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Is there a method to create monthly LST images from combining MOD11A2(8days) product?

The MOD11C3 product which is delivered monthly has larger spatial resolution than MOD11A2.

Im trying to create a script in python to do that but it seems to be above my coding skills

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2 Answers

up vote 2 down vote accepted

You're talking about temporal compositing. This is a major part of MODIS data because the data is collected so frequently (every 36 hours at most). What's tricky is how to choose one observation to use to represent a week or a month of input data. The MODIS data processing algorithms take into account all sorts of other data in order to choose the highest quality observation. These data include elevation, slope, snow cover, land cover, cloud cover, water vapor, satellite view angle, etc. For the MOD11 data products, these ancillary input data are detailed in section 3.2.6 of the MOD11 Algorithm Theoretical Basis Document. However, the complexity of these compositing algorithms is usually beyond the abilities of anyone except the data product PIs and their grad students.

If your project doesn't require super careful data processing, you can try combining the weekly rasters into one monthly raster yourself. Using Raster Calculator in ArcGIS, Band Math in ENVI, or the numpy.maximum function in NumPy, you could, on a pixel-by-pixel (i.e. element-wise) basis, take the average, median, mininum, or maximum observation. Of course, this can distory or skew the data depending on your study area, and the element-wise processing can lead to a noisy or patchwork look in the final data.

I hope that helps!

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Im moving on the second approach. Im trying to composite from 8 day observations. But the problem arises when the observations are overlapping with its current month as well with the next one –  nickves Jun 22 '12 at 17:44
    
You are just going to have to make a decision with those. If you are producing visuals that have a month next to them, I would probably just choose all of the 8-day observations dated with that month. Even if it's not a very scientific way of aggregating the data, at least it's straightforward and reproducible. You should also check the ATBD I linked above to see if there's information about whether the data product date indicates the first or last day of the compositing period. –  dmahr Jun 22 '12 at 19:13
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You may want to do this in a temporal GIS. An option is GRASS GIS 7, see

The new spatio-temporal support offers easy time series aggregation.

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