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
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.
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.