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American Journal of Innovative Research & Applied Sciences
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| | ARTICLES | Am. J. innov. res. appl. sci. Volume 5, Issue 5, Pages 326-335 (November 2017) |
| Research Article |
American Journal of innovative
Research & Applied Sciences
Research & Applied Sciences
ISSN 2429-5396 (Online)
OCLC Number: 920041286
OCLC Number: 920041286
|
| NOVEMBER | VOLUME 5 | N° 5 | 2017 |
Authors Contact
*Correspondant author and authors Copyright © 2017:
| Gbola Kehinde Adewuyi 1* | Martins Adewale Oyekola 1 | and | Stephen Adediran Aderinkomi 1 |
*Correspondant author and authors Copyright © 2017:
| Gbola Kehinde Adewuyi 1* | Martins Adewale Oyekola 1 | and | Stephen Adediran Aderinkomi 1 |
Affiliation.
1. The Polytechnic Ibadan | Department of Surveying and Geoinformatics | Oyo State | Nigeria |
1. The Polytechnic Ibadan | Department of Surveying and Geoinformatics | Oyo State | Nigeria |
This article is made freely available as part of this journal's Open Access: ID | Adewuyi-ManuscriptRef.1-ajira300917 |
ABSTRACT
Background: Density-Based Cluster is an unsupervised learning method that shows individual characteristics groups in a given data on the fact that a cluster in a data space shares a common region of either high, medium and low point density, separated one from other such clusters by sharing common regions of either high, medium or low point density. Objectives: This study aimed at investigating the density cluster image of selected physical feature/objects of interest and their locations of Amuwo Odofin Local Government Area, Lagos West Senatorial Districts, Lagos State, South Western Nigeria. Also, Seven (7) objects/Physical features and their location with their colour representation were determined using Google earth satellite imagery and they are; Bus Stop (Blue), Markets (Pink), Hospitals (Light Green), Hotels (Black), Schools (Deep Green), Churches (Red), and Banks (Brown). Methods: An unsupervised clustering technique was used for this study. The methodology adopted for this study was based on the use of Google earth imagery in determines the location and coordinate x, y of some objects of interest within the study area. Further analysis was carried out using ArcGIS 10.2 Software (Arc Map 10.2). Results: for this study, composite maps showing all the selected points of interest and map query for each object were presented to show the area covered by each feature selected. Also, from the result, the areas of Low, Medium/Moderate and high density were determined and it shows that mostly all the selected objects of interest were mainly at the upland part of the study area. Conclusion: The density map produced will go a long way in proper planning of the study area and also will help the Lagos State Government in planning and re-planning the area and also pave way for the private sectors to invest more in the area.
Keywords: Image clustering, objects of Interest, unsupervised clustering Techniques, density map, Proper Planning
Background: Density-Based Cluster is an unsupervised learning method that shows individual characteristics groups in a given data on the fact that a cluster in a data space shares a common region of either high, medium and low point density, separated one from other such clusters by sharing common regions of either high, medium or low point density. Objectives: This study aimed at investigating the density cluster image of selected physical feature/objects of interest and their locations of Amuwo Odofin Local Government Area, Lagos West Senatorial Districts, Lagos State, South Western Nigeria. Also, Seven (7) objects/Physical features and their location with their colour representation were determined using Google earth satellite imagery and they are; Bus Stop (Blue), Markets (Pink), Hospitals (Light Green), Hotels (Black), Schools (Deep Green), Churches (Red), and Banks (Brown). Methods: An unsupervised clustering technique was used for this study. The methodology adopted for this study was based on the use of Google earth imagery in determines the location and coordinate x, y of some objects of interest within the study area. Further analysis was carried out using ArcGIS 10.2 Software (Arc Map 10.2). Results: for this study, composite maps showing all the selected points of interest and map query for each object were presented to show the area covered by each feature selected. Also, from the result, the areas of Low, Medium/Moderate and high density were determined and it shows that mostly all the selected objects of interest were mainly at the upland part of the study area. Conclusion: The density map produced will go a long way in proper planning of the study area and also will help the Lagos State Government in planning and re-planning the area and also pave way for the private sectors to invest more in the area.
Keywords: Image clustering, objects of Interest, unsupervised clustering Techniques, density map, Proper Planning
DENSITY BASED CLUSTER IMAGE OF SELECTED OBJECTS OF INTEREST: A CASE STUDY OF AMUWO ODOFIN LOCAL GOVERNMENT AREA, LAGOS STATE, NIGERIA
| Gbola Kehinde Adewuyi | Martins Adewale Oyekola | and | Stephen Adediran Aderinkomi |. Am. J. innov. res. appl. sci. 2017; 5(5): 326-335.
| PDF FULL TEXT | | Received | 06 September 2017 | | Accepted | 19 October 2017 | | Published 24 October 2017 |
| Gbola Kehinde Adewuyi | Martins Adewale Oyekola | and | Stephen Adediran Aderinkomi |. Am. J. innov. res. appl. sci. 2017; 5(5): 326-335.
| PDF FULL TEXT | | Received | 06 September 2017 | | Accepted | 19 October 2017 | | Published 24 October 2017 |