Mr. Clovis Gaboardi Profile

Clovis Gaboardi

at Instituto Militar de Engenharia

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 | 7 March 2003 Paper

Use of C-band coherence channel for land cover classification in tropical regions

Corina da Costa Freitas, Clovis Gaboardi, Luciano Vieira Dutra

Proceedings Volume 4883, (2003) https://doi.org/10.1117/12.463037

KEYWORDS: Coherence (optics), Image segmentation, Image classification, Composites, Synthetic aperture radar, Matrices, Backscatter, Error analysis, Feature extraction, Vegetation

Read Abstract +

It is well known that C Band SAR data is not adequate for land cover classification especially in tropical environments. The purpose of this paper is to study selected feature extraction techniques to improve the C band usefulness. ERS1/2 tandem mode data was acquired over the Tapajos National Forest, Brazil, and gave the opportunity of testing the C band coherence map for classification purposes. The use of coherence for land cover classification is justified since it is expected low coherence in forest areas, in comparison with bare soil and sparse vegetation, which have high coherence. Texture is also a standard feature normally employed and from a set of fourteen of the Haralick's features, one was selected to be tested jointly with C band coherence map and the C band backscatter itself. Two sets of classes, one with 10 classes, the other with 4 classes were defined for training the classifiers. These classes represent typical classes in the region, and mainly include primary forest, several stages of regeneration and pasture. Iterative Conditional Mode (ICM), which is a contextual supervised per point classification scheme, and a supervised region classifier from a segmentation map produced by region growing type of segmentation were used to produce the classification maps. Statistical tests based on Kappa statistics were used to test the precision and significance of the results. The result shows that coherence map alone is adequate for the case of four classes, and the inclusion of any other feature either does not change the precision significantly or worse the results.

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 or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

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