I have two Landsat 5 NDVI images (Surface Reflectance products) from the same period of the year (only a few days apart), but one is from the 1980s and one from the 2000s. I am trying to do a change detection procedure based on NDVI differencing, and the expected outcome (based on aerial photographs) is that NDVI should have increased due to a widespread reforestation process, so the result of the differencing process (2007NDVI - 1987NDVI) should highlight mainly a) unchanged areas and b) areas of ndvi increase.
I tried to reclassify the difference image using a threshold calculated as μ ± n·σ; (μ represents the mean, and σ the standard deviation). I used n=1. (reference paper: http://www.sisef.it/iforest/contents/?id=ifor0909-007 ) The difference image classified this way, however, shows mainly unchanged pixels, so is it possible that the difference image shows no increase simply because the data are not "normalized"? Since this is a SR product, it has already been atmospherically corrected, so it may be that due to climatic differences during those two years in one case the vegetative season was more advanced than the other.
The first is from 1989 and the second from 2007.
Would in this case a histogram matching procedure be of any help (or any other procedure you might suggest)? And if so, how can I perform that using QGIS? I couldn't find any dedicated tool or plugin for it.