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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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A High-Quality Reprocessed MODIS Leaf Area Index Dataset (HiQ-LAI)

Authors: Yan, Kai; Wang, Jingrui; Weiss, Marie; Myneni, Ranga B.;

A High-Quality Reprocessed MODIS Leaf Area Index Dataset (HiQ-LAI)

Abstract

The High-Quality Leaf Area Index (HiQ-LAI) is derived from reprocessed MODIS LAI C6.1 product by SpatioTemporal Information Compositing Algorithm (STICA). This method integrates information from multiple dimensions, including pixel quality information, spatiotemporal correlation, and original observations, to improve the raw MODIS LAI retrievals with poor quality. The HiQ-LAI covers the period from 2000 to 2022, with spatial resolutions of 500m/5km for global vegetation area and temporal resolutions of 8 days. Ground-based verification results show that HiQ-LAI performs better than the original MODIS product (MOD15A2H C6.1). Time series curves of the HiQ-LAI exhibit reduced abnormal fluctuations and better alignment with expected phenological patterns. Additionally, the agreement with ground measurements increases gradually as raw data quality decreases. HiQ-LAI was found to be more continuous and consistent than MODIS LAI on a global scale from both spatial and temporal perspectives, especially in the equatorial regions where optical remote sensing usually cannot achieve good performance. Thus, We anticipate that HiQ-LAI with better spatio-temporal continuity will better support varying global LAI time series applications. Here, we offer a product version with a spatial resolution of 5km and a temporal resolution of 8 days. Another version has a spatial resolution of 500 meters and is available through Google Earth Engine (https://code.earthengine.google.com/?asset=projects/verselab-398313/assets/HiQ_LAI/wgs_500m_8d). More details about HiQ-LAI can be found at https://github.com/tiramisu18/HiQ-LAI

Keywords

SpatioTemporal Information Compositing Algorithm (STICA), Leaf Area Index (LAI), Spatio-temporal consistency, A High-Quality Reprocessed MODIS LAI Dataset (HiQ-LAI)

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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