I have new situation then I estimate APS.
I use amplitud stability index 0.9 for APS estimation. and them are enouht to estimate APS. It is a city area. But after connection calculation result shows taht most of connection are low cohherence <0.6. so estimation fails. I have tried different connection types but have not got good result. That may cause sutch situaton there stability is good but cohherence poor. I dont have a glue. Examples will be good.
1. numbers as amplitude stability index and temporal coherence are not absolute. you always need to specify how many images you are processing.
2. possible reasons for low temporal coherence: range of parameters to estimate is wrong; model chosen for estimating the movement is wrong; connections are too long and the atmospheric delay too strong; selected pixels/targets are noisy.
number of images are 27 so not to many so I used higher amplitude stability then usually.
1) Does I understood correctly that noisy pixel could have high aplitude stability (>0.9) but low cohherence? For me it is little bit hard to understand.
2) does it hav some “general rule” about connection length? In current issue I really have them quite long (10 km) because there is open water between 2 land area. Wether data is also quite poor rainy, thunderstorm ect?
3)”estimating model” – is it mean linear or smart (non -linear) or have some other possibilities?
1. phase is more sensitive than amplitude. usually pixels with stable amplitude have stable phase, but anything can happen
2. the atmospheric decorrelation length depends on wavelength and geographic area. anyway, to give a number, over 800m-1km connections should loose coherence. in 10km you will never find good coherence
3. yes. but u can also have seasonal/thermal models or anything else