|
|
|
|
  • 软件名称:水质遥感监测的关键要素叶绿素a的反演算法研究进展
  • 软件大小: 0.00 B
  • 软件评级: ★★★
  • 开 发 商: 罗婕纯一,秦龙君,毛鹏,熊育久,赵文利,高辉辉,邱国玉
  • 软件来源: 《遥感技术与应用》
  • 解压密码:www.gissky.net

资源简介

摘要: 叶绿素a浓度是表征水体富营养化程度的重要指标,通过遥感手段反演叶绿素a浓度是实现水体富营养化监测的一个有效途径,已衍生出了一系列叶绿素a浓度反演算法。这些算法各有所长,适用范围也各自有别。由于水体光学特征差异,盲目套用这些算法难以取得预期效果。为了推动水质遥感的进一步发展,从遥感反演的原理和数据源出发,对国内外利用遥感技术反演水体叶绿素a浓度的算法进行综述。根据算法结构设计的不同,将反演算法分为6大类,分别为荧光峰和反射峰算法、波段算法、指数算法、智能算法、基于水体分类的算法体系以及分析类算法,系统地梳理各类算法并分析算法特征。从算法适用的叶绿素a浓度区间和水体类型等角度出发,总结各类算法的适用范围,评述各类算法的优缺点,以期为环境和遥感工作者提供参考。主要结论如下:①Ⅱ类水体算法外推适应性较弱,应建立并补充实测数据集,研究各类水体光学特性异同点,构建基于水体分类的通用算法体系;②无人机技术与高光谱传感器的结合可为内陆水体水质监测提供新思路;③应结合机器学习算法与机理模型,发展物理原理约束的高精度反演模型。 关键词: 叶绿素a;  遥感;  水体;  水质;  富营养化     Abstract: Chlorophyll-a concentration is an important proxy for defining the tropic status of various bodies of water. Using remote sensing technology to retrieve chlorophyll-a concentration is an effective method for water eutrophication monitoring and a great number of algorithms for chlorophyll-a concentration retrieval are developed. These algorithms have different advantages and ranges of application. Because the optical characteristics vary in different bodies of water, it is hard to achieve desired results if blindly applying algorithms. In order to promote the further development of water quality remote sensing, the theory and data sources of remote sensing inversion are introduced.Then,domestic and foreign algorithms of retrieving chlorophyll-a concentration in water by remote sensing are summarized.The algorithms studied are categorized into six types by their architectural designs, namely: fluorescence peak and maximum peak algorithms, band algorithms, chlorophyll-a index algorithms,artificial intelligence algorithms,algorithm systems based on optical water types and analytical algori-thms.Each algorithm is presented systematically and its characteristics are analyzed.Then,all the aforementioned algorithms are compared regarding their applicable range of chlorophyll-a concentrations as well as water types.The applicability, merits and demerits of each category of algorithms are analyzed and concluded in order to provide reference for environmental and remote sensing researchers.The main conclusions are as follows:①the algorithm applicability for Case II waters is limited. More in-situ observations should be conducted to establish and supplement the database. Similarities and difference of various optical water types should be further studied to establish global algorithm systems based on optical water typologies; ②The combination of UAVs and hyperspectral sensors could provide new thoughts in monitoring inland water quality; ③Machine learning algorithms and mechanism models should be integrated to develop physical constrained models with high accuracy.

下载说明

·如果您发现该资源不能下载,请通知管理员.gissky@gmail.com

·为确保下载的资源能正常使用,请使用[WinRAR v3.8]或以上版本解压本站资源,缺省解压密码www.gissky.net ,如果是压缩文件为分卷多文件,请依次下载每一个文件,并按照顺序命名为1.rar,2.rar,3.rar...,然后鼠标右击1.rar解压.

·为了保证您快速的下载速度,我们推荐您使用[网际快车]等专业工具下载.

·站内提供的资源纯属学习交流之用,如侵犯您的版权请与我们联系.