Updates on Global LAnd Surface Satellite (GLASS) products suite

  • role: First author第一作者
  • Affiliation:

    Department of Geography, University of Hong Kong, Hong Kong 999077, China

  • Email:shunlin@hku.hk
  • Introduction:E-mail shunlin@hku.hk
LIANG Shunlin1,  
  • Affiliation:

    State Key Laboratory of Resources and Environmental Information System,Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

CHEN Xiaona2,  
  • Affiliation:

    School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China

CHEN Yan3,  
  • Affiliation:

    State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

    Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

CHENG Jie45,  
  • Affiliation:

    State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

    Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

JIA Kun45,  
  • Affiliation:

    State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

    Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

JIANG Bo45,  
  • Affiliation:

    School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China

LI Bing3,  
  • Affiliation:

    Peng Cheng Laboratory, Shenzhen 518055, China

LIU Qiang6,  
  • Affiliation:

    Department of Geography, University of Hong Kong, Hong Kong 999077, China

MA Han1,  
  • Affiliation:

    State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

    Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

SONG Liulin45,  
  • Affiliation:

    State Key Laboratory of Resources and Environmental Information System,Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

TANG Bohui2,  
  • Affiliation:

    School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China

XU Jianglei3,  
  • Affiliation:

    State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

    Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

YAO Yunjun45,  
  • Affiliation:

    School of Atmospheric Science, Sun Yat-sen University, Guangzhou 510275, China

YUAN Wenping7,  
  • Affiliation:

    State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

    Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

ZHANG Xiaotong45,  
  • Affiliation:

    School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China

ZHANG Yuzhen8,  
  • Affiliation:

    State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

    Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

ZHAO Xiang45,  
  • Affiliation:

    School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China

ZHOU Ji9

Resümee

The Global LAnd Surface Satellite (GLASS) products suite includes high-level satellite products of land surface essential variables from multiple universities and research institutes. Producing the GLASS products suite has been undertaken since 2010. The suite spans from the initial five products to the current 16 products, which are generated mostly from the Advanced Very High-Resolution Radiometer and/or Moderate Resolution Imaging Spectroradiometer data. Some of the products have been previously introduced in the literature, and this study provides an update on the algorithm developments, validation accuracies, and their typical applications in all 16 products. This study also describes the Hi-GLASS products at 30 m resolution and some perspectives for further future improvement and development of the GLASS products.Estimating land surface variables from satellite observations is an “ill-posed” inversion problem. For each pixel, the number of multispectral bands is usually smaller than the number of environmental variables, and the values of many spectral bands are highly correlated. Some novel solutions have been proposed to address the insufficient information in generating reliable GLASS products. We can identify at least four approaches. The first is based on the temporal signature of the satellite observations. A typical example is the MODIS Leaf Area Index (LAI) and the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) products generated using two-year observations simultaneously. The second uses an algorithm ensemble. A typical example is the evapotranspiration product based on integrating five estimation algorithms. The third uses multiple satellite observations. For example, the forest aboveground biomass product is based on optical, Lidar, and microwave data products. The last incorporates the physical model to generate the products, such as the gross primary production product.The GLASS products have several unique features compared with similar products on the market, including the following:(1) Several products are unique, such as the high-resolution (1 km) broadband emissivity and time-series forest aboveground biomass products.(2) Most products have long time series (i.e., over 40 years), while most other similar global products start from approximately the year 2000, with a period of approximately 20 years.(3) The radiation products, covering the world’s land and ocean surfaces, have a spatial resolution of 5 km, which is an order of magnitude higher than other such products in wide use, for example, the Global Energy and Water Exchanges, the Clouds and the Earth’s Radiant Energy System, and the International Satellite Cloud Climatology Project, which have spatial resolutions coarser than 100 km.(4) Several long-time-series global products have the highest spatial resolution in the world, such as 250 m for the LAI, FAPAR, and albedo products and 5 km for snow cover extent. Moreover, the all-weather LST and near-surface air temperature products have a 1-km resolution.(5) GLASS products are of high quality and accuracy.Over 2000 peer-reviewed papers based on the GLASS products have been published. Their applications are distributed in many scientific disciplines and societal benefits areas.We will continue to improve the quality and accuracy of the existing GLASS products and produce more GLASS products with higher spatial resolutions.

Schlüsselwort

satellite remote sensing;land surface;GLASS produces;radiation and energy budget;carbon cycle

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