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Investigation of land surface phenology detections in shrublands using multiple scale satellite data
Remote Sensing of Environment ( IF 13.5 ) Pub Date : 2021-01-01 , DOI: 10.1016/j.rse.2020.112133
Dailiang Peng , Yan Wang , George Xian , Alfredo R. Huete , Wenjiang Huang , Miaogen Shen , Fumin Wang , Le Yu , Liangyun Liu , Qiaoyun Xie , Lingling Liu , Xiaoyang Zhang

Abstract Shrublands occupy about 13% of the global land surface, contain about one-third of the biodiversity, store about half of the global terrestrial carbon, and provide many ecosystem services to a large amount of world's human population and livestock. Because phenology is a sensitive indicator of the response of shrubland ecosystems to climate change, the alteration of ecosystems following species invasions, and the dynamics of shrubland ecosystem function, biodiversity, and carbon budgets, it is critical to monitor and assess phenological dynamics in shrubland ecosystems. However, most current land surface phenology (LSP) products derived from satellite data do not provide phenology detections in some semiarid shrublands where the amplitude of seasonal vegetation greenness is small. Therefore, we investigated the LSP detection using multiple spatial resolution satellite data and examined the impacts of spatial scales and shrubland ecosystem components (shrub and herb cover) on LSP detections over the western United States. Specifically, greenup onset date (GUD) in shrublands was detected from 30 m Harmonized Landsat and Sentinel-2 (HLS) data and 500 m Visible Infrared Imaging Radiometer Suite (VIIRS) data to quantify scale effects. The GUD spatial patterns were explored with 30 m pixel variations in shrubland ecosystem components. The results show that GUD values varied with percent vegetation cover and shifted to earlier dates with increasing vegetation cover, demonstrating that satellite observations were not able to capture greenup onset until a threshold of green vegetation cover is reached. GUD was mostly undetectable from both HLS and VIIRS pixels with vegetation cover less than 10% and became fully detectable with vegetation covers larger than 50%. Similarly, the differences of GUD between HLS and VIIRS detections also decreased with increased vegetation cover. As a result of high shrubland heterogeneity, GUD from 30 m HLS pixels could be partially detected within a 500 m pixel despite GUD being undetectable from VIIRS time series. Moreover, vegetation cover heterogeneity also made it difficult for GUD at 30 m to be aggregated to coarse scales (such as to 500 m VIIRS pixels). These findings have significant implications to the detection and characterization of shrubland LSP responses to environmental and climate changes.

中文翻译:

基于多尺度卫星数据的灌木地表物候检测研究

摘要 灌木地约占全球陆地面积的13%,包含约三分之一的生物多样性,储存了全球约一半的陆地碳,并为世界上大量的人口和牲畜提供了许多生态系统服务。由于物候是灌木生态系统对气候变化、物种入侵后生态系统变化以及灌木生态系统功能、生物多样性和碳收支动态的敏感指标,因此监测和评估灌木生态系统的物候动态至关重要. 然而,目前大多数源自卫星数据的地表物候 (LSP) 产品在某些季节性植被绿度幅度较小的半干旱灌木林中无法提供物候检测。所以,我们使用多个空间分辨率卫星数据研究了 LSP 检测,并检查了空间尺度和灌木地生态系统成分(灌木和草本植物覆盖)对美国西部 LSP 检测的影响。具体而言,从 30 m 协调陆地卫星和哨兵 2 (HLS) 数据和 500 m 可见红外成像辐射计套件 (VIIRS) 数据中检测到灌木丛中的绿化开始日期 (GUD),以量化尺度效应。GUD 空间模式是在灌木地生态系统组件中以 30 m 像素变化进行探索的。结果表明,GUD 值随植被覆盖率的百分比而变化,并随着植被覆盖率的增加而移至更早的日期,这表明卫星观测在达到绿色植被覆盖率阈值之前无法捕获绿化开始。GUD 在植被覆盖率小于 10% 的 HLS 和 VIIRS 像素中几乎无法检测到,而在植被覆盖率大于 50% 的情况下完全可以检测到。同样,HLS 和 VIIRS 检测之间的 GUD 差异也随着植被覆盖度的增加而减小。由于灌木丛的高度异质性,尽管 VIIRS 时间序列无法检测到 GUD,但可以在 500 m 像素内部分检测到来自 30 m HLS 像素的 GUD。此外,植被覆盖的异质性也使得 30 m 处的 GUD 难以聚合到粗尺度(例如 500 m VIIRS 像素)。这些发现对检测和表征灌木地 LSP 对环境和气候变化的响应具有重要意义。
更新日期:2021-01-01
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