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台湾岛高分一号卫星WFV数据气溶胶反演与验证
引用本文:贾亮亮,汪小钦,苏华,王峰.台湾岛高分一号卫星WFV数据气溶胶反演与验证[J].环境科学学报,2018,38(3):1117-1127.
作者姓名:贾亮亮  汪小钦  苏华  王峰
作者单位:福州大学空间数据挖掘和信息共享教育部重点实验室, 福建省空间信息工程研究中心, 福州 350002,福州大学空间数据挖掘和信息共享教育部重点实验室, 福建省空间信息工程研究中心, 福州 350002,福州大学空间数据挖掘和信息共享教育部重点实验室, 福建省空间信息工程研究中心, 福州 350002,福州大学空间数据挖掘和信息共享教育部重点实验室, 福建省空间信息工程研究中心, 福州 350002
基金项目:国家重点研发计划(No.20017YFB0504203);中央引导地方发展专项(No.2017L3012);海西政务大数据应用协同创新中心资助项目
摘    要:针对国产中等分辨率遥感数据的特性,集成暗像元和深蓝算法的优势,提供了一种能够同时对低反射率和高反射率地表类型实现AOD反演的方法.基于该方法,以台湾岛为例,利用高分一号卫星(GF-1)WFV数据反演得到550 nm处的AOD.与MODIS气溶胶产品(MOD04)进行比较,二者空间分布具有很好的一致性,总体相关系数r优于0.9.利用全球气溶胶自动观测网(AERONET)站点数据进行反演结果的验证.反演结果与AERONET实测值具显著的相关性(r0.85),70%的反演结果满足误差精度要求.通过与暗像元法、深蓝算法的反演结果进行对比,本文方法在结果精度和空间覆盖度方面具有独特的优势.在台湾岛地区,夏、冬季分别采用海洋型和大陆型气溶胶模式比较适合;随着GF-1卫星数据空间分辨率的降低,气溶胶反演结果与地基观测值的相关性系数呈现先降低、后平稳的趋势,但整体变化不是太大.

关 键 词:高分一号  暗像元法  深蓝算法  气溶胶光学厚度(AOD)  台湾  6S模型
收稿时间:2017/7/25 0:00:00
修稿时间:2017/9/29 0:00:00

Validation of retrieving aerosol over Taiwan Island using GF-1 satellite WFV data
JIA Liangliang,WANG Xiaoqin,SU Hua and WANG Feng.Validation of retrieving aerosol over Taiwan Island using GF-1 satellite WFV data[J].Acta Scientiae Circumstantiae,2018,38(3):1117-1127.
Authors:JIA Liangliang  WANG Xiaoqin  SU Hua and WANG Feng
Institution:Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education, National Engineering Research Center of Spatial Information Technology, Fuzhou University, Fuzhou 350002,Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education, National Engineering Research Center of Spatial Information Technology, Fuzhou University, Fuzhou 350002,Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education, National Engineering Research Center of Spatial Information Technology, Fuzhou University, Fuzhou 350002 and Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education, National Engineering Research Center of Spatial Information Technology, Fuzhou University, Fuzhou 350002
Abstract:According to the characteristics of domestic medium-resolution remote sensing data, we proposed a new method for retrieving aerosol optical depth (AOD) from optical images by integrating the advantages of dark-pixel and deep-blue algorithms. The method was proved to be effective and suitable for AOD estimation over both low-reflectivity and high-reflectivity surface cover types. Here, we estimated AOD at 550 nm over Taiwan Island based on GF-1 WFV data, and the results were compared with MODIS AOD products (MOD04). The spatial distributions of AOD from GF-1 are well consistent with those from MOD04 (r>0.9). Moreover, the inversion results were validated by using the ground-measured AODs from AERONET. The retrieved AOD is significantly correlated with the AERONET data (r>0.85), and about 70% of the estimated results meet the accuracy requirement. Compared with the dark-pixel and deep-blue algorithms, the proposed method has distinctive advantages in terms of estimation accuracy and spatial coverage. In Taiwan Island, the marine and continental aerosol types are suitable for AOD estimation in summer and winter, respectively. With the decrease of spatial resolution of GF-1 images, the correlation coefficient between the image-estimation and ground-observation AOD presents a trend of decline first and then stable, while the overall change is not significant.
Keywords:GF-1  dark pixel  deep blue  aerosol optical depth (AOD)  Taiwan  6S model
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