USING OF MARKOV CHAIN, MOLA, AND NEIGHBORHOOD FILTER FOR DEVELOPING AND INCREASING THE EFFICIENCY OF LOGISTIC REGRESSION TO PREDICT MULTIPLE LAND-USE CHANGES, A CASE STUDY: TEHRAN

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.

ASKARIAN OMRAN HOSEIN; PAHLAVANI PARHAM

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

Journal Paper

Paper Information

Journal: ENGINEERING JOURNAL OF GEOSPATIAL INFORMATION TECHNOLOGY Year:2015 | Volume:3 | Issue:2 Page(s): 89-109

Download Full-Text

Persian Verion

View:

1,009

Download:

Cites:

Information Journal Paper

Title

USING OF MARKOV CHAIN, MOLA, AND NEIGHBORHOOD FILTER FOR DEVELOPING AND INCREASING THE EFFICIENCY OF LOGISTIC REGRESSION TO PREDICT MULTIPLE LAND-USE CHANGES, A CASE STUDY: TEHRAN

Author(s)

ASKARIAN OMRAN HOSEIN | PAHLAVANI PARHAM | Issue Writer Certificate

Keywords

MULTIPLE LAND USE CHANGESQ2

NEIGHBORHOODQ2

LOGISTIC REGRESSIONQ2

MARKOV CHAINQ1

MOLAQ2

Abstract

To reach a more accurate prediction of future of a city, modeling must be done for all land-uses of the town. LOGISTIC REGRESSION only can model a bivariate urban growth, i.e., urban and non-urban. Also, this method cannot consider the NEIGHBORHOOD effects in the allocation process. Due to this issue, the aim of this paper is to provide a method for modeling multiple land-use changes and applying the NEIGHBORHOOD parameter in allocation process, and thereby increasing the accuracy of modeling. So, in this article, we predicted the land-use map of the year 2014, using the land-use maps of the years 2002 and 2008 by considering the effects of the NEIGHBORHOOD parameter and by comparing the predicted land-use map of the year 2014 with the reference map of 2014, the accuracy of the model was obtained. Reference land-use maps were obtained using classification of Landsat images of 2002, 2008, and 2014 using the Support Vector Machine (SVM) method. In the proposed method, the first modeling was performed separately using the LOGISTIC REGRESSION method for each land-use. Then the results of the LOGISTIC REGRESSION as a Competency Map for allocation process were combined with the MARKOV CHAIN and a combined method of MOLA-Neighborhood to obtain the land-use map of 2014. The procedure was performed in 4 different scenarios. In three of them, the NEIGHBORHOOD effects was considered as 3´3, 5´5, and 7´7 kernel and in the last one, modeling was performed without considering NEIGHBORHOOD effects. The accuracy of 4 scenarios was compered using the reference map of 2014. In the best scenario the accuracy of method was obtained using overall accuracy, kappa index and location about 84.26% and 76.35%, and 79.3%. Finally, the accuracy of each land-use category was evaluated separately using the ROC, which indicates the capability of the proposed approach of this paper. Finally, the land-use map of the year 2020 was predicted in two different scenarios.

Cites

No record.

References

No record.

Cite

APA: Copy

ASKARIAN OMRAN, HOSEIN, & PAHLAVANI, PARHAM. (2015). USING OF MARKOV CHAIN, MOLA, AND NEIGHBORHOOD FILTER FOR DEVELOPING AND INCREASING THE EFFICIENCY OF LOGISTIC REGRESSION TO PREDICT MULTIPLE LAND-USE CHANGES, A CASE STUDY: TEHRAN. ENGINEERING JOURNAL OF GEOSPATIAL INFORMATION TECHNOLOGY, 3(2), 89-109. SID. https://sid.ir/paper/230114/en

Vancouver: Copy

ASKARIAN OMRAN HOSEIN, PAHLAVANI PARHAM. USING OF MARKOV CHAIN, MOLA, AND NEIGHBORHOOD FILTER FOR DEVELOPING AND INCREASING THE EFFICIENCY OF LOGISTIC REGRESSION TO PREDICT MULTIPLE LAND-USE CHANGES, A CASE STUDY: TEHRAN. ENGINEERING JOURNAL OF GEOSPATIAL INFORMATION TECHNOLOGY[Internet]. 2015;3(2):89-109. Available from: https://sid.ir/paper/230114/en

IEEE: Copy

HOSEIN ASKARIAN OMRAN, and PARHAM PAHLAVANI, “USING OF MARKOV CHAIN, MOLA, AND NEIGHBORHOOD FILTER FOR DEVELOPING AND INCREASING THE EFFICIENCY OF LOGISTIC REGRESSION TO PREDICT MULTIPLE LAND-USE CHANGES, A CASE STUDY: TEHRAN,” ENGINEERING JOURNAL OF GEOSPATIAL INFORMATION TECHNOLOGY, vol. 3, no. 2, pp. 89–109, 2015, [Online]. Available: https://sid.ir/paper/230114/en

Related Journal Papers