Mostafa Javadian, Francisco Salgado-Castillo, Koen Hufkens, Andrew D. Richardson
{"title":"物候监测的连续性:评估更新后的PhenoCam的性能","authors":"Mostafa Javadian, Francisco Salgado-Castillo, Koen Hufkens, Andrew D. Richardson","doi":"10.1016/j.agrformet.2025.110774","DOIUrl":null,"url":null,"abstract":"Vegetation phenology plays a crucial role in land-atmosphere interactions and ecosystem productivity, necessitating high-quality, long-term datasets. The PhenoCam Network addresses this need by using digital cameras to capture canopy greenness (GCC, the green chromatic coordinate). Since 2008, the StarDot NetCam SC has been the network's backbone, but its discontinuation, particularly exacerbated by supply chain problems and delays during the COVID-19 pandemic, requires the identification of a successor to ensure continuity. This study evaluates the StarDot NetCam Live 2 camera's performance against the SC model. We visually compared imagery from different seasons, evaluated color accuracy using a ColorChecker, and assessed the similarity of seasonal and diurnal GCC patterns. Results show that the Live 2 provides slightly improved GCC accuracy relative to the ColorChecker. Both cameras effectively capture seasonal changes in canopy greenness for three different vegetation types. High R<sup>2</sup> values (0.87–0.95) between the cameras 3-day GCC, confirm strong agreement in seasonal GCC time series and phenological transition dates, with an average difference of 4.1 ± 1.6 days. Diurnal GCC patterns also showed consistent agreement, strongest on sunny days (R<sup>2</sup>=0.71). The results of this study support the integration of the Live 2 camera into the PhenoCam Network, thereby facilitating the continuation of long-term phenological monitoring efforts.","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"15 1","pages":""},"PeriodicalIF":5.7000,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Continuity in phenological monitoring: Assessing the performance of an updated PhenoCam\",\"authors\":\"Mostafa Javadian, Francisco Salgado-Castillo, Koen Hufkens, Andrew D. Richardson\",\"doi\":\"10.1016/j.agrformet.2025.110774\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Vegetation phenology plays a crucial role in land-atmosphere interactions and ecosystem productivity, necessitating high-quality, long-term datasets. The PhenoCam Network addresses this need by using digital cameras to capture canopy greenness (GCC, the green chromatic coordinate). Since 2008, the StarDot NetCam SC has been the network's backbone, but its discontinuation, particularly exacerbated by supply chain problems and delays during the COVID-19 pandemic, requires the identification of a successor to ensure continuity. This study evaluates the StarDot NetCam Live 2 camera's performance against the SC model. We visually compared imagery from different seasons, evaluated color accuracy using a ColorChecker, and assessed the similarity of seasonal and diurnal GCC patterns. Results show that the Live 2 provides slightly improved GCC accuracy relative to the ColorChecker. Both cameras effectively capture seasonal changes in canopy greenness for three different vegetation types. High R<sup>2</sup> values (0.87–0.95) between the cameras 3-day GCC, confirm strong agreement in seasonal GCC time series and phenological transition dates, with an average difference of 4.1 ± 1.6 days. Diurnal GCC patterns also showed consistent agreement, strongest on sunny days (R<sup>2</sup>=0.71). The results of this study support the integration of the Live 2 camera into the PhenoCam Network, thereby facilitating the continuation of long-term phenological monitoring efforts.\",\"PeriodicalId\":50839,\"journal\":{\"name\":\"Agricultural and Forest Meteorology\",\"volume\":\"15 1\",\"pages\":\"\"},\"PeriodicalIF\":5.7000,\"publicationDate\":\"2025-08-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Agricultural and Forest Meteorology\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.1016/j.agrformet.2025.110774\",\"RegionNum\":1,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AGRONOMY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agricultural and Forest Meteorology","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1016/j.agrformet.2025.110774","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRONOMY","Score":null,"Total":0}
引用次数: 0
摘要
植被物候在陆地-大气相互作用和生态系统生产力中起着至关重要的作用,需要高质量的长期数据集。PhenoCam网络通过使用数码相机捕捉树冠绿度(GCC,绿色色度坐标)来满足这一需求。自2008年以来,StarDot NetCam SC一直是该网络的骨干,但由于供应链问题和2019冠状病毒病大流行期间的延误,其停产尤其加剧了这一问题,因此需要确定继任者以确保连续性。本研究评估了StarDot NetCam Live 2相机与SC模型的性能。我们从视觉上比较了不同季节的图像,使用ColorChecker评估了颜色准确性,并评估了季节和昼夜GCC模式的相似性。结果表明,Live 2提供了相对于ColorChecker稍微改进的GCC精度。这两款相机都能有效地捕捉到三种不同植被类型的冠层绿化率的季节性变化。相机3天GCC之间的高R2值(0.87-0.95)证实了季节GCC时间序列与物候过渡日期的强一致性,平均差异为4.1±1.6 d。日GCC模式也表现出一致的一致性,在晴天最强(R2=0.71)。本研究的结果支持将Live 2摄像机集成到PhenoCam网络中,从而促进长期物候监测工作的继续。
Continuity in phenological monitoring: Assessing the performance of an updated PhenoCam
Vegetation phenology plays a crucial role in land-atmosphere interactions and ecosystem productivity, necessitating high-quality, long-term datasets. The PhenoCam Network addresses this need by using digital cameras to capture canopy greenness (GCC, the green chromatic coordinate). Since 2008, the StarDot NetCam SC has been the network's backbone, but its discontinuation, particularly exacerbated by supply chain problems and delays during the COVID-19 pandemic, requires the identification of a successor to ensure continuity. This study evaluates the StarDot NetCam Live 2 camera's performance against the SC model. We visually compared imagery from different seasons, evaluated color accuracy using a ColorChecker, and assessed the similarity of seasonal and diurnal GCC patterns. Results show that the Live 2 provides slightly improved GCC accuracy relative to the ColorChecker. Both cameras effectively capture seasonal changes in canopy greenness for three different vegetation types. High R2 values (0.87–0.95) between the cameras 3-day GCC, confirm strong agreement in seasonal GCC time series and phenological transition dates, with an average difference of 4.1 ± 1.6 days. Diurnal GCC patterns also showed consistent agreement, strongest on sunny days (R2=0.71). The results of this study support the integration of the Live 2 camera into the PhenoCam Network, thereby facilitating the continuation of long-term phenological monitoring efforts.
期刊介绍:
Agricultural and Forest Meteorology is an international journal for the publication of original articles and reviews on the inter-relationship between meteorology, agriculture, forestry, and natural ecosystems. Emphasis is on basic and applied scientific research relevant to practical problems in the field of plant and soil sciences, ecology and biogeochemistry as affected by weather as well as climate variability and change. Theoretical models should be tested against experimental data. Articles must appeal to an international audience. Special issues devoted to single topics are also published.
Typical topics include canopy micrometeorology (e.g. canopy radiation transfer, turbulence near the ground, evapotranspiration, energy balance, fluxes of trace gases), micrometeorological instrumentation (e.g., sensors for trace gases, flux measurement instruments, radiation measurement techniques), aerobiology (e.g. the dispersion of pollen, spores, insects and pesticides), biometeorology (e.g. the effect of weather and climate on plant distribution, crop yield, water-use efficiency, and plant phenology), forest-fire/weather interactions, and feedbacks from vegetation to weather and the climate system.