Global 24 solar terms phenological MODIS normalized difference vegetation index dataset in 2001–2022

IF 3.3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Geoscience Data Journal Pub Date : 2024-08-08 DOI:10.1002/gdj3.268

Jing Yang, Taixia Wu, Xiying Sun, Kai Liu, Muhammad Farhan, Xuan Zhao, Quanshan Gao, Yingying Yang, Yuhan Shao, Shudong Wang

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引用次数: 0

Abstract

Phenology reflects the life cycle of vegetation, crucial for monitoring global vegetation diversity, ecosystem stability, and agricultural security. However, there is currently no dataset related to phenology. The 24 solar terms (24STs), based on the Sun's annual motion, reflect the changing seasons, temperature fluctuations, and phenological phenomena. They serve as a vital means to characterize vegetation phenology. This study generate a global Normalized Difference Vegetation Index (NDVI) product based on 24STs using Moderate Resolution Imaging Spectroradiometer (MODIS) on the Google Earth Engine (GEE). The 24STs NDVI dataset adopted the maximum value compositing (MVC) to process the NDVI values between two adjacent 24STs. The product has a spatial resolution of 250 m, covering the period from 2001 to 2022. Comparing with the MOD13Q1, good spatiotemporal consistency between the two datasets was observed, confirming the reliability of the 24STs product. However, the 24STs product holds distinct phenological meanings. This product introduces, for the first time, a vegetation index dataset based on the 24STs, enriching the vegetation index dataset and facilitating further research on phenology.

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2001-2022 年全球 24 节气物候 MODIS 归一化差异植被指数数据集

物候反映了植被的生命周期，对监测全球植被多样性、生态系统稳定性和农业安全至关重要。然而，目前还没有与物候相关的数据集。基于太阳周年运动的 24 节气（24ST）反映了季节变化、温度波动和物候现象。它们是描述植被物候特征的重要手段。本研究利用谷歌地球引擎（GEE）上的中分辨率成像分光仪（MODIS）生成基于 24STs 的全球归一化植被指数（NDVI）产品。24STs NDVI 数据集采用最大值合成法（MVC）处理相邻两个 24STs 之间的 NDVI 值。该数据集的空间分辨率为 250 米，时间跨度为 2001 年至 2022 年。与 MOD13Q1 相比，两个数据集的时空一致性良好，这证实了 24STs 产品的可靠性。不过，24STS 产品具有独特的物候学含义。该产品首次引入了基于 24STs 的植被指数数据集，丰富了植被指数数据集，有助于进一步开展物候学研究。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Geoscience Data Journal GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES

CiteScore

5.90

自引率

9.40%

发文量

审稿时长

4 weeks

期刊介绍： Geoscience Data Journal provides an Open Access platform where scientific data can be formally published, in a way that includes scientific peer-review. Thus the dataset creator attains full credit for their efforts, while also improving the scientific record, providing version control for the community and allowing major datasets to be fully described, cited and discovered. An online-only journal, GDJ publishes short data papers cross-linked to – and citing – datasets that have been deposited in approved data centres and awarded DOIs. The journal will also accept articles on data services, and articles which support and inform data publishing best practices. Data is at the heart of science and scientific endeavour. The curation of data and the science associated with it is as important as ever in our understanding of the changing earth system and thereby enabling us to make future predictions. Geoscience Data Journal is working with recognised Data Centres across the globe to develop the future strategy for data publication, the recognition of the value of data and the communication and exploitation of data to the wider science and stakeholder communities.

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