[R-sig-Geo] Pre-processing remotely-sensed data and calculating MSAVI2 in R

[Keren Raiter]

Hello, I'm needing to calculate the modified soil-adjusted vegetation index (MSAVI2) for data captures for different years. The imagery I have to work with is plane fly-over imagery from 2010-2012 (the baseline), and GeoEye (or in some cases WorldView2) (the impact data). I know that comparing plane data with satellite data is very problematic but this is what I need to do for now. I have already calculated MSAVI2 for the GeoEye data including calculating the L value based on the gain, abscal factor, effective bandwidth and offset and then calculating the top-of-atmosphere reflectances (TOARs) based on Earth-Sun distances and solar exoatmospheric irradiance, before then calculating MSAVI2 based on the TOARs - i've done this manually with raster calculator and the i.vi tool in QGIS, but now am looking for a workflow to do this with script in R; plus to deal with the plane fly-over imagery too. Does anyone have recommendations for the most appropriate packages and functions within them for: - reprojecting, resampling and co-registering the different datasets - clipping / masking the datasets - because the different datasets cover different geographical extents so I need to look only at the areas that are common to both, and also because I'm just focusing on one vegetation type which i have a polygon (vector) layer for. - calculating MSAVI2 and comparing MSAVI values from different years - mapping results. If anyone could also please guide me on how to find example scripts that cover some or all of this workflow, or would be willing to share their code on this with me, I'd be eternally grateful! I have worked with rasters in R before but that was in the days of raster package and I'm not so sure what's the best tool suite for the current project. Thank you, Keren
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