| 基于Landsat8影像估算新安江水库光合有效辐射漫射衰减系数 |
| 摘要点击 1529 全文点击 1000 投稿时间：2015-06-09 修订日期：2015-08-01 |
| 查看HTML全文
查看全文 查看/发表评论 下载PDF阅读器 |
| 中文关键词 Landsat 8 新安江水库 PAR漫射衰减系数 经验方法 遥感估算 |
| 英文关键词 Landsat 8 data Xin'anjiang Reservoir PAR diffuse attenuation coefficient empirical method remote sensing estimation |
| 作者 | 单位 | E-mail | | 张毅博 | 南京师范大学虚拟地理环境教育部重点实验室, 江苏省地理信息资源开发与利用协同创新中心, 南京 210023
中国科学院南京地理与湖泊研究所湖泊与环境国家重点实验室, 南京 210008 | hbxgzyb@126.com | | 张运林 | 中国科学院南京地理与湖泊研究所湖泊与环境国家重点实验室, 南京 210008 | ylzhang@niglas.ac.cn | | 査勇 | 南京师范大学虚拟地理环境教育部重点实验室, 江苏省地理信息资源开发与利用协同创新中心, 南京 210023 | | | 施坤 | 中国科学院南京地理与湖泊研究所湖泊与环境国家重点实验室, 南京 210008 | | | 周永强 | 中国科学院南京地理与湖泊研究所湖泊与环境国家重点实验室, 南京 210008
中国科学院大学, 北京 100049 | | | 刘明亮 | 杭州市环境保护科学研究院, 杭州 310014 | |
|
| 中文摘要 |
| 光合有效辐射(photosynthetically active radiation,PAR)是指可以被植物利用并进行光合作用的那部分太阳辐射,其进入湖水后受光学组分(悬浮颗粒、有色可溶性有机物和浮游植物)的吸收和散射作用发生衰减,对湖泊生物的密度和分布具有重要影响. 本研究构建了基于Landsat 8影像数据的较为清洁的新安江水库PAR漫衰减系数的遥感估算模型,进而分析其时空分布特征及主要影响因素. 结果表明, 利用Landsat 8的第二、三和第八波段构建的多元回归模型能够得到较为准确的估算结果,模型决定系数为0.87. 利用独立样本对构建的模型验证,预测值和实测值相对误差绝对值均值为9.16%,均方根误差为0.06 m-1,由此可见利用Landsat 8数据的3个波段,采用多元回归模型能够较好地估算较清洁水体的PAR漫射衰减系数. 基于14景Landsat 8影像发现,新安江水库PAR漫射衰减系数季节差异性明显,秋季(9~11月)和夏季(6~8月)PAR漫射衰减系数较高,分别为(0.82±0.60)m-1和(0.77±0.41)m-1,而冬季(12~次年2月)和春季(3~5月)PAR漫射衰减系数相对较低,分别为(0.56±0.50)m-1和(0.40±0.45)m-1. 新安江水库PAR漫射衰减系数空间差异性显著,全湖PAR漫射衰减系数变化范围为(0.002~13.86)m-1,均值为(0.64±0.49)m-1. 漫射衰减系数的季节变化主要是由季节性降雨和浮游植物季节性生长引起,空间差异性主要由外源河流输入和部分水域采砂过程导致悬浮物浓度变化引起. |
| 英文摘要 |
| Photosynthetically active radiation (PAR) is defined as the wavelength band of 400 to 700 nm, representing most of the visible solar radiation that could be used for photosynthesis. PAR is attenuated by the absorption and scattering of nonpigment suspended matter, chromophoric dissolved organic matter and phytoplankton, and it plays an important role in determining the density and distribution of aquatic organisms. This study developed an empirical model and presented the spatial-temporal distribution of PAR diffuse attenuation coefficient [Kd(PAR)] for the slightly turbid Xin'anjiang Reservoir based on the in situ ground data and the matching Landsat 8 data. The results showed that the three-band combinational model of Kd(PAR) using Band 2, Band 3 and Band 8 could give a reasonable and acceptable estimation accuracy with a determination coefficient of 0.87. Independent dataset was used to validate the model with a mean relative error of 9.16% and a root mean square error of 0.06 m-1. Therefore, the three-band combination using Landsat 8 data could be used to accurately estimate Kd(PAR) in the slightly turbid Xin'anjiang Reservoir. Kd(PAR) exhibited significant seasonal and spatial differences. Kd(PAR) was higher in autumn (September-November) and summer (June-August) with the average Kd(PAR) of (0.82±0.60) m-1and (0.77±0.41) m-1, but lower in winter (December-February) and spring (March-May) with the average Kd(PAR) of (0.56±0.50) m-1 and (0.40±0.45) m-1, respectively. Spatially, Kd(PAR) ranged from 0.002 to 13.86 m-1 with an average of (0.64±0.49) m-1. The temporal heterogeneity of Kd(PAR) was mainly caused by the seasonal rainfall and seasonal growth of phytoplankton. The spatial heterogeneity was mainly caused by suspended matter concentration derived from watershed inputs and human dredging activity. |
|
|
|
