Estimating fractional snow cover in vegetated environments using MODIS surface reflectance data
文献类型：期刊论文
| 作者 | Xiao, Xiongxin4; He, Tao4; Liang, Shunlin3; Liu, Xinyan4; Ma, Yichuan4; Liang, Shuang2; Chen, Xiaona1 |
| 刊名 | INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
 |
| 出版日期 | 2022-11-01 |
| 卷号 | 114页码:23 |
| 关键词 | Fractional snow cover MODIS Forest cover Viewing angle North America |
| ISSN号 | 1569-8432 |
| DOI | 10.1016/j.jag.2022.103030 |
| 通讯作者 | He, Tao(taohers@whu.edu.cn) |
| 英文摘要 | Advances in snow-cover mapping techniques have resulted in more accurate estimation of fractional snow cover (FSC) in areas with no vegetation; however, vegetation interference limits the accuracy of available snow cover information from satellite observations. The aim of this study was to develop a robust and enhanced FSC-retrieval algorithm using Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance data for vegetated areas. The experiments were conducted in North America, where vegetation cover is complex and heterogeneous, using 28 Landsat-8 - MODIS image pairs acquired for the entire snow cover season (September 2015-May 2016). The FSC retrieval models were established from 20 sub-models based on the Extremely Randomized Trees method incorporating input information from multiple sources, such as commonly used variables, vegetationand snow-related variables, location and geometry related variables, and other auxiliary variables. The FSC retrieval models were divided into forest- and non-forest types. We further investigated a canopy correction method to mitigate vegetation interference effects caused by the viewing geometry of satellite observations. The results show that the integration of 20 sub-models largely decreased model dependence on the training sample quality and improved the robustness of the model predictions. In the validation of the independent dataset, there was a noticeable improvement in FSC estimation for different land-cover and vegetation-cover types, with rootmean-square errors (RMSEs) reduced by an average of 11% compared to the Trimmed-Model. The application of canopy correction under the "Recommend" conditions (i.e., viewing zenith angle in [45 degrees , 70 degrees] and fraction of forest cover in [0, 0.3]) improved the FSC prediction accuracy. Moreover, based on a comparison with the MOD10A1-based FSC map, our FSC estimation showed improved consistency across various vegetation coverages based on the Landsat reference FSC values, with 40% lower RMSEs and 8% increase in overall accuracy. |
| WOS关键词 | GRAIN-SIZE ; SPECTRAL REFLECTANCE ; FOREST CANOPY ; RETRIEVAL ; ALBEDO ; ALGORITHM ; TEMPERATURE ; AREA ; PRODUCTS ; DRIVEN |
| 资助项目 | National Natural Science Foundation of China[42090012] ; Hubei Province Natural Science Foundation[2021CFA082] ; National Key Research and Development Program of China[2020YFA0608704] |
| WOS研究方向 | Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:000868791600001 |
| 出版者 | ELSEVIER |
| 资助机构 | National Natural Science Foundation of China ; Hubei Province Natural Science Foundation ; National Key Research and Development Program of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/186243]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | He, Tao |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 2.Chinese Acad Sci, Aerosp Informat Res Inst, Beijing 100094, Peoples R China 3.Univ Hong Kong, Dept Geog, Hong Kong 999077, Peoples R China 4.Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430079, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xiao, Xiongxin,He, Tao,Liang, Shunlin,et al. Estimating fractional snow cover in vegetated environments using MODIS surface reflectance data[J]. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,2022,114:23. |
| APA | Xiao, Xiongxin.,He, Tao.,Liang, Shunlin.,Liu, Xinyan.,Ma, Yichuan.,...&Chen, Xiaona.(2022).Estimating fractional snow cover in vegetated environments using MODIS surface reflectance data.INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,114,23. |
| MLA | Xiao, Xiongxin,et al."Estimating fractional snow cover in vegetated environments using MODIS surface reflectance data".INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 114(2022):23. |
入库方式： OAI收割
来源：地理科学与资源研究所
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