The long time series vegetation trends （LTSVT） research based on remote sensing in large area is the core field of vegetation ecology and an important direction in the global change study. AVHRR

SPOT VGT and MODIS are currently the main data resources of LTSVT research. With volumes of remote sensing data

the analysis and evaluation methods for LTSVT study emerged as an urgent issue. Algebra calculation

Fourier transformation

PCA analysis

wavelet transform

linear trend analysis （LTA）

correlation analysis （CA）

etc.

are the main methods. After the assessing and grouping of the methods

we focused on comparing the LTA and CA

which were well accepted methods

with the newly introduced Sen+Mann-Kendall method. Our review showed Sen+Mann-Kendall had a strong strength of errors resistance and was not constrained by the data statistical distribution.