Improvement of urban land use and land cover classification approach in arid areas
文献类型：会议论文
| 作者 | Qian ; Jing1 ; 2 ; Zhou ; Qiming1 ; Chen ; Xi2 |
| 出版日期 | 2010 |
| 会议名称 | Proceedings of SPIE - The International Society for Optical Engineering, Image and Signal Processing for Remote Sensing XVI |
| 会议日期 | 2010 |
| 会议地点 | Toulouse, France |
| 关键词 | Arid regions - Image analysis - Image classification - Land use - Landforms - Maximum likelihood - Photography - Pixels - Remote sensing - Signal processing - Aerial Photographs - Arid area - Bare soils - Beijing-1 - Built-up areas - Classification approach - Classification results - Construction materials - Data sets - Discrete elements - Extraction accuracy - Field investigation - High resolution image - Land-cover types - Landsat ETM - Maximum likelihood classifications - Mixed pixel - Multi-sensor data - Object oriented - object-oriented classification method - Object-oriented processing - Spectral characteristics - Stony deserts - Urban areas - Urban change detection - Urban environments - Urban land use |
| 中文摘要 | Extraction of urban land-use information is base step of urban change detection. However, challenges remain in automatic delineation of urban areas and differentiation of finer inner-city land cover types. The extraction accuracy of built-up area is still unsatisfactory. This is mainly due to the heterogeneity nature of urban areas, where continuous and discrete elements occur side by side. Another reason is the mixed pixel problem, which is particularly serious in an urban environment. The built-up areas in arid areas may confuse with nearby bare soil and stony desert, which present very similar spectral characteristics as construction materials such as concrete, while they are often surrounded by farmland. This study focuses on improving urban land use and land cover classification approach in typical city of China's west arid areas using multi-sensor data. Pixel-based classification of the NDBI and Maximum Likelihood Classification (MLC) and object-oriented image classification were used in the study and the classification dataset including Landsat ETM (1999), CBERS (2005), and Beijing-1 (2006). The accuracy is assessed using high-resolution images, aerial photograph and field investigation data. The traditional pixel-based classification approach typically yield large uncertainty in the classification results. Object-oriented processing techniques are becoming more popular compared to traditional pixel-based image analysis. © 2010 Copyright SPIE - The International Society for Optical Engineering. (30 refs.) |
| 收录类别 | EI |
| 会议录 | Remote Sensing for Agriculture, Ecosystems, and Hydrology XII
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| ISSN号 | 0277-786X |
| ISBN号 | 13: 9780819483478 |
| 源URL | [http://ir.xjlas.org/handle/365004/10908]  |
| 专题 | 新疆生态与地理研究所_中国科学院新疆生态与地理研究所(2010年以前数据) |
| 推荐引用方式 GB/T 7714 | Qian,Jing1,2,et al. Improvement of urban land use and land cover classification approach in arid areas[C]. 见:Proceedings of SPIE - The International Society for Optical Engineering, Image and Signal Processing for Remote Sensing XVI. Toulouse, France. 2010. |
入库方式： OAI收割
来源：新疆生态与地理研究所
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