Classifications of Satellite Imagery for Identifying Urban Area Structures

• 作者: Abdlhamed Jamil Abdulmohsen Al-Shareef Amer Al-Thubaiti
• 来源期刊: 遥感技术进展(英文)
• 学科: 数学
• 关键词: REMOTE SENSING SATELLITE IMAGERY Image Processing Classification Assessment Urban
• 年，卷（期）: 2020,（1）
• 页码范围: 12-32
• 页数: 21页
• 分类号: O17

摘要

This study compares three types of classifications of satellite data to identify the most suitable for making city maps in a semi-arid region. The source of our data was GeoEye 1 satellite. To classify this data, two pro-grammes were used: an Object-Based Classification and a Pixel-Based Classification. The second classification programme was further subdi-vided into two groups. The first group included classes (buildings, streets, vacant land, vegetations) which were treated simultaneously and on a single image basis. The second, however, was where each class was identified individually, and the results of each class produced a single image and were later enhanced. The classification results were then as-sessed and compared before and after enhancement using visual then automatic assessment. The results of the evaluation showed that the pix-el-based individual classification of each class was rated the highest after enhancement, increasing the Overall Classification Accuracy by 2%, from 89% to 91.00%. The results of this classification type were adopted for mapping Jeddah’s buildings, roads, and vegetations.