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利用谷歌地球引擎实现更有效的草原管理:决策支持应用视角。

Leveraging Google Earth Engine for a More Effective Grassland Management: A Decision Support Application Perspective.

机构信息

Department of Agricultural, Food, and Environmental Sciences, University of Perugia, 06121 Perugia, Italy.

出版信息

Sensors (Basel). 2024 Jan 27;24(3):834. doi: 10.3390/s24030834.

DOI:10.3390/s24030834
PMID:38339552
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10856977/
Abstract

Grasslands cover a substantial portion of the earth's surface and agricultural land and is crucial for human well-being and livestock farming. Ranchers and grassland management authorities face challenges in effectively controlling herders' grazing behavior and grassland utilization due to underdeveloped infrastructure and poor communication in pastoral areas. Cloud-based grazing management and decision support systems (DSS) are needed to address this issue, promote sustainable grassland use, and preserve their ecosystem services. These systems should enable rapid and large-scale grassland growth and utilization monitoring, providing a basis for decision-making in managing grazing and grassland areas. In this context, this study contributes to the objectives of the EU LIFE IMAGINE project, aiming to develop a Web-GIS app for conserving and monitoring Umbria's grasslands and promoting more informed decisions for more sustainable livestock management. The app, called "Praterie" and developed in Google Earth Engine, utilizes historical Sentinel-2 satellite data and harmonic modeling of the EVI (Enhanced Vegetation Index) to estimate vegetation growth curves and maturity periods for the forthcoming vegetation cycle. The app is updated in quasi-real time and enables users to visualize estimates for the upcoming vegetation cycle, including the maximum greenness, the days remaining to the subsequent maturity period, the accuracy of the harmonic models, and the grassland greenness status in the previous 10 days. Even though future additional developments can improve the informative value of the Praterie app, this platform can contribute to optimizing livestock management and biodiversity conservation by providing timely and accurate data about grassland status and growth curves.

摘要

草原覆盖了地球表面和农业用地的很大一部分,对人类福祉和畜牧业至关重要。由于基础设施不发达和牧区通信不畅,牧场主和草原管理当局在有效控制牧民放牧行为和草原利用方面面临挑战。需要基于云的放牧管理和决策支持系统(DSS)来解决这个问题,促进可持续的草原利用,并保护其生态系统服务。这些系统应该能够快速、大规模地监测草原的生长和利用情况,为管理放牧和草原地区的决策提供依据。在这种情况下,本研究有助于实现欧盟 LIFE IMAGINE 项目的目标,该项目旨在开发一个用于保护和监测翁布里亚草原的 Web-GIS 应用程序,并为更可持续的畜牧业管理提供更明智的决策。该应用程序称为“Praterie”,在 Google Earth Engine 中开发,利用历史 Sentinel-2 卫星数据和 EVI(增强植被指数)的谐波建模来估计植被生长曲线和即将到来的植被周期的成熟度。该应用程序几乎实时更新,使用户能够可视化即将到来的植被周期的估计值,包括最大绿色度、到下一个成熟度周期的剩余天数、谐波模型的准确性以及前 10 天的草原绿色度状态。尽管未来的进一步发展可以提高 Praterie 应用程序的信息价值,但该平台可以通过提供有关草原状况和生长曲线的及时、准确的数据,为优化畜牧业管理和生物多样性保护做出贡献。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4102/10856977/4374aa03cbf3/sensors-24-00834-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4102/10856977/50b09d8808d0/sensors-24-00834-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4102/10856977/170e4a058dc1/sensors-24-00834-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4102/10856977/78a061a856c1/sensors-24-00834-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4102/10856977/ce364388157d/sensors-24-00834-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4102/10856977/4374aa03cbf3/sensors-24-00834-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4102/10856977/50b09d8808d0/sensors-24-00834-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4102/10856977/170e4a058dc1/sensors-24-00834-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4102/10856977/78a061a856c1/sensors-24-00834-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4102/10856977/ce364388157d/sensors-24-00834-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4102/10856977/4374aa03cbf3/sensors-24-00834-g005.jpg

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Framing the relationship between people and nature in the context of European conservation.在欧洲保护的背景下构建人与自然的关系。
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