Object based image analysis of support vector machine and rule based image classification for building extraction. Degree thesis, Universiti Teknologi MARA, Shah Alam. (2020)
Abstract
Building extraction is one of the main procedures used in updating digital maps and geographic information system databases. This is a challenging task in a remote sensing community to extract buildings from high spatial remote sensing imagery because of the spectral similarity between man-made objects such as buildings, parking lots, roads, in the urban areas. This study utilizes Pleiades-1A satellite image data of Shah Alam areas to extract buildings in urban area. The main goal of this study is to demonstrate the capability of object-based image analysis (OBIA) in building extraction from high spatial remote sensing imagery. Different classification approaches, including support vector machine (SVM) and rule-based classification, were applied to the Pleiades-1 A. Results show that rule-based classification has a better overall accuracy closeness index with 0.07 while SVM had 0.14 of overall accuracy closeness index. The rule-based classification resulted in fewer buildings that under-segmentation and over-segmentation. The classification accuracy of the result obtained is approximately 95% for SVM and 83% for rule-based classification. The overall accuracy and kappa coefficient for SVM is 95.11% and 93% respectively and the classification accuracy using rule-based image classification shows 83.49%) and 76%) of overall accuracy and kappa coefficient respectively. The map of building extraction using SVM shows the distribution of building, tree, road, waterbody, land, grass and shadow area are 14%, 19%, 23%, 6%, 12%, 26%, and 0% respectively and the map of building extraction using rule-based image classification shows 26%), 24%o, 14%), 3%o, 30%), 3%) and 0% of building, grass, land, road, tree, waterbody and shadow area respectively.
| Item Type: | Thesis (Degree) |
|---|---|
| Keywords: | Digital maps, GIS, Remote sensing, Spatial, Satellite imagery |
| Taxonomy: | By Subject > Architecture, Planning & Surveying > Surveying Sciences And Geomatics By Subject > Architecture, Planning & Surveying > Building Surveying |
| Local Content Hub: | Subjects > Architecture, Planning & Surveying |
| Depositing User: | Eza Eliana Abdul Wahid |
| Date Deposited: | 12 Jan 2021 02:49 |
| Last Modified: | 12 Jan 2021 02:49 |
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