| 基于对象影像分析方法支持下的多源遥感影像光伏电场提取 |
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| 引用本文： | 李彦甫,刘勇.基于对象影像分析方法支持下的多源遥感影像光伏电场提取[J].测绘与空间地理信息,2016(3):68-72. |
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| 作者姓名： | 李彦甫 刘勇 |
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| 作者单位： | 兰州大学资源环境学院,甘肃兰州,730000 |
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| 基金项目： | 国家自然科学基金项目(41271360) |
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| 摘 要： | 以光伏电场为代表的新能源在我国尤其是西部荒漠地区发展迅猛,利用遥感信息分析方法自动、快速、准确获取该类能源用地具有重要现实意义。以宁夏中卫市沙漠光伏产业园为研究区,在基于对象影像分析方法的支持下分析了光伏电场在Landsat 8 OLI、World View Ⅱ和高分-1号(GF-1)遥感影像上的光谱、纹理等特征并进行了提取试验。
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| 关 键 词： | 基于对象影像分析 分割参数优选 光伏电场 信息提取 |
Extraction of Photovoltaic Electric Farms from Multi-source Remote Sensing Images Based on Object-based Image Analysis |
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| Abstract: | As one of representative of new energy, photovoltaic electric farms are extending rapidly in China, especially in desert area of the western China.It isof realistic significance to extract photovoltaic electric farms automatically, quickly and accurately.In this artical, the photovoltaic electric farms at Ningxia Desert Photovoltaic Industry Park, Zhongwei City, China, were extracted through ob-ject-based image analysis ( OBIA)method through employing spectral and textural features in Landsat 8 OLI, WorldView II and GF-1 images.It is shown that OBIA is effective on extraction of photovoltaic electric farms from either middle or high resolution remote sensing images with high precision.For Worldview II and GF-1 images, solar cell arrays can be extracted firstly based on four fea-tures:RRI, Length/Width, dissimilarity and brightness, and then internal road and other entries can be extracted based on the con-text, geometry, spectral features.Rule sets constructed in this way is accessible, transferable and have fewer features.For Landsat 8 OLI images, photovoltaic electric farms can be extracted using RRI, NDBI, and brightness features. |
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| Keywords: | object-based image analysis optimal segmentation parameter photovoltaic electric farms information extraction |
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