对全球地表物候长期连续性的洞察:MODIS和VIIRS产品的比较分析

IF 11.4 1区 地球科学 Q1 ENVIRONMENTAL SCIENCES
Khuong H. Tran , Xiaoyang Zhang , Yongchang Ye , Geoffrey M. Henebry , Mark A. Friedl , Yu Shen , Yuxia Liu , Shuai An , Shuai Gao
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引用次数: 0

摘要

可见光红外成像辐射计套件(VIIRS)全球地表物候(GLSP)产品(VNP22Q2 C2)自2013年开始投入生产,旨在提供全球尺度上植被地表物候的年度测量,以接替2001年首次生产的中分辨率成像光谱仪(MODIS)土地覆盖动力学(LCD)产品(MCD12Q2 C61)。虽然已经在当地进行了单独的验证,以确保每种产品检测到的表型的可靠性和准确性,但全面了解这两种操作产品之间的差异对于下游应用非常重要。因此,本研究对地表物候(LSP)产品进行了批判性分析和交叉比较,以确保全球物候动态的长期连续性。具体而言,我们比较了5种500 m空间分辨率的LSP产品:两种NASA运行产品MCD12Q2 C61和VNP22Q2 C2,以及另外三种应用VNP22Q2 C2算法生成的LSP产品,这些产品仅来自NOAA-20 VIIRS, SNPP和NOAA-20 VIIRS,以及Aqua和Terra上的MODIS。首先,我们使用高质量的参考LSP数据集对500米的5个产品进行了交叉验证,该数据集是通过融合Harmonized Landsat和Sentinel-2 (HLS)观测数据和近地表PhenoCam时间序列,在北美、欧洲和日本的不同生态系统中生成的。其次,在12块金色瓷砖的500米处对5种LSP产品进行了交叉比较。第三,在全球范围内评估MCD12Q2 C61和VNP22Q2 C2产品之间的长期可比性和连续性。这些综合评估表明,VNP22Q2 C2产品为MCD12Q2 C61记录提供了整体的全球连续性。与HLS-PhenoCam LSP产品的独立参考数据相比,来自VNP22Q2 C2算法的四个LSP产品产生了高度可比性的结果,平均绝对差(MAD)为~ 11天,平均系统偏差(MSB)为~ 7天。交叉比较表明,在12个选定的黄金瓷砖中,5个500米LSP产品与MADs <; 7天;然而,它们与MCD12Q2 C61的一致性在MADs ~ 9-10天时略低。MCD12Q2 C61和VNP22Q2 C2产品在全球尺度上具有连续性,除了在干旱/半干旱、热带和高纬度生态系统中,两者之间存在15天的绝对差异。最后提出:(1)对MODIS数据采用相同的物候检测算法可以增强MODIS与VIIRS LSP产品的连续性;(2)整合多个VIIRS传感器数据可以提高VIIRS GLSP产品的质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An insight into long-term continuity in global land surface phenology: A comparative analysis of MODIS and VIIRS products
The Visible Infrared Imaging Radiometer Suite (VIIRS) Global Land Surface Phenology (GLSP) product (VNP22Q2 C2) has been operationally produced since 2013, and is designed to provide annual measurements of the phenologies of vegetated land surfaces at the global scale, succeeding the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Dynamics (LCD) product (MCD12Q2 C61), which was first produced in 2001. Although separate validations have been conducted locally to ensure the reliability and accuracy of the detected phenometrics for each product, a comprehensive understanding of the differences between these two operational products is important for downstream applications. Therefore, this study conducted critical analyses and cross-comparisons of the land surface phenology (LSP) products to ensure long-term continuity in the global phenological dynamics. Specifically, we compared five LSP products at 500 m spatial resolution: two NASA operational products of MCD12Q2 C61 and VNP22Q2 C2, as well as three other LSP products that were generated by applying the VNP22Q2 C2 algorithm to different time series from NOAA-20 VIIRS only, both SNPP and NOAA-20 VIIRS, and MODIS on Aqua and Terra. First, we cross-validated the five products at 500 m using a high-quality reference LSP dataset at 30 m that was generated by fusing the Harmonized Landsat and Sentinel-2 (HLS) observations with near-surface PhenoCam time series across diverse ecosystems in North America, Europe, and Japan. Second, cross-comparisons were conducted between the five LSP products at 500 m across 12 golden tiles. Third, the long-term comparability and continuity between the MCD12Q2 C61 and the VNP22Q2 C2 products were assessed globally. These comprehensive evaluations demonstrated that the VNP22Q2 C2 product provides overall global continuity for the MCD12Q2 C61 record. Compared to independent reference data from the HLS-PhenoCam LSP product, the four LSP products derived from the VNP22Q2 C2 algorithm produced highly comparable results with a mean absolute difference (MAD) of ∼ 11 days and mean systematic bias (MSB) of ∼ 7 days. The cross-comparisons indicated a strong agreement among the five 500 m LSP products in the 12 selected golden tiles with MADs < 7 days; however, their agreement with the MCD12Q2 C61 was slightly lower with MADs ∼ 9–10 days. The global-scale evidence of continuity between the MCD12Q2 C61 and VNP22Q2 C2 products was an absolute difference of < 15 days, except in arid/semiarid, tropical, and high-latitude ecosystems. Finally, it is suggested that (1) the continuity from MODIS to VIIRS LSP products would be enhanced if the same phenological detection algorithm was applied to the MODIS data, and (2) the quality of the VIIRS GLSP product could be improved by integrating data from multiple VIIRS sensors.
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来源期刊
Remote Sensing of Environment
Remote Sensing of Environment 环境科学-成像科学与照相技术
CiteScore
25.10
自引率
8.90%
发文量
455
审稿时长
53 days
期刊介绍: Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing. The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques. RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.
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