China Collection 1.1: an aerosol optical depth dataset at 1km resolution over mainland China retrieved from satellite data

被引:0
|
作者
Xue, Yong [1 ,2 ]
He, Xingwei [1 ,4 ]
Xu, Hui [1 ,4 ]
Guang, Jie [1 ]
Yang, Leiku [3 ]
机构
[1] Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing Applicat Chinese Acad Sci & B, Inst Remote Sensing Applicat, Beijing 100101, Peoples R China
[2] London Metropolitan Univ, Fac Comp, London N7 8DB, England
[3] Beijing Normal Univ, Sch Geog, Beijing 100875, Peoples R China
[4] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
关键词
SRAP; AOD; China Collection 1.1; MODIS; ALBEDO; CLOUDS;
D O I
10.1117/12.975846
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
NASA's Moderate Resolution Imaging Spectro-radiometer (MODIS) sensors have been observing the Earth from polar orbit, from Terra since early 2000 and from Aqua since mid-2002._MODIS is uniquely suited for characterization of aerosols, combining broad swath size, multi-band spectral coverage and moderately high spatial resolution imaging. By using MODIS data, many algorithms have showed excellent competence at the aerosol distribution and properties retrieval. However, in China, many regions are not satisfied with the dark density pixel condition. In this paper, aerosol optical depth (AOD) datasets (China Collection 1.1) at 1 km resolutions have been derived from the MODIS data using the Synergetic Retrieval of Aerosol Properties (SRAP) method over mainland China for the period from August 2002 to now, comprising AODs at 470, 550, and 660 nm. We compared the China Collection 1.1 AOD datasets for 2010 with AERONET data. From those 2460 collocations, representing mutually cloud-free conditions, we find that 62% of China Collection 1.1 AOD values comparing with AERONET-observed values within an expected error envelop of 20% and 55% within an expected error envelop of 15%. Compared with MODIS Level 2 aerosol products, China Collection 1.1 AOD datasets have a more complete coverage with fewer data gaps over the study region.
引用
收藏
页数:7
相关论文
共 50 条
  • [41] Developing an annual building volume dataset at 1-km resolution from 2001 to 2019 in China
    Yan, Wenting
    Wu, Jianping
    Zhang, Chaoqun
    Chen, Xiuzhi
    Ren, Jiashun
    Xiao, Zhenzhen
    Liao, Ziyin
    Lafortezza, Raffaele
    Li, Xueyan
    Su, Yongxian
    INTERNATIONAL JOURNAL OF DIGITAL EARTH, 2024, 17 (01)
  • [42] Observation of an agricultural biomass burning in central and east China using merged aerosol optical depth data from multiple satellite missions
    Xue, Y.
    Xu, H.
    Guang, J.
    Mei, L.
    Guo, J.
    Li, C.
    Mikusauskas, R.
    He, X.
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2014, 35 (16) : 5971 - 5983
  • [43] A Long-Term Historical Aerosol Optical Depth Data Record (1982-2011) Over China From AVHRR
    Gao, Ling
    Chen, Lin
    Li, Jun
    Heidinger, Andrew K.
    Xu, Xiaofeng
    Qin, Shiguang
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2019, 57 (05): : 2467 - 2480
  • [44] 1 km-resolution gridded dataset of phosphorus rate for rice wheat and maize in China over 2004–2016
    Wenmeng Zhang
    Tianyi Zhang
    Xiaoguang Yang
    Scientific Data, 10
  • [45] Evaluation and Comparison of MODIS Collection 6.1 and Collection 6 Dark Target Aerosol Optical Depth over Mainland China Under Various Conditions Including Spatiotemporal Distribution, Haze Effects, and Underlying Surface
    Huang, Y.
    Zhu, B.
    Zhou, X.
    Chen, D.
    Zhu, Z.
    Zhang, T.
    Gong, W.
    Ji, Y.
    Xia, X.
    Wang, L.
    EARTH AND SPACE SCIENCE, 2019, 6 (12) : 2575 - 2592
  • [46] Spatio-temporal variation and impact factors analysis of satellite-based aerosol optical depth over China from 2002 to 2015
    He, Qingqing
    Zhang, Ming
    Huang, Bo
    ATMOSPHERIC ENVIRONMENT, 2016, 129 : 79 - 90
  • [47] Variation and Driving Factor of Aerosol Optical Depth over the South China Sea from 1980 to 2020
    Sun, Enwei
    Fu, Chuanbo
    Yu, Wei
    Xie, Ying
    Lu, Yiwen
    Lu, Chunsong
    ATMOSPHERE, 2022, 13 (03)
  • [48] A daily high-resolution (1 km) human thermal index collection over the North China Plain from 2003 to 2020
    Li, Xiang
    Luo, Ming
    Zhao, Yongquan
    Zhang, Hui
    Ge, Erjia
    Huang, Ziwei
    Wu, Sijia
    Wang, Peng
    Wang, Xiaoyu
    Tang, Yu
    SCIENTIFIC DATA, 2023, 10 (01)
  • [49] A daily high-resolution (1 km) human thermal index collection over the North China Plain from 2003 to 2020
    Xiang Li
    Ming Luo
    Yongquan Zhao
    Hui Zhang
    Erjia Ge
    Ziwei Huang
    Sijia Wu
    Peng Wang
    Xiaoyu Wang
    Yu Tang
    Scientific Data, 10
  • [50] Spatio-temporal variations in aerosol optical and cloud parameters over Southern India retrieved from MODIS satellite data
    Balakrishnaiah, G.
    Kumar, K. Raghavendra
    Reddy, B. Suresh Kumar
    Gopal, K. Rama
    Reddy, R. R.
    Reddy, L. S. S.
    Swamulu, C.
    Ahammed, Y. Nazeer
    Narasimhulu, K.
    KrishnaMoorthy, K.
    Babu, S. Suresh
    ATMOSPHERIC ENVIRONMENT, 2012, 47 : 435 - 445