Global 500 m seamless dataset (2000–2022) of land surface reflectance generated from MODIS products

The Moderate Resolution Imaging Spectroradiometer (MODIS) is widely utilized for retrieving land surface reflectance to reflect plant conditions, detect ecosystem phenology, monitor forest fires, and constrain terrestrial energy budgets. However, the state-of-the-art MODIS surface reflectance produc...

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Published in:Earth System Science Data
Main Authors: Liang, Xiangan, Liu, Qiang, Wang, Jie, Chen, Shuang, Gong, Peng
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2024
Subjects:
Online Access:https://doi.org/10.5194/essd-16-177-2024
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spelling ftnonlinearchiv:oai:noa.gwlb.de:cop_mods_00070942 2024-02-11T10:08:08+01:00 Global 500 m seamless dataset (2000–2022) of land surface reflectance generated from MODIS products Liang, Xiangan Liu, Qiang Wang, Jie Chen, Shuang Gong, Peng 2024-01 electronic https://doi.org/10.5194/essd-16-177-2024 https://noa.gwlb.de/receive/cop_mods_00070942 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00069266/essd-16-177-2024.pdf https://essd.copernicus.org/articles/16/177/2024/essd-16-177-2024.pdf eng eng Copernicus Publications Earth System Science Data -- http://www.earth-syst-sci-data.net/volumes_and_issues.html -- http://www.bibliothek.uni-regensburg.de/ezeit/?2475469 -- 1866-3516 https://doi.org/10.5194/essd-16-177-2024 https://noa.gwlb.de/receive/cop_mods_00070942 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00069266/essd-16-177-2024.pdf https://essd.copernicus.org/articles/16/177/2024/essd-16-177-2024.pdf https://creativecommons.org/licenses/by/4.0/ uneingeschränkt info:eu-repo/semantics/openAccess article Verlagsveröffentlichung article Text doc-type:article 2024 ftnonlinearchiv https://doi.org/10.5194/essd-16-177-2024 2024-01-15T00:22:44Z The Moderate Resolution Imaging Spectroradiometer (MODIS) is widely utilized for retrieving land surface reflectance to reflect plant conditions, detect ecosystem phenology, monitor forest fires, and constrain terrestrial energy budgets. However, the state-of-the-art MODIS surface reflectance products suffer from temporal and spatial gaps due to atmospheric conditions (e.g. clouds and aerosols), limiting their use in ecological, agricultural, and environmental studies. Therefore, there is a need for reconstructing spatiotemporally seamless (i.e. gap-filled) surface reflectance data from MODIS products, which is difficult due to the intrinsic inconsistency of observations resulting from various sun/view geometry and the prolonged missing values resulting from polar night or heavy cloud coverage, especially in monsoon season. We built a framework for generating the global 500 m daily seamless data cubes (SDC500) based on MODIS surface reflectance dataset, which contains the generation of a land-cover-based a priori database, bidirectional reflectance distribution function (BRDF) correction, outlier detection, gap filling, and smoothing. The first global spatiotemporally seamless land surface reflectance at 500 m resolution was produced, covering the period from 2000 to 2022. Preliminary evaluation of the dataset at 12 sites worldwide with different land cover demonstrated its robust performance. The quantitative assessment shows that the SDC500 gap-filling results have a root-mean-square error (RMSE) of 0.0496 and a mean absolute error (MAE) of 0.0430. The SDC500 BRDF correction results showed an RMSE of 0.056 and a bias of −0.0085 when compared with MODIS nadir BRDF-adjusted reflectance (NBAR) products, indicating the acceptable accuracy of both products. From a temporal perspective, the SDC500 eliminates abnormal fluctuations while retaining the useful localized feature of rapid disturbances. From a spatial perspective, the SDC500 shows satisfactory spatial continuity. In conclusion, the SDC500 is a ... Article in Journal/Newspaper polar night Niedersächsisches Online-Archiv NOA Earth System Science Data 16 1 177 200
institution Open Polar
collection Niedersächsisches Online-Archiv NOA
op_collection_id ftnonlinearchiv
language English
topic article
Verlagsveröffentlichung
spellingShingle article
Verlagsveröffentlichung
Liang, Xiangan
Liu, Qiang
Wang, Jie
Chen, Shuang
Gong, Peng
Global 500 m seamless dataset (2000–2022) of land surface reflectance generated from MODIS products
topic_facet article
Verlagsveröffentlichung
description The Moderate Resolution Imaging Spectroradiometer (MODIS) is widely utilized for retrieving land surface reflectance to reflect plant conditions, detect ecosystem phenology, monitor forest fires, and constrain terrestrial energy budgets. However, the state-of-the-art MODIS surface reflectance products suffer from temporal and spatial gaps due to atmospheric conditions (e.g. clouds and aerosols), limiting their use in ecological, agricultural, and environmental studies. Therefore, there is a need for reconstructing spatiotemporally seamless (i.e. gap-filled) surface reflectance data from MODIS products, which is difficult due to the intrinsic inconsistency of observations resulting from various sun/view geometry and the prolonged missing values resulting from polar night or heavy cloud coverage, especially in monsoon season. We built a framework for generating the global 500 m daily seamless data cubes (SDC500) based on MODIS surface reflectance dataset, which contains the generation of a land-cover-based a priori database, bidirectional reflectance distribution function (BRDF) correction, outlier detection, gap filling, and smoothing. The first global spatiotemporally seamless land surface reflectance at 500 m resolution was produced, covering the period from 2000 to 2022. Preliminary evaluation of the dataset at 12 sites worldwide with different land cover demonstrated its robust performance. The quantitative assessment shows that the SDC500 gap-filling results have a root-mean-square error (RMSE) of 0.0496 and a mean absolute error (MAE) of 0.0430. The SDC500 BRDF correction results showed an RMSE of 0.056 and a bias of −0.0085 when compared with MODIS nadir BRDF-adjusted reflectance (NBAR) products, indicating the acceptable accuracy of both products. From a temporal perspective, the SDC500 eliminates abnormal fluctuations while retaining the useful localized feature of rapid disturbances. From a spatial perspective, the SDC500 shows satisfactory spatial continuity. In conclusion, the SDC500 is a ...
format Article in Journal/Newspaper
author Liang, Xiangan
Liu, Qiang
Wang, Jie
Chen, Shuang
Gong, Peng
author_facet Liang, Xiangan
Liu, Qiang
Wang, Jie
Chen, Shuang
Gong, Peng
author_sort Liang, Xiangan
title Global 500 m seamless dataset (2000–2022) of land surface reflectance generated from MODIS products
title_short Global 500 m seamless dataset (2000–2022) of land surface reflectance generated from MODIS products
title_full Global 500 m seamless dataset (2000–2022) of land surface reflectance generated from MODIS products
title_fullStr Global 500 m seamless dataset (2000–2022) of land surface reflectance generated from MODIS products
title_full_unstemmed Global 500 m seamless dataset (2000–2022) of land surface reflectance generated from MODIS products
title_sort global 500 m seamless dataset (2000–2022) of land surface reflectance generated from modis products
publisher Copernicus Publications
publishDate 2024
url https://doi.org/10.5194/essd-16-177-2024
https://noa.gwlb.de/receive/cop_mods_00070942
https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00069266/essd-16-177-2024.pdf
https://essd.copernicus.org/articles/16/177/2024/essd-16-177-2024.pdf
genre polar night
genre_facet polar night
op_relation Earth System Science Data -- http://www.earth-syst-sci-data.net/volumes_and_issues.html -- http://www.bibliothek.uni-regensburg.de/ezeit/?2475469 -- 1866-3516
https://doi.org/10.5194/essd-16-177-2024
https://noa.gwlb.de/receive/cop_mods_00070942
https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00069266/essd-16-177-2024.pdf
https://essd.copernicus.org/articles/16/177/2024/essd-16-177-2024.pdf
op_rights https://creativecommons.org/licenses/by/4.0/
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container_title Earth System Science Data
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