Articles | Volume 16, issue 3
https://doi.org/10.5194/essd-16-1601-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-1601-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
26 Mar 2024
Data description paper |
| 26 Mar 2024
| 26 Mar 2024
HiQ-LAI: a high-quality reprocessed MODIS leaf area index dataset with better spatiotemporal consistency from 2000 to 2022
Innovation Research Center of Satellite Application (IRCSA), Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Jingrui Wang
CORRESPONDING AUTHOR
School of Land Science and Techniques, China University of Geosciences, Beijing 100083, China
Rui Peng
School of Land Science and Techniques, China University of Geosciences, Beijing 100083, China
Kai Yang
School of Land Science and Techniques, China University of Geosciences, Beijing 100083, China
Xiuzhi Chen
Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou 519082, China
Gaofei Yin
Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 610031, China
Jinwei Dong
Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
Marie Weiss
Institute National de la Recherche Agronomique, Université d'Avignon et des Pays du Vaucluse (INRA-UAPV), 228 Route de l'Aérodrome, 84914 Avignon, France
Jiabin Pu
Department of Earth and Environment, Boston University, Boston, MA 02215, USA
Ranga B. Myneni
Department of Earth and Environment, Boston University, Boston, MA 02215, USA
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Cited
10 citations as recorded by crossref.
- Multi-decadal temporal reconstruction of Sentinel-3 OLCI-based vegetation products with multi-output Gaussian process regression D. D.Kovács et al. 10.1016/j.ecoinf.2024.102816
- Interactions and Conflicts between Urbanization and Greenness: A Case Study from Nanjing, China S. Yang et al. 10.3390/rs16132505
- HiQ-FPAR: A High-Quality and Value-added MODIS Global FPAR Product from 2000 to 2023 K. Yan et al. 10.1038/s41597-025-04391-4
- A dataset of continuous MuSyQ leaf chlorophyll content product with a 30 m spatial and 10-day temporal resolution in China(2021–2022) L. GUAN et al. 10.11922/11-6035.nesdc.2024.0186.zh
- Mapping global leaf inclination angle (LIA) based on field measurement data S. Li & H. Fang 10.5194/essd-17-1347-2025
- Degradation and deforestation increase the sensitivity of the Amazon Forest to climate extremes M. Longo et al. 10.1088/1748-9326/adc58c
- Spatially resolved analysis of speciated VOC emissions and their contributions to secondary pollutant formation: a comparative assessment of anthropogenic and biogenic sources in China Y. Wang et al. 10.1016/j.envint.2025.109627
- A Comprehensive Evaluation of Global Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) Products of MODIS, GLASS, and GEO Over China L. Xia et al. 10.1109/JSTARS.2025.3575839
- An Insight Into the Internal Consistency of MODIS Global Leaf Area Index Products X. Zhang et al. 10.1109/TGRS.2024.3434366
- Natural and anthropogenic influences on short-term forest growth status: Evidence and mechanisms from China Z. Tian et al. 10.1016/j.jenvman.2025.126084
10 citations as recorded by crossref.
- Multi-decadal temporal reconstruction of Sentinel-3 OLCI-based vegetation products with multi-output Gaussian process regression D. D.Kovács et al. 10.1016/j.ecoinf.2024.102816
- Interactions and Conflicts between Urbanization and Greenness: A Case Study from Nanjing, China S. Yang et al. 10.3390/rs16132505
- HiQ-FPAR: A High-Quality and Value-added MODIS Global FPAR Product from 2000 to 2023 K. Yan et al. 10.1038/s41597-025-04391-4
- A dataset of continuous MuSyQ leaf chlorophyll content product with a 30 m spatial and 10-day temporal resolution in China(2021–2022) L. GUAN et al. 10.11922/11-6035.nesdc.2024.0186.zh
- Mapping global leaf inclination angle (LIA) based on field measurement data S. Li & H. Fang 10.5194/essd-17-1347-2025
- Degradation and deforestation increase the sensitivity of the Amazon Forest to climate extremes M. Longo et al. 10.1088/1748-9326/adc58c
- Spatially resolved analysis of speciated VOC emissions and their contributions to secondary pollutant formation: a comparative assessment of anthropogenic and biogenic sources in China Y. Wang et al. 10.1016/j.envint.2025.109627
- A Comprehensive Evaluation of Global Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) Products of MODIS, GLASS, and GEO Over China L. Xia et al. 10.1109/JSTARS.2025.3575839
- An Insight Into the Internal Consistency of MODIS Global Leaf Area Index Products X. Zhang et al. 10.1109/TGRS.2024.3434366
- Natural and anthropogenic influences on short-term forest growth status: Evidence and mechanisms from China Z. Tian et al. 10.1016/j.jenvman.2025.126084
Latest update: 30 Jun 2025
Short summary
Variations in observational conditions have led to poor spatiotemporal consistency in leaf area index (LAI) time series. Using prior knowledge, we leveraged high-quality observations and spatiotemporal correlation to reprocess MODIS LAI, thereby generating HiQ-LAI, a product that exhibits fewer abnormal fluctuations in time series. Reprocessing was done on Google Earth Engine, providing users with convenient access to this value-added data and facilitating large-scale research and applications.
Variations in observational conditions have led to poor spatiotemporal consistency in leaf area...
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