Ms. Deepali Shrivastava Profile

Deepali Shrivastava

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 30 April 2016

Automated endmember extraction for subpixel classification of multispectral and hyperspectral data

Deepali Shrivastava, Vinay Kumar, Richa Sharma

Proc. SPIE. 9880, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications VI

KEYWORDS: Landsat, Remote sensing, Reflectivity, Vegetation, Atmospheric corrections, Data acquisition, Image classification, Ear, Earth observing sensors, Alternate lighting of surfaces

Read Abstract +

Most of the multispectral sensors acquire data in several broad wavelength bands and are capable of extracting different Land Cover features while hyperspectral sensors contain ample spectral data in narrow bandwidth (10- 20nm). The spectrally rich data enable the extraction of useful quantitative information from earth surface features. Endmembers are the pure spectral components extracted from the remote sensing datasets. Most approaches for Endmember extraction (EME) are manual and have been designed from a spectroscopic viewpoint, thus neglecting the spatial arrangement of the pixels. Therefore, EME techniques which can consider both spectral and spatial aspects are required to find more accurate Endmembers for Subpixel classification. Multispectral (EO-1 ALI and Landsat 8 OLI) and Hyperspectral (EO-1 Hyperion) datasets of Udaipur region, Rajasthan is used in this study. All the above mentioned datasets are preprocessed and converted to surface reflectance using Fast Line-of-sight Atmospheric Analysis of Spectral Hypercube (FLAASH). Further Automated Endmember extraction and Subpixel classification is carried out using Multiple Endmember Spectral Mixture Analysis (MESMA). Endmembers are selected from spectral libraries to be given as input to MESMA. To optimize these spectral libraries three techniques are deployed i.e. Count based Endmember selection (CoB), Endmember Average RMSE (EAR) and Minimum Average Spectral Angle (MASA) for endmember selection. Further identified endmembers are used for classifying multispectral and hyperspectral data using MESMA and SAM. It was observed from the obtained classified results that diverse features, spread over a pixel, which are spectrally same are well classified by MESMA whereas SAM was unable to do so.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print format on SPIE.org.

PERSONAL SIGN IN
Full access may be available with your subscription

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Institutional Access:

PURCHASE THIS CONTENT

INTERESTED IN A FREE CORPORATE TRIAL?

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years