i use this data for my research
in my study, i want to combined both data with image fusion methods and then i do supervised classification for land cover analysis
i want to ask what step of preprocessing should i do first so i can combined them? or what must i do to make both to the same unit? Should I extract sentinel 1 into the dem shape first?
or can you tell me what the process must i do so that both data can be combined?
for pre-processing of the SAR data, calibration and Terrain Correction should be sufficient, maybe speckle filtering is also a good idea.
You can then create a stack of both data sets (can be found in the coregistration menu). If you use the supervised classification in SNAP you can choose Random Forest classifier. It can handle input data of different units.
If you want to classify in QGIS you need some kind of transformation to get both images scaled. Earlier versions of SNAP hat a scaling tool but I can’t find it in the newer ones. Have a look at image transformations in remote sensing.
How do I use the random forest classifier ? I have to combine sentine-1 with sentinel 2, so do I need to fuse them first or should I input them both (like we do to stack them in co-registration) in random forest classifier ? Please tell me the steps
could you plz send me a screen shot of all steps after taking shape geometries, how do i store it for supervised classification . i am new to snap. and please let me know how do i use random forest classifier? what inputs should i give?..its saying error in dimensions, how do i manage it
ok thanks before @ABraun but i’ve tried twice with the different master and slave
first, i try corregistration with sentinel 1 as master and sentinel 2 as slave, when proccess done, i load RGB of sentinel 1 data and it can be open, but not for sentinel 2, sentinel 2 min max value becomes 0
ande second, i’ve tried the opposite, And the results are also opposite too, sentinel 1 can not open and becomes all black, but sentinel 2 can load RGB color
did [quote=“dini_ramanda, post:22, topic:6277”]
l’ve finished with coregistration and was succesful, ^^
What did you change so that it works now?
Visually, you can display an RGB or HSV image of both inputs. Technically, a PCA would be the first I could think of in SNAP. As S2 has more bands than S1 it will be dominant in the PCA but the S1 should still be included in the main components. You could also calculate further S1 products of the S1 image (right-click > create filtered band, eg. sobel filter or high pas filter) and have them in included in the stack.#
i just follow your instruction to use coregistration - stack tools - create stack
emmm sorry, i dont understand, maybe you can give specific of the step, i little confused what you mean
cause there is no create filtered band when i do right click on the image