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首页> 外文会议>International symposium on multispectral image processing and pattern recognition >Land cover's refined classification based on multi source of remote sensing information fusion: a case study of national geographic conditions census in China
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Land cover's refined classification based on multi source of remote sensing information fusion: a case study of national geographic conditions census in China

机译：基于多源遥感信息融合的土地覆盖物精细分类研究-以中国国家地理普查为例

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The project of The First National Geographic Conditions Census developed by Chinese government has designed the data acquisition content and indexes, and has built corresponding classification system mainly based on the natural property of material. However, the unified standard for land cover classification system has not been formed; the production always needs converting to meet the actual needs. Therefore, it proposed a refined classification method based on multi source of remote sensing information fusion. It takes the third-level classes of forest land and grassland for example, and has collected the thematic data of Vegetation Map of China (1:1,000,000), attempts to develop refined classification utilizing raster spatial analysis model. Study area is selected, and refined classification is achieved by using the proposed method. The results show that land cover within study area is divided principally among 20 classes, from subtropical broad-leaved forest (31131) to grass-forb community type of low coverage grassland (41192); what's more, after 30 years in the study area, climatic factors, developmental rhythm characteristics and vegetation ecological geographical characteristics have not changed fundamentally, only part of the original vegetation types have changed in spatial distribution range or land cover types. Research shows that refined classification for the third-level classes of forest land and grassland could make the results take on both the natural attributes of the original and plant community ecology characteristics, which could meet the needs of some industry application, and has certain practical significance for promoting the product of The First National Geographic Conditions Census.
机译：中国政府制定的《第一次国家地理条件普查》项目设计了数据采集的内容和指标，并主要根据物质的自然属性建立了相应的分类体系。但是，还没有形成统一的土地覆被分类标准。生产总是需要转换以满足实际需求。因此，提出了一种基于多源遥感信息融合的精细分类方法。以林地和草地三级分类为例，收集了中国植被图（1：1,000,000）的专题数据，尝试利用栅格空间分析模型进行精细分类。选择研究区域，并使用所提出的方法实现精细分类。结果表明，研究区域内的土地覆盖主要分为20类，从亚热带阔叶林（31131）到低覆盖草地的草丛群落类型（41192）。而且，研究区经过30年的发展，气候因素，发育节律特征和植被生态地理特征没有发生根本变化，只有部分原始植被类型的空间分布范围或土地覆盖类型发生了变化。研究表明，对林地和草地三级分类的精细分类可以使结果既具有原始的自然属性，又具有植物群落生态特征，可以满足某些工业应用的需求，具有一定的现实意义。宣传《第一份国家地理条件普查》的产品。

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