Manifold coordinates from Isometric mapping（Isomap） and Local Tangent Space Alignment（LTSA） preserve the spectral features of ground objects from Hyperspectral Imagery（HSI） through nonlinear dimensionality reduction.However

the theoretical differences result in differing capabilities in preserving spectral features.Thus

a comparison of two coordinates can make the underlying features prominent.Therefore

this paper proposes an innovative method called Difference Maps from Manifold Coordinates（DMMC）

which is based on Isomap and LTSA

to extract underlying features.First

spectral interpretations are matched with both coordinates and ensured to preserve the same spectral features.Second

the Isomap and LTSA coordinates are transformed into a uniform system using coordinate normalization and axis-direction adjustment.Finally

the difference maps are obtained through subtraction operations between the weighted manifold maps

and underlying features are extracted using classical image processing approaches.Two case studies are performed to evaluate the proposed method

and the results are compared with those obtained u sing Isomap and LTSA.The results show that DMMC outperforms Isomap and LTSA in extracting underlying features

such as the underlying shallow water near the river bank and the low spatial-resolution road in the large image scene of a swamp.This method provides a novel scheme for extracting underlying features from HSI data.