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Article: Advancements in high-resolution land surface satellite products: A comprehensive review of inversion algorithms, products and challenges

TitleAdvancements in high-resolution land surface satellite products: A comprehensive review of inversion algorithms, products and challenges
Authors
KeywordsAlgorithm
High-resolution
Land
Landsat
Satellite products
Issue Date1-Dec-2024
PublisherElsevier
Citation
Science of Remote Sensing, 2024, v. 10 How to Cite?
AbstractFor many applications, raw satellite observations need to be converted to high-level products of various essential environmental variables. While numerous products are available at kilometer spatial resolutions, there are few global products at high spatial resolutions (10–30 m), which are also referred to fine or medium resolutions in the literature. To facilitate the development of more high spatial resolution products, this paper systematically reviews the state-of-the-art progress on inversion algorithms and publicly available regional and global products. We begin with an inventory of available high-resolution satellite data, and then present different algorithms for determining cloud masks, estimating aerosol optical depth, and performing atmospheric correction and topographic correction for land surface reflectance retrieval. The majority of this paper reviews the inversion algorithms and existing regional to global products of 18 variables in four major categories: 1) Land surface radiation, including broadband albedo, land surface temperature, and all-wave net radiation; 2) Terrestrial ecosystem variables, including leaf area index, fraction of absorbed photosynthetically active radiation, fractional vegetation cover, fractional forest cover, tree height, forest above-ground biomass gross primary production, net primary production, and agricultural crop yield; 3) Water cycle and cryosphere, including soil moisture, evapotranspiration, and snow cover; and 4) Land surface types, such as global land cover, impervious surface, inland water, crop type, and fire. Since the existing products over large regions are usually spatially discontinuous due to cloud contamination, different data fusion and data assimilation algorithms and some products for producing spatially seamless and temporally continuous products are presented. In the end, we discuss a variety of challenges in generating global high spatial resolution satellite products.
Persistent Identifierhttp://hdl.handle.net/10722/347862
ISSN
2023 Impact Factor: 5.7
2023 SCImago Journal Rankings: 2.372

 

DC FieldValueLanguage
dc.contributor.authorLiang, Shunlin-
dc.contributor.authorHe, Tao-
dc.contributor.authorHuang, Jianxi-
dc.contributor.authorJia, Aolin-
dc.contributor.authorZhang, Yuzhen-
dc.contributor.authorCao, Yunfeng-
dc.contributor.authorChen, Xiaona-
dc.contributor.authorChen, Xidong-
dc.contributor.authorCheng, Jie-
dc.contributor.authorJiang, Bo-
dc.contributor.authorJin, Huaan-
dc.contributor.authorLi, Ainong-
dc.contributor.authorLi, Siwei-
dc.contributor.authorLi, Xuecao-
dc.contributor.authorLiu, Liangyun-
dc.contributor.authorLiu, Xiaobang-
dc.contributor.authorMa, Han-
dc.contributor.authorMa, Yichuan-
dc.contributor.authorSong, Dan Xia-
dc.contributor.authorSun, Lin-
dc.contributor.authorYao, Yunjun-
dc.contributor.authorYuan, Wenping-
dc.contributor.authorZhang, Guodong-
dc.contributor.authorZhang, Yufang-
dc.contributor.authorSong, Liulin-
dc.date.accessioned2024-10-01T00:30:48Z-
dc.date.available2024-10-01T00:30:48Z-
dc.date.issued2024-12-01-
dc.identifier.citationScience of Remote Sensing, 2024, v. 10-
dc.identifier.issn2666-0172-
dc.identifier.urihttp://hdl.handle.net/10722/347862-
dc.description.abstractFor many applications, raw satellite observations need to be converted to high-level products of various essential environmental variables. While numerous products are available at kilometer spatial resolutions, there are few global products at high spatial resolutions (10–30 m), which are also referred to fine or medium resolutions in the literature. To facilitate the development of more high spatial resolution products, this paper systematically reviews the state-of-the-art progress on inversion algorithms and publicly available regional and global products. We begin with an inventory of available high-resolution satellite data, and then present different algorithms for determining cloud masks, estimating aerosol optical depth, and performing atmospheric correction and topographic correction for land surface reflectance retrieval. The majority of this paper reviews the inversion algorithms and existing regional to global products of 18 variables in four major categories: 1) Land surface radiation, including broadband albedo, land surface temperature, and all-wave net radiation; 2) Terrestrial ecosystem variables, including leaf area index, fraction of absorbed photosynthetically active radiation, fractional vegetation cover, fractional forest cover, tree height, forest above-ground biomass gross primary production, net primary production, and agricultural crop yield; 3) Water cycle and cryosphere, including soil moisture, evapotranspiration, and snow cover; and 4) Land surface types, such as global land cover, impervious surface, inland water, crop type, and fire. Since the existing products over large regions are usually spatially discontinuous due to cloud contamination, different data fusion and data assimilation algorithms and some products for producing spatially seamless and temporally continuous products are presented. In the end, we discuss a variety of challenges in generating global high spatial resolution satellite products.-
dc.languageeng-
dc.publisherElsevier-
dc.relation.ispartofScience of Remote Sensing-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectAlgorithm-
dc.subjectHigh-resolution-
dc.subjectLand-
dc.subjectLandsat-
dc.subjectSatellite products-
dc.titleAdvancements in high-resolution land surface satellite products: A comprehensive review of inversion algorithms, products and challenges-
dc.typeArticle-
dc.identifier.doi10.1016/j.srs.2024.100152-
dc.identifier.scopuseid_2-s2.0-85200231848-
dc.identifier.volume10-
dc.identifier.eissn2666-0172-
dc.identifier.issnl2666-0172-

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