Spatial scale of chlorophyll-a concentration in Lake Taihu by using remote sensing images

China Symposium on Remote Sensing Pub Date : 2010-09-14 DOI:10.1117/12.910421

Y. Bao, Q. Tian

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引用次数: 2

Abstract

Chlorophyll-a concentration is one of the most important indexes of Lake Eutrophication. Fine temporal and spatial resolution remote sensing images provide an effective way to monitor blue-green algae in Lake Taihu by studying the spatial distribution regularities of chla concentration. However, both low spatial resolution remote sensing images (e.g. MODIS) due to their heterogeneity and high or moderate spatial resolution remote sensing images (e.g. TM/ETM+) due to their low temporal resolution give rise to unsatisfactory estimate of chla concentration. Therefore, in this study, an effective method for estimating chla concentration using remote sensing images at different scales was developed. Chla concentration was inferred from Hyperion images at 30m resolution and MODIS images at 250m resolution. The spatial variability of Chla concentration was analyzed and Taihu Lake was divided into area with low variability and area with high variability. The quadratic polynomial (R2=0.8709) and linear (R2=0.7387) correlation was established. Finally, the obtained relationship between chla concentration estimate at different spatial scales were applied to correct the estimate from MODIS data.

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基于遥感影像的太湖叶绿素a浓度空间尺度研究

叶绿素-a浓度是湖泊富营养化的重要指标之一。精细时空分辨率遥感影像通过研究chla浓度的空间分布规律，为太湖蓝绿藻监测提供了有效途径。然而，低空间分辨率遥感图像(如MODIS)由于其异质性，以及高或中等空间分辨率遥感图像(如TM/ETM+)由于其低时间分辨率，都导致对chla浓度的估计不令人满意。因此，本研究开发了一种利用不同尺度遥感影像估算chla浓度的有效方法。Chla浓度由30m分辨率的Hyperion图像和250m分辨率的MODIS图像推断。分析了Chla浓度的空间变异性，将太湖划分为低变异性区和高变异性区。建立二次多项式相关(R2=0.8709)和线性相关(R2=0.7387)。最后，利用不同空间尺度下chla浓度估计值之间的关系对MODIS数据的估计值进行校正。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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China Symposium on Remote Sensing

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