| 高光谱遥感数据藻类信息提取方法研究 |
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| 引用本文： | 赵杏杏,丛小飞,孙腾科.高光谱遥感数据藻类信息提取方法研究[J].测绘与空间地理信息,2014(7):26-31. |
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| 作者姓名： | 赵杏杏 丛小飞 孙腾科 |
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| 作者单位： | [1]河海大学地球科学与工程学院,江苏南京210098 [2]河海大学商学院,江苏南京210098 |
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| 基金项目： | 国家自然科学基金项目（41204016;41274028）;江苏省科技支撑计划项目（BE2010316）资助 |
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| 摘 要： | 以Sacramento-San Joaquin三角洲水域为研究区,利用2007年覆盖研究区的64个航带的HyMap数据,分别用混合调谐匹配滤波(MTMF)和决策树进行藻类信息的分类提取,在此基础上均采用Kappa系数作为标准进行精度评价。结果表明:混合调谐匹配波(MTMF)分析方法对藻类进行分类的结果,Kappa系数是0.634;用基于指数的决策树方法对藻类进行分类的结果,Kappa系数是0.613,两种结果都具有高度的一致性。这说明这两种方法在提取水生物种方面比价有效。
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| 关 键 词： | HyMap MFMT 决策树 藻类 |
Mothod of Extraction of Algae Information on Hyperspectral Data |
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| Institution: | ZHAO Xing - xing, CONG Xiao - fei , SUN Teng - ke (1. Institute of Geographical Information Science and Engineering, Hohai University, Nanjing 210098, China; 2. Business School of Hohal University, Hohal University, Nanjing 210098, China) |
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| Abstract: | This paper use Sacramento - San Joaquin Delta as the study area. On the base of the HyMap data covering 64 aircraft in 2007, with the mixed tuned matched filtering （MTMF） and decision tree method, we extract algae information, and on this basis are using Kappa coefficient as a standard to evaluate the accuracy. The results showed that： hybrid tuner matching wave （MTMF） analysis method to classify the results of algae, kappa coefficient was 0. 634 ; using decision tree - based index of the algae classification results, kappa coefficient was O. 613, both results are highly consistency. This shows that these two methods parity effective in extracting water clock. |
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| Keywords: | HyMap MFMT decision paper algae |
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