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

IF 5.7 Q1 ENVIRONMENTAL SCIENCES Science of Remote Sensing Pub Date : 2024-07-26 DOI:10.1016/j.srs.2024.100152
Shunlin Liang , Tao He , Jianxi Huang , Aolin Jia , Yuzhen Zhang , Yunfeng Cao , Xiaona Chen , Xidong Chen , Jie Cheng , Bo Jiang , Huaan Jin , Ainong Li , Siwei Li , Xuecao Li , Liangyun Liu , Xiaobang Liu , Han Ma , Yichuan Ma , Dan-Xia Song , Lin Sun , Liulin Song
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Abstract

For 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.

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高分辨率陆地表面卫星产品的进展 :反演算法、产品和挑战综合评述
在许多应用中,原始卫星观测数据需要转换成各种基本环境变量的高级产品。虽然有许多千米级空间分辨率的产品,但很少有高空间分辨率(10-30 米)的全球产品,这在文献中也被称为精细或中等分辨率。为促进更多高空间分辨率产品的开发,本文系统回顾了反演算法的最新进展以及公开的区域和全球产品。我们首先盘点了现有的高分辨率卫星数据,然后介绍了用于确定云层掩蔽、估算气溶胶光学深度以及为陆地表面反射率检索进行大气校正和地形校正的不同算法。本文大部分内容回顾了四大类 18 个变量的反演算法和现有的区域到全球产品:1) 陆地表面辐射,包括宽带反照率、陆地表面温度和全波净辐射;2) 陆地生态系统变量,包括叶面积指数、吸收的光合有效辐射分量、植被覆盖率分量、森林覆盖率分量、树高、森林地上生物量总初级生产量、净初级生产量和农作物产量;3) 水循环和冰冻圈,包括土壤水分、蒸发蒸腾和积雪覆盖;以及 4) 地表类型,如全球土地覆盖、不透水表面、内陆水域、作物类型和火灾。由于云层污染,现有的大区域产品通常在空间上是不连续的,因此我们介绍了不同的数据融合和数据同化算法,以及一些用于生成空间上无缝、时间上连续的产品。最后,我们讨论了生成全球高空间分辨率卫星产品所面临的各种挑战。
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