于洋, 付迎春, 马超. 多云雨城市地区Landsat多时相影像的大气校正反射率特征评估[J]. 华南师范大学学报(自然科学版), 2018, 50(1): 77-84.
引用本文: 于洋, 付迎春, 马超. 多云雨城市地区Landsat多时相影像的大气校正反射率特征评估[J]. 华南师范大学学报(自然科学版), 2018, 50(1): 77-84.
Atmospheric Correction Assessment of Surface Reflectance for Multi-temporal Landsat Images in Cloudy and Rainy Urban Area[J]. Journal of South China Normal University (Natural Science Edition), 2018, 50(1): 77-84.
Citation: Atmospheric Correction Assessment of Surface Reflectance for Multi-temporal Landsat Images in Cloudy and Rainy Urban Area[J]. Journal of South China Normal University (Natural Science Edition), 2018, 50(1): 77-84.

多云雨城市地区Landsat多时相影像的大气校正反射率特征评估

Atmospheric Correction Assessment of Surface Reflectance for Multi-temporal Landsat Images in Cloudy and Rainy Urban Area

  • 摘要: 应用2种主要大气校正方法(LEDAPS与FLAASH),对广州城区多时相Landsat TM、ETM+和OLI传感器影像进行大气校正评估,包括连续15年大气校正前后影像的地表反射率、归一化差异植被指数NDVI、缨帽变换绿度与亮度分量和地物类别可分性Jeffreis Matusita(J-M)距离的差异比较. 结果表明:2种校正影像的校正效果在可见光波段最明显,且在不同波段表现出不同的光谱响应特征;校正后的时间序列影像反射率均具有波动性,FLAASH方法校正影像反射率波动较为显著;相对LEDAPS校正影像,FLAASH校正影像高估了近红外波段反射率,从而高估了NDVI、缨帽变换分量;成对t检验结果显示2种校正影像在二次人工林与城市用地的类别可分性上存在显著差异. 应用FLAASH校正影像的反射率计算得到较高的缨帽分量值,主要源于FLAASH对短波红外波段水汽校正的不足,证明在多云雨城市地区(如广州市),水汽对大气校正存在重要影响.

     

    Abstract: Two main atmospheric correction methods LEDAPS and FLAASH are applied to multi-temporal Landsat TM, ETM+ and OLI sensor images to complete an atmospheric correction assessment. It includes comparisons of 15 consecutive years atmospheric corrected images surface reflectance, Normalized Difference Vegetation Index (NDVI), Tasseled Cap components of Greenness and Brightness and class separability Jeffreis Matusita (J-M) distance in Guangzhou City before and after correction. The results show: two main atmospheric correction methods present the different spectral response characteristic in each band, and correction effect is the most obvious in the visible bands; both of the corrected time series images reflectance showed standard error variability, especially to FLAASH corrected images; compared with LEDAPS corrected images, FLAASH corrected images overestimate Near-Infrared(NIR) reflectance and related spectral indexes such as NDVI and Tasseled Cap components; according to paired t-test, two sets of images also show differences on the class separability of artificial vegetation cover and city areas. FLAASH corrected reflectance calculate higher tasseled cap components, which mainly come from insufficient correction of water vapor in shortwave infrared bands. For the cloudy and rainy urban areas like Guangzhou, water vapor has an important influence on atmospheric correction.

     

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