| 太湖富营养化水体比辐射率测量及MODIS水体温度反演应用 |
| |
| 引用本文： | 阎福礼,林亚森,王世新,周艺. 太湖富营养化水体比辐射率测量及MODIS水体温度反演应用[J]. 中国科学院大学学报, 2019, 36(6): 784-793. DOI: 10.7523/j.issn.2095-6134.2019.06.009 |
| |
| 作者姓名： | 阎福礼 林亚森 王世新 周艺 |
| |
| 作者单位： | 1. 中国科学院遥感与数字地球研究所, 北京 100101;2. 中国科学院大学, 北京 100049 |
| |
| 基金项目： | 国家自然科学基金（41371363，40701126）资助 |
| |
| 摘 要： | 比辐射率是遥感温度反演的重要参数，水体成分变化会改变水体热辐射物理性质，对比辐射率造成影响。目前研究水体成分对水体比辐射率影响的研究比较缺乏。利用搭配PIKE积分球的Nicolet iS50傅里叶红外光谱仪测定不同浓度浮游藻类、悬浮物对水体比辐射率的影响，提出一种二类水体比辐射率的计算模型，基于该公式计算MODIS影像在分裂窗算法中的比辐射率响应与太湖表面温度，并进行空间分析与精度评价。实验结果表明：蓝藻与悬浮物对水体比辐射率都有影响，悬浮物影响更显著；在综合考虑叶绿素a和悬浮物的条件下，与传统水温反演结果相比，偏差最大可达1.21 ℃；在较低浓度的悬浮颗粒物条件下，浮游藻类叶绿素a浓度对温度反演的最大偏差达0.86 ℃，在较低浮游藻类叶绿素a浓度条件下，悬浮颗粒物浓度对温度反演的最大偏差达0.98 ℃。真实性检验结果表明，蓝藻和悬浮物浓度对温度反演的最大影响值达到0.78 ℃，多数验证点的影响值在0.53~0.78 ℃之间。研究表明，引入蓝藻与悬浮物浓度的比辐射率校正函数能够有效降低水体表面温度的遥感反演误差。
|
| 关 键 词： | 叶绿素a浓度 悬浮物浓度 比辐射率 表面温度反演 |
| 收稿时间： | 2018-03-16 |
| 修稿时间： | 2018-05-17 |
Water body emissivity measurement in Taihu Lake and its application in the watersurface temperature retrieval using the MODIS datasets |
| |
| YAN Fuli,LIN Yasen,WANG Shixin,ZHOU Yi. Water body emissivity measurement in Taihu Lake and its application in the watersurface temperature retrieval using the MODIS datasets[J]. , 2019, 36(6): 784-793. DOI: 10.7523/j.issn.2095-6134.2019.06.009 |
| |
| Authors: | YAN Fuli LIN Yasen WANG Shixin ZHOU Yi |
| |
| Affiliation: | 1. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China;2. University of Chinese Academy of Sciences, Beijing 100049, China |
| |
| Abstract: | Emissivity of the surface target is an important parameter for remote sensing surface temperature retrieval, and the changes of water constituents bring about changes of water physical property and influence emissivity. However, studies on influences of water body constituent on emissivity are rare at the present. In this study, we determined the influences of blue-green algae and suspended sediments on water body emissivity using the Nicolet iS50 FT-IR spectrometer of Thermos Scientific Co. Ltd with an integrating sphere of the PIKE technologies, and proposed a method to obtain case II water emissivity. Based on the classic split window method and the MODIS datasets, we compared the water surface temperature retrieved using the proposed emissivity with the temperature retrieved using the widely-used water emissivity. Analysis indicates that blue-green algae and suspend solid do have influences on water body emissivity, and suspend solid has greater influence. The maximum influence on surface temperature retrieval is 1.21℃ when we take blue-green algae and suspend solid into a comprehensive consideration. The maximum influence of blue-green algae is 0.86℃ when suspend solid concentration is low. The maximum influence of suspend solid is 0.98℃ when blue-green algae concentration is low. In the actual retrieval and authenticity test, the concentrations of blue-green algae and suspended solid are low, the overall maximum influence on surface temperature retrieval is 0.78℃, and the impacts at most of the validation samples are between 0.53℃ and 0.78℃. Experiment shows that the introduction of emissivity correction function based on the chlorophyll-a concentrations of the blue-green algae and suspended sediments considerably reduces errors in water surface temperature retrieval. |
| |
| Keywords: | concentration of the chlorophyll a concentration of suspended sediments emissivity surface temperature retrieval |
|
| 点击此处可从《中国科学院大学学报》浏览原始摘要信息 |
|
点击此处可从《中国科学院大学学报》下载全文 |
