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[科技报告 ] Global assessment of soil carbon in grasslands 进入全文
FAO
Soils contribute to the achievement of the UN Sustainable Development Goals through carbon sequestration. By enhancing soil health and fertility, soils can play a crucial role in climate action, land degradation neutrality, and alleviating hunger. The present study provides a spatially explicit report on the state of grassland soils and can be used as a baseline for future work to explore the impacts of livestock management on soil carbon at regional, country and farm levels. Assessing the current state of grassland systems and their potential to sequester carbon in the soil is of key importance to understand the trade-offs between grassland services on food security, biodiversity conservation and climate mitigation.
[前沿资讯 ] Geospatial Data for Vegetation Monitoring 进入全文
地理空间世界
To leverage Geospatial data and technologies for monitoring and managing the planet’s green cover, in line with the Sustainable Development Goals for life on land (SDG 15) and climate action (SDG 13). An application was developed for vegetation monitoring derives data from the Indian Remote Sensing Satellites and archives them. The data includes vegetation indices, soil moisture, temperature throughout the field, rainfall and other such parameters which are continuously archived by the application. Data from a freely available foreign satellite are also used. The application facilitates interactive visualization and analytics on the web. The repository of multi-temporal (over 22 years) and multi-resolution (500 to 10 m) NDVI time series data is available on VEDAS (https://vedas.sac.gov.in/vege- tation-monitoring/index.html). The website provides capabilities to perform several image processing operations such as image differencing, temporal classification, Geospatial query, principal component analysis, temporal NDVI compositing and long-term statistics. The application also supports the presentation of data such as heat maps, temporal profiles, and Year-on-Year (YoY) comparisons. Zonal statistics at the district, taluka and village levels are also supported.
[前沿资讯 ] Tavant and Bayer enter into an innovative agritech partnership to transform sustainable farming practices 进入全文
SeedQuest
Tavant, Silicon Valley's leading digital products and solutions company, today announced a strategic partnership with Bayer, a global leader in agriculture solutions, to introduce innovative AgriTech solutions that will empower organizations to drive innovation and growers to optimize crop yields, reduce expenses, and minimize their environmental footprint. The partnership comes at a crucial time when growers face mounting pressure to increase productivity while confronting many challenges beyond their control, such as unpredictable weather events and unstable commodity markets. By leveraging the latest technologies, such as Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT) analytics, Bayer’s ready-to-use data models, and Tavant’s technical and specialized expertise in the Agri industry, this partnership aims to empower the organizations to drive innovation and manage the farming challenges. With a focus on enhancing transparency and promoting sustainability throughout the food supply chain, this collaboration is set to transform the agricultural industry.
[学术文献 ] 自然灾害综合风险防范信息服务技术体系构建及展望 进入全文
地球信息科学学报
构建自然灾害综合风险防范信息服务业务技术体系是支撑新时代防灾减灾救灾工作的必然要求.文章聚焦全链条、多主体、多灾种综合风险防范信息服务需求,建立了自然灾害综合风险防范信息服务的技术体系框架,构建了涵盖常态减灾和灾前预防、灾中救援、灾后恢复重建等非常态救灾全过程的综合风险防范信息服务产品体系,建立了信息产品开发、行业数据协同、网络大数据挖掘、信息服务平台集成等方面的关键技术.其中,信息产品体系构建从灾害管理过程、主要业务类型和工作任务方面进行三级分类.信息产品开发方面研发了基于致灾、灾情、救灾3类标准灾害信息要素的灾害信息产品制作、表达和动态定制技术;行业数据协同方面研发了双向自适应的部门微服务数据共享新机制及多部门多源异构数据接入、融合处理技术;网络大数据挖掘领域研发了基于网页、移动通信、社交网络、物联网等网络大数据的致灾、灾情、救灾要素信息挖掘与融合分析技术;信息服务集成平台搭建领域研发了基于云服务架构的时空分布式大数据管理、业务工具模型集成、"云+端"多渠道信息服务技术.该技术体系解决灾害信息服务时效性不高、完备性不足等问题,为开辟与政府部门统计并行的灾害信息数据获取新途径提供了技术支撑。
[前沿资讯 ] Using a standard RGB camera and AI to obtain vegetation data 进入全文
EurekAlert
Aerial imagery is a valuable component of precision agriculture, providing farmers with important information about crop health and yield. Images are typically obtained with an expensive multispectral camera attached to a drone. But a new study from the University of Illinois and Mississippi State University (MSU) shows that pictures from a standard red-green-blue (RGB) camera combined with AI deep learning can provide equivalent crop prediction tools for a fraction of the cost. Multispectral cameras provide color maps that represent vegetation to help farmers monitor plant health and spot problem areas. Vegetation indices such as the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Red Edge Index (NDRE) display healthy areas as green, while problem areas show up as red.
[前沿资讯 ] Satellite data shows sustained severe drought in Europe 进入全文
ScienceDaily
Europe has been experiencing a severe drought for years. Across the continent, groundwater levels have been consistently low since 2018, even if extreme weather events with flooding temporarily give a different picture. The beginning of this tense situation is documented in a publication by Eva Boergens in Geophysical Research Letters from the year 2020. In it, she noted that there was a striking water shortage in Central Europe during the summer months of 2018 and 2019. Since then, there has been no significant rise in groundwater levels; the levels have remained constantly low. This is shown by data analyses by Torsten Mayer-Gürr and Andreas Kvas from the Institute of Geodesy at Graz University of Technology (TU Graz). As part of the EU's Global Gravity-based Groundwater Product (G3P) project, they used satellite gravimetry to observe the world's groundwater resources and documented their changes in recent years.
