk Depth and Surface Temperature in a

Sub-Alpine Lake Using Landsat Imagery”, The Science of the Total

Environment, Vol. 268, 2001, pp. 19-29.

Kloiber, S.M., Brezonik, P.L., Olmanson, L.G., and Bauer, M.E., “A

Procedure for Regional Lake Water Clarity Assessment Using Landsat

Multispectral Data”, Remote Sensing of Environment, Vol. 82, 2002a, pp.

38–47.

Kloiber, S.T., Brezonik, P.L., and Bauerc, M.E., “Application of Landsat

Imagery to Regional-Scale Assessments of Lake Clarity”, Water Research,

Vol. 36, 2002b, pp.4330-4340.

Thank you so much for all your input.

Cheers

Juan

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