• DocumentCode
    3690416
  • Title

    China collection 2.1: Aerosol Optical Depth dataset for mainland China at 1km resolution

  • Author

    Yong Xue;Xingwei He;Hui Xu;Jie Guang;Jianping Guo;Linlu Mei

  • Author_Institution
    Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    2222
  • Lastpage
    2225
  • Abstract
    A wide range of data products have been published since the operation of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on NASA´s TERRAModerate Resolution Imaging Spectroradiometer (MODIS) sensor on NASA´s TERRA and AQUA satellites. Based on DarkTarget and DeepBlue method, NASA has published Aerosol Optical Depth (AOD) products Collection 6.0 with spatial resolution of 3km. Although validated globally, regional and systematic errors are still found in the MODIS-retrieved AOD products. This is especially remarkable for bright heterogeneous land surface, such as mainland China. In order to solve the aerosol retrieval problem over heterogeneous bright land surface, the Synergetic Retrieval of Aerosol Properties algorithm (SRAP) has been developed based on the synergetic use of the MODIS data of TERRA and AQUA satellites. Using the SRAP algorithm, we produced AOD dataset-China Collection 2.1 at 1km spatial resolution, dated from August 2002 to 2012. We compared the China Collection 2.1 AOD datasets for 2010 with AERONET data. From those 2460 collocations, representing mutually cloud-free conditions, we find that 62% of China Collection 2.1 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 2.1 AOD datasets have a more complete coverage with fewer data gaps over the study region.
  • Keywords
    "Aerosols","MODIS","Land surface","Remote sensing","Sea surface","Satellites","Clouds"
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
  • ISSN
    2153-6996
  • Electronic_ISBN
    2153-7003
  • Type

    conf

  • DOI
    10.1109/IGARSS.2015.7326247
  • Filename
    7326247