Mr. Xiaoyu Chang Profile

Xiaoyu Chang

at Wuhan Univ

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 | 14 February 2020 Paper

A novel self-relearning approach for Landsat image change detection

Xiaoyu Chang, Xin Huang, Jiayi Li

Proceedings Volume 11428, 114280J (2020) https://doi.org/10.1117/12.2538192

KEYWORDS: Earth observing sensors, Landsat, Detection and tracking algorithms, Soil science, Remote sensing, Image classification, Environmental monitoring

Read Abstract +

Land cover composition and change are important aspects for many scientific research and socioeconomic assessments. The multi-date land cover change detection is generally more difficult and time-consuming to select enough training samples when considering multi-date image labels at the same location. To improve the accuracy for multi-date change detection, this study proposed a new algorithm framework, combining self-learning and relearning algorithm. Wuhan was selected as the experimental area, and Landsat images in 2005 and 2016 were used to extract six main types of change classes. Firstly, PCM (primitive co-occurrence matrix) and the minimum class certainty are used to ensure the high confidence of selected candidate set samples, and then the most informative samples are identified for classification from the candidate samples. To save computing costs, we adopt clustering method to reduce the self-relearning samples. Based on our experimental results, the self-relearning algorithm increases the final classification accuracy by approximately 2.5% (from 92.64% to 95.09%) in the case of using few initial training samples, providing a feasible solution for the multi-date change detection.

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