This paper proposes an approach of modeling with a permanent-scatterer（PS） network（MPSN） based on the neighborhood differential idea

aiming at effectively and reliably detecting both linear and nonlinear ground deformations and estimating atmospheric effects by differential synthetic aperture radar interferometry with permanent scatterers（PS-DInSAR）.Firstly

the triangular irregular network（TIN） of PSs is generated based on the PSs’ image coordinates.Deformations are correlative both temporally and spatially

but atmospheric delays are only correlative spatially.Furthermore

the shorter the intervals of space and time series are

the more the correlations of deformations and atmospheric delays will strengthen.So the phase difference of neighboring PSs can depress the atmospheric influence.Then the neighboring differential phase model（NDPM） is constructed based on the neighborhood of PSs among the TIN

and the corresponding set of neighboring differential phases is generated.What are unknown in NDPM are residual elevation difference Δh

i

j and mean velocity difference Δv

i

j between two neighboring PSs i and j.Secondly

the TIN is twice optimized according to distance（

<

1km） and multi-image phase coherence（γ） between two neighboring PSs

and the neighboring differential phases hardly influenced by atmosphere delays are selected to resolve the NDPM by using a simple periodogram

i.e.to estimate the residual elevation difference Δh

i

j and the mean velocity difference Δv

i

j between two neighboring PSs i and j.After the estimation of Δh

i

j and Δv

i

j

the elevation Δh and the mean velocity v of every PS are respectively calculated through network adjustment based on the optimized TIN.Finally

the PS’s phase residue Δ

r

es can be calculated.Then the temporal and spatial correlations of deformations and atmospheric delays are taken into account again

and the appropriate filters are selected to discriminate the following phases from phase residue Δ

r

es

（1）PS’s atmospheric phases in differential interferograms

（2）PS’s atmospheric phases in SAR images

（3）PS’s no-linear deformation phases.A set of computer programs are developed in Matlab environment to implement the above approach.Lujazui in Shanghai is selected as the study site

and the experiments are performed using 26 SAR images taken by ERS-1/2 from 1992 to 2002 to estimate linear motion rate

nonlinear motion magnitude

total deformation distribution

and atmospheric delay for each SAR image.The obtained measurements are very consistent with the ground-based measurements.Based on modeling with PSs’ TIN

the neighboring differential phases hardly influenced by atmosphere delays are selected to resolve the NDPM.The results are more reliable and precise.The experiment results show that the proposed modeling and methods are viable

and the computation software is reliable.