In the course of working through my MODIS LST project and reviewing the steps that Imhoff and Zhang took as well has the data preparations other researchers have taken ( Neteler ) the issue of MODIS Quality control bits came up. Every MODIS HDF file comes with multiple SDS or multiple layers of data. For 
The MODIS package for R For people who work in GIS in R there has been a bit of challenge in working with data from Modis. I’ll use an example from my own work on UHI to illustrate. A while back I decided that I wanted to look at albedo data from MODIS. If you 
Introduction Zhang and Imhoff (2010) pdf here utilized NLCD impervious surface area (ISA), Olson biomes, and MODIS Land Surface temperature (LST) to estimate the magnitude of UHI in large cities across the US. Peng employed a similar approach in studying 419 large cities ( population greater than 1m ) around world. Peng’s work suggests a limit or 
Introduction Zhang and Imhoff (2010) pdf here utilized NLCD impervious surface area (ISA), Olson biomes, and MODIS Land Surface temperature (LST) to estimate the magnitude of UHI in large cities across the US. Peng employed a similar approach in studying 419 large cities ( population greater than 1m ) around world. Peng’s work suggests a limit 
Just a couple quick examples. Starting with 30 meter impervious surface Followed by MODIS Land cover ( “red” is urban ) And finally Day LST Google earth
I’ve started a tutorial on using the MODIS package in R the first few steps are here. While I wait on a release of the package I thought I would play around a bit with the MRT tool and see how it worked. Let’s recall where we are going. I have an inventory of around 
In the course of putting together data for my kriging project with the CRN stations, I got another idea related to a small but potentially important corner of the concerns over UHI in the global temperature index. For clarity I suppose I should make it clear that my position is that the UHI bias is 
Programmers like Oscar Perpiñán Lamigueiro are the reason I love R! Oscar is the maintainer of the rasterVis package and it in this post I’ll explain why it is must have package for anyone working with the raster package in R. My latest project is focused on the NOAA’s Climate Reference Network. The details can 
If you haven’t worked with the gWidgets package it’s worth some time exploring it which is what I’ve been doing for a little paleo project I’ve been working on. After struggling with the few demos and tutorials I could find I went ahead and bought the book: Programming Graphical User Interfaces in R. Luckily the 
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
