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首页> 外文期刊>Earth System Science Data Discussions >Webcam network and image database for studies of phenological changes of vegetation and snow cover in Finland, image time series from 2014 to 2016
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Webcam network and image database for studies of phenological changes of vegetation and snow cover in Finland, image time series from 2014 to 2016

机译:网络摄像头网络和图像数据库,用于研究芬兰植被和积雪的物候变化,图像时间序列,2014年至2016年

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In recent years, monitoring of the status of ecosystems using low-cost web (IP) or time lapse cameras has received wide interest. With broad spatial coverage and high temporal resolution, networked cameras can provide information about snow cover and vegetation status, serve as ground truths to Earth observations and be useful for gap-filling of cloudy areas in Earth observation time series. Networked cameras can also play an important role in supplementing laborious phenological field surveys and citizen science projects, which also suffer from observer-dependent observation bias. We established a network of digital surveillance cameras for automated monitoring of phenological activity of vegetation and snow cover in the boreal ecosystems of Finland. Cameras were mounted at 14?sites, each site having 1–3?cameras. Here, we document the network, basic camera information and access to images in the permanent data repository (http://www.zenodo.org/communities/phenology_camera/). Individual DOI-referenced image time series consist of half-hourly images collected between 2014 and 2016 (https://doi.org/10.5281/zenodo.1066862). Additionally, we present an example of a colour index time series derived from images from two contrasting sites.
机译:近年来,使用低成本网络(IP)或延时摄影机监视生态系统的状态已引起广泛关注。联网摄像机具有广阔的空间覆盖范围和较高的时间分辨率,可提供有关积雪和植被状况的信息,可作为对地球观测的地面实况,并有助于填补地球观测时间序列中多云地区的缺口。网络摄像机在补充费力的物候田野调查和公民科学项目方面也可以发挥重要作用,这些工​​作也受到依赖于观察者的观察偏差的困扰。我们建立了一个数字监控摄像头网络,用于自动监控芬兰北方生态系统中植被和积雪的物候活动。摄像机安装在14个站点上,每个站点都有1-3个摄像机。在这里,我们记录了网络,基本摄像机信息以及对永久数据存储库(http://www.zenodo.org/communities/phenology_camera/)中图像的访问。各个DOI参照的图像时间序列包括2014年至2016年之间收集的半小时图像(https://doi.org/10.5281/zenodo.1066862)。此外,我们提供了一个颜色索引时间序列的示例,该时间索引源于来自两个对比点的图像。

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