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

被引:12
作者
Liang, Shunlin [1 ]
He, Tao [2 ]
Huang, Jianxi [3 ,4 ]
Jia, Aolin [5 ]
Zhang, Yuzhen [6 ]
Cao, Yunfeng [7 ]
Chen, Xiaona [8 ]
Chen, Xidong [9 ]
Cheng, Jie [10 ,11 ]
Jiang, Bo [10 ,11 ]
Jin, Huaan [12 ,13 ]
Li, Ainong [12 ,13 ]
Li, Siwei [2 ]
Li, Xuecao [3 ,4 ]
Liu, Liangyun [14 ]
Liu, Xiaobang [15 ]
Ma, Han [1 ]
Ma, Yichuan [2 ]
Song, Dan-Xia [16 ,17 ]
Sun, Lin [18 ]
Yao, Yunjun [10 ,11 ]
Yuan, Wenping [19 ]
Zhang, Guodong [20 ]
Zhang, Yufang [21 ]
Song, Liulin [10 ,11 ]
机构
[1] Univ Hong Kong, Dept Geog, Jockey Club STEM Lab Quantitat Remote Sensing, Hong Kong 999077, Peoples R China
[2] Wuhan Univ, Sch Remote Sensing & Informat Engn, Hubei Key Lab Quantitat Remote Sensing Land & Atmo, Wuhan 430079, Peoples R China
[3] China Agr Univ, Coll Land Sci & Technol, Beijing 100083, Peoples R China
[4] Minist Agr & Rural Affairs, Key Lab Remote Sensing Agrihazards, Beijing 100083, Peoples R China
[5] Luxembourg Inst Sci & Technol LIST, Environm Res & Innovat ERIN Dept, 41 Rue Brill, L-4422 Belvaux, Luxembourg
[6] Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing Engn Res Ctr Ind Spectrum Imaging, Beijing 100083, Peoples R China
[7] Beijing Forestry Univ, Precis Forestry Key Lab Beijing, Beijing 100083, Peoples R China
[8] Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
[9] Univ Hong Kong, Future Urban & Sustainable Environm FUSE Lab, Hong Kong 999007, Peoples R China
[10] Beijing Normal Univ, Fac Geog Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China
[11] Beijing Normal Univ, Fac Geog Sci, Beijing Engn Res Ctr Global Land Remote Sensing Pr, Beijing 100875, Peoples R China
[12] Chinese Acad Sci, Res Ctr Digital Mt & Remote Sensing Applicat, Inst Mt Hazards & Environm, Chengdu 610041, Peoples R China
[13] Wanglang Mt Remote Sensing Observat & Res Stn Sich, Mianyang 621000, Peoples R China
[14] Chinese Acad Sci, Aerosp Informat Res Inst, Beijing 100094, Peoples R China
[15] Elect Technol Grp Corp, Res Inst China 27, Zhengzhou 450047, Peoples R China
[16] Cent China Normal Univ, Hubei Prov Key Lab Geog Proc Anal & Simulat, Wuhan 430079, Peoples R China
[17] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China
[18] Shandong Univ Sci & Technol, Geomat Coll, Qingdao 266590, Shandong, Peoples R China
[19] Peking Univ, Inst Carbon Neutral, Sino French Inst Earth Syst Sci, Coll Urban & Environm Sci, Beijing 100091, Peoples R China
[20] Southwest Jiaotong Univ, Fac Geosci & Environm Engn, Chengdu 610031, Peoples R China
[21] Northwestern Polytech Univ, Sch Software, Xian 710072, Peoples R China
来源
SCIENCE OF REMOTE SENSING | 2024年 / 10卷
基金
中国国家自然科学基金;
关键词
Satellite products; High-resolution; Land; Algorithm; Landsat; LEAF-AREA INDEX; FRACTIONAL VEGETATION COVER; GROSS PRIMARY PRODUCTION; FOREST CANOPY COVER; TOPOGRAPHIC CORRECTION METHODS; REMOTE-SENSING DATA; BROAD-BAND ALBEDO; WAVE-FORM LIDAR; EMISSIVITY SEPARATION ALGORITHM; CLOUD DETECTION ALGORITHM;
D O I
10.1016/j.srs.2024.100152
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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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页数:49
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