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机构地区:[1]中国科学院烟台海岸带研究所,烟台264003 [2]中国科学院大学,北京100049
出 处:《资源科学》2014年第3期463-472,共10页Resources Science
基 金:中国科学院战略性先导科技专项-应对气候变化的碳收支认证及相关问题(编号:XDA05130703);中国科学院知识创新工程重要方向项目(编号:kzcx2-yw-224);国家自然科学基金项目(编号:40801016)
摘 要:土地利用分类是土地利用数据建立和土地利用变化研究的前提。鉴于我国海岸带土地利用多样性显著而分类系统研究相对不足的现实,本文简要论述国内外海岸带土地利用分类系统的研究进展、适用的遥感数据类型和制图精度,并从陆海耦合的角度出发回顾国内滨海湿地分类系统的研究成果。在此基础上,提出中国海岸带土地利用遥感分类系统优化方案,包含8个一级类型和24个二级类型,较全面地涵盖了全国海岸带的土地资源类型,并从海岸带区域的特征出发,强调了湿地资源的细分;应用该分类系统,基于Landsat TM影像建立解译标志,并对2010年中国海岸带区域土地利用进行遥感制图,表明该分类系统具有较强的可行性。本研究可为全国尺度海岸带土地资源遥感调查、土地利用管理与规划、海岸带综合管理等研究工作提供参考。Land use classification systems are very important for land use studies and classification systems available for various remote sensing data have received much attention in recent years. In view of the diversity of land use and a lack of land use classification studies on China' s coastal zone, we discuss research progress, available remote sensing images and mapping accuracy for land use in coastal zones in China and internationally. We then review the status quo of studies on coastal wetland classification systems in China. We found that almost all existing land use classification systems are suitable at specific regional scales only. Therefore, considering the main characteristics of China' s coastal zone we developed an optimized and comprehensive land use classification system suitable for the whole coastal zone in China using archived time series Landsat TM/ETM+ images and HJ-CCD images. The system includes eight primary categories and 24 subcategories, which covers most types of land use. Primary categories include farmland, forest, grassland, built-up, inland freshwater, coastal saltwater, human made (saltwater) wetland and unused land. Based on archived Landsat TM images captured in 2010, visual interpretation marks of 24 land use types were created and the land use classification system tested by creating a land use map in 2010 for China' s coastal zone. This land use classification system is very effective and suitable for visual interpretation of coastal land use based on remote sensing images at a spatial resolution of 30m.
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