HJ-1A卫星CCD1数据的大气校正及在滇池蓝藻监测中的应用
Atmospheric Correction of HJ-1ACCD1 Data and Its Application in Cyanobacteria Bloom Monitoring in Dian Chi Lake
投稿时间:2014-02-17  修订日期:2014-03-27
DOI:
中文关键词:CCD1  大气校正  6S模型  滇池  蓝藻
英文关键词:CCD1  atmospheric correction  6S model  Dian Chi  Cyanobacteria
基金项目:国家高科技研究发展计划(863计划)(编号:2012AA121402);高等学校博士学科点专项科研基金联合资助课题(编号:20115303110002)
作者单位E-mail
杨荣 云南师范大学旅游与地理科学学院昆明 650500西部资源环境地理信息技术教育部工程研究中心昆明650500 xixi8708@163.com 
杨昆* 云南师范大学信息学院昆明650500 西部资源环境地理信息技术教育部工程研究中心昆明650500 kmdcynu@163.com 
洪亮 云南师范大学旅游与地理科学学院昆明 650500西部资源环境地理信息技术教育部工程研究中心昆明650500  
王倍倍 云南师范大学旅游与地理科学学院昆明 650500西部资源环境地理信息技术教育部工程研究中心昆明650500  
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中文摘要:
      HJ-1A卫星CCD1数据具有免费、高空间分辨率等优点。但是由于受大气的影响,电磁波在传输过程中发生失真,为了提高CCD1数据的提取精度,就必须对其进行大气校正。本文利用6S模型对2013年9月30日的HJ-1A卫星CCD1数据进行了大气校正,并从归一化植被指数(NDVI)的变化、与中分辨率成像光谱仪(MODIS)地表反射率数据对比2个方面对校正结果进行精度验证。结果表明:NDVI的标准差校正前为0.179866,校正后为0.247689,大气校正能够有效的降低大气对遥感图像造成的影响,图像的层次更加丰富;在滇池的建筑物、水体、植被3种地物中分别选取1个像元,获得CCD1数据和MODIS数据分别在这3个像元上的反射率值。3种地物的地表反射率在2种数据中都具有较好的一致性,在4个波段的误差均在15%左右。对于水体,波段3和波段4的误差较小(<10%),建议在进行滇池水质参数反演时尽量选用3、4波段。利用经过大气校正后的CCD1数据计算NDVI并结合密度分割的方法对滇池蓝藻信息进行了提取,提取的结果与滇池蓝藻实测数据具有较好的相关性,相关系数达到0.7703,说明利用HJ-1A卫星CCD1数据可以快速、动态地监测滇池蓝藻暴发。
英文摘要:
      The aim of this study focused on the atmospheric correction of HJ-1ACCD1 image and its application in cyanobacteria bloom monitoring in Dian Chi Lake. In this paper, the atmospheric correction for the HJ-1ACCD1 image took on September 30, 2013 was made by using 6S model (Second Simulation of Satellite Signal in the Solar Spectrum) to reduce the influence of atmosphere on the extraction accuracy of HJ-1ACCD1 image. The accuracy of atmospheric correction on HJ-1ACCD1 was verified through the variations of normalized difference vegetation index (NDVI) and the comparison of HJ-1ACCD1 surface reflectance and moderate-resolution imaging spectroradiometer (MODIS) surface reflectance. The results showed that the standard deviation of NDVI was 0.179866 before correction, but was 0.247689 after correction, indicating that atmospheric correction can effectively reduce the impact of atmosphere on remote sensing image and improve the quality of image with richer gradation. The reflectance values of buildings, water and vegetation in Dian Chi Lake from CCD1 and MODIS agreed well with each other, with the errors of less than 15% in the four wave bands, especially in Band 3 and Band 4, which was less than 10% for the reflectance values of water. As a result, it is suggested to use Band 3 and Band 4 for the inversion of water quality parameters in Dian Chi Lake. Cyanobacteria information in Dian Chi Lake, which was extracted using density segmentation method and NDVI calculated by CCD1 data after atmospheric correction, was correlated with (approximated) the measured data of Cyanobacteria in Dian Chi Lake with high correlation coefficient of 0.7703, indicating that HJ-1ACCD1 data can timely demonstrate the dynamic of Cyanobacterial blooms.
杨荣,杨昆,洪亮,王倍倍.2014.HJ-1A卫星CCD1数据的大气校正及在滇池蓝藻监测中的应用[J].水生态学杂志,35(4):8-14.
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