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Article: Updates on Global LAnd Surface Satellite(GLASS)products suite

TitleUpdates on Global LAnd Surface Satellite(GLASS)products suite
Authors
Keywordscarbon cycle
GLASS produces
land surface
radiation and energy budget
satellite remote sensing
Issue Date7-Apr-2023
PublisherAmerican Association for the Advancement of Science
Citation
Journal of Remote Sensing, 2023, v. 27, n. 4, p. 831-856 How to Cite?
AbstractThe 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.
Persistent Identifierhttp://hdl.handle.net/10722/350122
ISSN
2023 SCImago Journal Rankings: 0.521

 

DC FieldValueLanguage
dc.contributor.authorLiang, Shunlin-
dc.contributor.authorChen, Xiaona-
dc.contributor.authorChen, Yan-
dc.contributor.authorCheng, Jie-
dc.contributor.authorJia, Kun-
dc.contributor.authorJiang, Bo-
dc.contributor.authorLi, Bing-
dc.contributor.authorLiu, Qiang-
dc.contributor.authorMa, Han-
dc.contributor.authorSong, Liulin-
dc.contributor.authorTang, Bohui-
dc.contributor.authorXu, Jianglei-
dc.contributor.authorYao, Yunjun-
dc.contributor.authorYuan, Wenping-
dc.contributor.authorZhang, Xiaotong-
dc.contributor.authorZhang, Yuzhen-
dc.contributor.authorZhao, Xiang-
dc.contributor.authorZhou, Ji-
dc.date.accessioned2024-10-21T03:56:17Z-
dc.date.available2024-10-21T03:56:17Z-
dc.date.issued2023-04-07-
dc.identifier.citationJournal of Remote Sensing, 2023, v. 27, n. 4, p. 831-856-
dc.identifier.issn1007-4619-
dc.identifier.urihttp://hdl.handle.net/10722/350122-
dc.description.abstractThe 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.-
dc.languageeng-
dc.publisherAmerican Association for the Advancement of Science-
dc.relation.ispartofJournal of Remote Sensing-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectcarbon cycle-
dc.subjectGLASS produces-
dc.subjectland surface-
dc.subjectradiation and energy budget-
dc.subjectsatellite remote sensing-
dc.titleUpdates on Global LAnd Surface Satellite(GLASS)products suite-
dc.typeArticle-
dc.identifier.doi10.11834/jrs.20232462-
dc.identifier.scopuseid_2-s2.0-85164135937-
dc.identifier.volume27-
dc.identifier.issue4-
dc.identifier.spage831-
dc.identifier.epage856-
dc.identifier.eissn2694-1589-
dc.identifier.issnl1007-4619-

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