基于小波和交叉小波变换的 MODIS fPAR 产品不能反映热带干旱森林的现场条件

IF 3.8 Q2 ENVIRONMENTAL SCIENCES Remote Sensing Applications-Society and Environment Pub Date : 2024-07-14 DOI:10.1016/j.rsase.2024.101298
Arturo Sanchez-Azofeifa , Iain Sharp , Kayla Stan
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引用次数: 0

摘要

光合有效辐射分量(fPAR)在确定生态系统的碳通量方面发挥着关键作用。尽管 MODIS 的 fPAR 产品已在北半球证明了其有效性,但在占热带森林总面积 40% 的热带干旱森林 (TDF) 中,其有效性仍有待验证。本研究利用无线传感器网络(WSN)在圣罗莎国家公园环境监测超级站点生成原位绿色 fPAR 数据集,旨在验证 2013 年至 2017 年的 MODIS fPAR 产品。本研究对原位数据集采用了一种双通量 fPAR 估算方法,然后通过基于 Savitzky-Golay 导数的平滑、单变量小波变换和交叉小波分析来比较原位数据集和 MODIS fPAR 数据集之间的物候变量。我们的研究结果表明,MODIS fPAR 产品与地面数据之间存在显著的时间差异,MODIS 在检测TDF的返青或衰老开始时间方面始终滞后 18-55 天。然而,年度和季节间的模式具有统计学意义(p < 0.05),并在 MODIS 和原地数据集中得到了复制。值得注意的是,这些模式在极端水情(干旱和飓风)期间会出现偏差,MODIS 低估了干旱的影响,未能体现飓风的影响。此外,MODIS 的 fPAR 产品不能有效捕捉小尺度 fPAR 变化和季节内差异。因此,本研究强调了 MODIS fPAR 观测在 TDFs 背景下的有限准确性。因此,在依赖 MODIS fPAR 产品监测热带干旱森林的快速物候变化时应谨慎行事。
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MODIS fPAR products do not reflect in-situ conditions in a tropical dry forest based on wavelet and cross-wavelet transforms

The fraction of Photosynthetically Active Radiation (fPAR) plays a pivotal role in determining the carbon flux in ecosystems. Although the MODIS fPAR product has demonstrated effectiveness in the Northern Hemisphere, its validity still needs to be verified in the context of Tropical Dry Forests (TDFs), which constitute 40% of all tropical forests. This study utilized a Wireless Sensor Network (WSN) to generate an in-situ Green fPAR dataset at the Santa Rosa National Park Environmental Monitoring Supersite, aiming to validate MODIS fPAR products from 2013 to 2017. This study employs a 2-flux fPAR estimation approach for the in-situ dataset, followed by Savitzky–Golay derivative-based smoothing, univariate-wavelet transforms, and cross-wavelet analysis to compare phenological variables between the in-situ and MODIS fPAR datasets. Our findings reveal a significant temporal disparity between the MODIS fPAR products and ground-based data, with MODIS consistently lagging in detecting the onset of green-up or senescence in TDFs by 18–55 days. However, the annual and inter-seasonal patterns were statistically significant (p < 0.05) and replicated in the MODIS and in-situ datasets. Notably, these patterns deviate during extreme water conditions (droughts and hurricanes), with MODIS underestimating the effects of drought and failing to represent hurricane impact. Furthermore, MODIS fPAR products do not effectively capture small-scale fPAR variations and intra-seasonal differences. Therefore, this study underscores the limited accuracy of MODIS fPAR observations in the context of TDFs. Consequently, caution is warranted when relying on MODIS fPAR products to monitor rapid phenological changes in Tropical Dry Forests.

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来源期刊
CiteScore
8.00
自引率
8.50%
发文量
204
审稿时长
65 days
期刊介绍: The journal ''Remote Sensing Applications: Society and Environment'' (RSASE) focuses on remote sensing studies that address specific topics with an emphasis on environmental and societal issues - regional / local studies with global significance. Subjects are encouraged to have an interdisciplinary approach and include, but are not limited by: " -Global and climate change studies addressing the impact of increasing concentrations of greenhouse gases, CO2 emission, carbon balance and carbon mitigation, energy system on social and environmental systems -Ecological and environmental issues including biodiversity, ecosystem dynamics, land degradation, atmospheric and water pollution, urban footprint, ecosystem management and natural hazards (e.g. earthquakes, typhoons, floods, landslides) -Natural resource studies including land-use in general, biomass estimation, forests, agricultural land, plantation, soils, coral reefs, wetland and water resources -Agriculture, food production systems and food security outcomes -Socio-economic issues including urban systems, urban growth, public health, epidemics, land-use transition and land use conflicts -Oceanography and coastal zone studies, including sea level rise projections, coastlines changes and the ocean-land interface -Regional challenges for remote sensing application techniques, monitoring and analysis, such as cloud screening and atmospheric correction for tropical regions -Interdisciplinary studies combining remote sensing, household survey data, field measurements and models to address environmental, societal and sustainability issues -Quantitative and qualitative analysis that documents the impact of using remote sensing studies in social, political, environmental or economic systems
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