For example, when we are doing change detection for 20 years, we can not get high resolution image for 1990's, so how can we reduce this kind of error using ERDAS?
Hi there
The advantages of high resolution satellite data is that you can discriminate the target features in high resolution and vice versa with the low resolution data. But having said that, the matching (High Res VS. Low Res) depends on your target area.
If you get a similar results (Spectral signatures) from both the sensors (High & low) then you can conclude that low resolution satellite serves the purpose and you don't need to opt for a high res satellite image.
Another crucial factor to consider is the number of bands, if you low res and high res satellites have different bands then you have match the number of bands using interpolation and then do the comparison.
Hope it helps
You can generate pansharpened image if the resolution are from same satellite data sets. However if you are intending to compare MODIS type of data with landsat or landsat with wordview 2 or anyother satellite then it is more relevent to do feature extraction and integrate it via GIS.
If you do a change analysis, then a post classification algorithm method is the best:
1. pre-define the scale of your output maps (which should be the same or/ at least comparable)
2. classify each dataset separately,
3. then compare the resulting maps
However, if you want to merge them to get a better sharpened image only, then you can do it without the need to classify any (although the resolutions should not be far from each other: say in the order of 1:4)
thank you,
As you know there are several (perhaps many) methods that have been developed to digitally merge image data sets with different spatial and spectral resolutions. The best one to use depends on the application and information that is of interest. Below are two of my papers that deal with this particular topic that may be of interest to you:
Digital merging of Landsat TM and digitized NHAP data for 1:24 000-scale image mapping.
Photogrammetric Engineering and Remote Sensing, Vol. 52, No. 10, 1986, pp. 1637-1646.
Comparison of Three Different Methods to Merge Multiresolution and Multispectral Data: Landsat TM and SPOT Panchromatic
Photogrammetric Engineering and Remote Sensing, Vol. 57, No. 3, March 1991, pp. 295-303
I hope there is something useful for you in the papers and good luck with your work.
Pat
via resolution merge or image fusion in ERDAS IMAGINE or other rs softwares
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