| 水体悬浮泥沙动态监测的遥感反演模型对比分析——以鄱阳湖为例 |
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| 引用本文： | 陈晓玲,吴忠宜,田礼乔,陈莉琼,叶艺. 水体悬浮泥沙动态监测的遥感反演模型对比分析——以鄱阳湖为例[J]. 科技导报(北京), 2007, 25(6): 19-22 |
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| 作者姓名： | 陈晓玲 吴忠宜 田礼乔 陈莉琼 叶艺 |
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| 作者单位： | 武汉大学测绘遥感信息工程国家重点实验室,武汉,430079;江西师范大学鄱阳湖生态环境与资源研究教育部重点实验室,南昌,330022;武汉大学测绘遥感信息工程国家重点实验室,武汉,430079 |
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| 基金项目： | 国家重点基础研究发展计划(973计划)项目(2003CB415205)，国家自然科学基金项目(40676094)，教育部“长江学者和创新团队发展计划”创新团队项目(IRT0438) |
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| 摘 要： | 水体泥沙是进行水环境监测及研究与泥沙输移有关的侵蚀、沉积过程所带来的灾害问题的关键因素,实现悬浮泥沙遥感定量动态监测的关键在于建立合适的反演模型。采用实测光谱模拟TM/ETM 和MERIS数据,对比分析了单波段和波段比值遥感因子构建的5种常用的经验半经验模型。结果表明,以MERIS第7波段遥感反射率为遥感因子建立的对数模型最适宜鄱阳湖地区悬浮泥沙的动态监测。
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| 关 键 词： | 灾害监测 遥感 悬浮泥沙 |
| 文章编号： | 1000-7857(2007)06-0019-04 |
| 修稿时间： | 2007-02-14 |
Inversion Model for Dynamic Monitoring of Suspended Sediment: A Case Study on Poyang Lake |
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| CHEN Xiaoling,WU Zhongyi,TIAN Liqiao,CHEN Liqiong,YE Yi. Inversion Model for Dynamic Monitoring of Suspended Sediment: A Case Study on Poyang Lake[J]. Science & Technology Review, 2007, 25(6): 19-22 |
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| Authors: | CHEN Xiaoling WU Zhongyi TIAN Liqiao CHEN Liqiong YE Yi |
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| Affiliation: | 1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China 2. The Key Laboratory of Poyang Lake Ecological Environment and Resource Revelopment, Jiangxi Normal University, Nanchang 330022, China |
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| Abstract: | The suspended sediment is closely related with water environment quality and is also the key issue in the disaster study associated with the processes of erosion,deposit and sediment transportation.A fitted inversion model plays an important role in the dynamic monitoring of suspended sediments.In this study,in situ observed remote sensing reflectance data were used to simulate the corresponding channels of TM/ETM and MERIS data.A comparison is made on five empirical and semi-empirical inversion models for a single channel and the ratios among different channels.The result suggests that the logarithmic model based on reflectance of MERIS channel 7 is most suitable for suspended sediment dynamic monitoring in Poyang Lake. |
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| Keywords: | disaster monitoring remote sensing suspended sediment |
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