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[科技图书] Methods of Geo-Spatial Sampling 进入全文

Data Collection in Fragile States

地理空间数据技术的进步有可能改变调研数据的收集方式。由于长期以来一直受高成本,能力有限和监管困难的困扰,通常使用次优或非概率方法来进行样本选择,特别是在收集困难的情况下。本章节介绍了在三种不同设置下基于GIS的采样的经验供参考。

[前沿资讯] Artificial intelligence and farmer knowledge boost smallholder maize yields 进入全文

EurekAlert

Farmers in Colombia's maize-growing region of Córdoba had seen it all: too much rain one year, a searing drought the next. Yields were down and their livelihoods hung in the balance. The situation called for a new approach. They needed information services that would help them decide what varieties to plant, when they should sow and how they should manage their crops. A consortium formed with the government, Colombia's National Cereals and Legumes Federation (FENALCE), and big-data scientists at the International Center for Tropical Agriculture (CIAT). The researchers used big-data tools, based on the data farmers helped collect, and yields increased substantially.

[前沿资讯] Codes of Conduct for Better Ag. Data Management 进入全文

全球农业与营养开放数据网(GODAN)

The adoption of digital technologies in agriculture has marked the start of a major transformation: Better services and products, innovations, enhanced decision making and increased profitability and productivity. But do all stakeholders in the agricultural sector have the same access and control to these insights? Do farmers really benefit equally, or even at all, from the benefits of data sharing? What concerns do farmers have on such issues as data ownership, privacy and security? In a bid to better understand the importance of the socio-ethical considerations surrounding smart farming, and the challenges involved in balancing the cost of new technologies against expected benefits to farmers, GODAN, in collaboration with the Technical Centre for Agricultural and Rural Cooperation (CTA) established a Sub-Group on Data Codes of Conduct in February 2019.

[学术文献] Architecture design approach for IoT-based farm management information systems 进入全文

Precision Agriculture

Smart farming adopts advanced technology and the corresponding principles to increase the amount of production and economic returns, often also with the goal to reduce the impact on the environment. One of the key elements of smart farming is the farm management information systems (FMISs) that supports the automation of data acquisition and processing, monitoring, planning, decision making, documenting, and managing the farm operations. An increased number of FMISs now adopt internet of things (IoT) technology to further optimize the targeted business goals. Obviously IoT systems in agriculture typically have different functional and quality requirements such as choice of communication protocols, the data processing capacity, the security level, safety level, and time performance. For developing an IoT-based FMIS, it is important to design the proper architecture that meets the corresponding requirements. To guide the architect in designing the IoT based farm management information system that meets the business objectives a systematic approach is provided. To this end a design-driven research approach is adopted in which feature-driven domain analysis is used to model the various smart farming requirements. Further, based on a FMIS and IoT reference architectures the steps and the modeling approaches for designing IoT-based FMIS architectures are described. The approach is illustrated using two case studies on smart farming in Turkey, one for smart wheat production in Konya, and the other for smart green houses in Antalya.

[学术文献] Study of Wireless Communication Technologies on Internet of Things for Precision Agriculture 进入全文

Wireless Personal Communications

Precision agriculture is a suitable solution to these challenges such as shortage of food, deterioration of soil properties and water scarcity. The developments of modern information technologies and wireless communication technologies are the foundations for the realization of precision agriculture. This paper attempts to find suitable, feasible and practical wireless communication technologies for precision agriculture by analyzing the agricultural application scenarios and experimental tests. Three kinds of Wireless Sensor Networks (WSN) architecture, which is based on narrowband internet of things (NB-IoT), Long Range (LoRa) and ZigBee wireless communication technologies respectively, are presented for precision agriculture applications. The feasibility of three WSN architectures is verified by corresponding tests. By measuring the normal communication time, the power consumption of three wireless communication technologies is compared. Field tests and comprehensive analysis show that ZigBee is a better choice for monitoring facility agriculture, while LoRa and NB-IoT were identified as two suitable wireless communication technologies for field agriculture scenarios.

[前沿资讯] Using machine learning to understand climate change 进入全文

EurekAlert

Methane is a potent greenhouse gas that is being added to the atmosphere through both natural processes and human activities, such as energy production and agriculture. To predict the impacts of human emissions, researchers need a complete picture of the atmosphere's methane cycle. They need to know the size of the inputs--both natural and human--as well as the outputs. They also need to know how long methane resides in the atmosphere. To help develop this understanding, Tom Weber, an assistant professor of earth and environmental sciences at the University of Rochester; undergraduate researcher Nicola Wiseman '18, now a graduate student at the University of California, Irvine; and their colleague Annette Kock at the GEOMAR Helmholtz Centre for Ocean Research in Germany, used data science to determine how much methane is emitted from the ocean into the atmosphere each year. Their results, published in the journal Nature Communications, fill a longstanding gap in methane cycle research and will help climate scientists better assess the extent of human perturbations. The study is part of Weber's effort to use data science to better understand how various greenhouse gases, including nitrogen and carbon dioxide, affect global climate systems.

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