APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUES IN LAND USE/COVER MAPPING

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Moosavi v.; NIAZI Y.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Seminar Paper

Paper Information

Seminar: NATIONAL GEOMATICS CONFERENCE
Year:2014 | Issue:21

Download Full-Text

View:

172

Download:

150

Information Seminar Paper

Title

APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUES IN LAND USE/COVER MAPPING

Author(s)

Moosavi v. | NIAZI Y. | Issue Writer Certificate

Keywords

ANN

SUB-PIXEL CLASSIFICATION AND ETM+

Abstract

THIS STUDY WAS CARRIED OUT TO EVALUATE SEVERAL ARTIFICIAL NEURAL NETWORKS (ANNS) AS SUB-PIXEL CLASSIFICATION TECHNIQUES TO EXTRACT FRACTIONAL AREAS FROM LANDSAT ENHANCED THEMATIC MAPPER (ETM+) IN AREAS WITH LOW GROUND TRUTH DATA. AN INTENSIVE FIELD SURVEY WAS PERFORMED ON 30 PATCHES WITH THE AVERAGE OF 5 HECTARES USING A TACHYMETER AND THE CORRESPONDING MAPS WERE PRODUCED IN SCALE OF 1: 2000. FRACTIONAL AREAS OBTAINED FROM ANN MODEL WAS COMPARED WITH THE GROUND TRUTH DATA. THIS STUDY INDICATED AN AVERAGE ACCURACY OF ABOUT 95 PERCENT FOR ANN THAT CONFIRMS THE SIGNIFICANT PERFORMANCE OF THIS METHOD. IN THE ANN MODEL, A FEED-FORWARD NEURAL NETWORK (FNN) HAS BEEN EMPLOYED, USING 11 NEURONS IN THE HIDDEN LAYER AND LEVENBERG-MARQUARDT (LM) TRAINING ALGORITHM. FOR THE HIDDEN AND THE OUTPUT LAYERS, HYPERBOLIC TANGENT SIGMOID AND LOG-SIGMOID TRANSFER FUNCTIONS HAVE OFFERED THE BEST RESULTS, RESPECTIVELY. THIS STUDY INDICATED THE CAPABILITY OF ANN BASED SUB-PIXEL CLASSIFICATION METHOD IN AREAS WITH THE LACK OF COMPLETE GROUND TRUTH DATA.

Multimedia

No record.

Cites

No record.

References

No record.

Cite

APA: Copy

Moosavi, v., & NIAZI, Y.. (2014). APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUES IN LAND USE/COVER MAPPING. NATIONAL GEOMATICS CONFERENCE. SID. https://sid.ir/paper/947172/en

Vancouver: Copy

Moosavi v., NIAZI Y.. APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUES IN LAND USE/COVER MAPPING. 2014. Available from: https://sid.ir/paper/947172/en

IEEE: Copy

v. Moosavi, and Y. NIAZI, “APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUES IN LAND USE/COVER MAPPING,” presented at the NATIONAL GEOMATICS CONFERENCE. 2014, [Online]. Available: https://sid.ir/paper/947172/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops