Earlier this year the Met Office released the MIDAS Open database, a publically available version of a popular dataset containing hourly weather measurements across the UK. The Centre for Environmental Data Analysis (CEDA) has now published an updated version of MIDAS Open, bringing in new data for 2018 and updates for previous years. CEDA anticipate the new data will be particularly useful for service providers or members of the public who have previously been unable to access the restricted MIDAS dataset.
For decades, farm data across ACP countries has been collected by governments, financial service providers and even mobile network operators, to provide insights into agriculture that can be used to shape and influence the sector from the top down. But with more than 40% of African households now belonging to farmer cooperatives – many of which digitally record and store their members’ farm data – decision-makers increasingly acknowledge that a more localised and inclusive approach to data may be the best way to transform agriculture.
[学术文献] Predicting the Spatial Distribution and Severity of Soil Erosion in the Global Tropics using Satellite Remote Sensing 进入全文
Soil erosion has long been recognized as a major process of land degradation globally, affecting millions of hectares of land in the tropics and resulting in losses in productivity and biodiversity, decreased resilience of both marine and terrestrial ecosystems, and increased vulnerability to climate change. This paper presents an assessment of the extent of soil erosion in the global tropics at a moderate spatial resolution (500 m) based on a combination of systematic field surveys using the Land Degradation Surveillance Framework (LDSF) methodology and Earth observation data from the Moderate Resolution Imaging Spectroradiometer (MODIS) platform. The highest erosion prevalence was observed in wooded grassland, bushland, and shrubland systems in semi-arid areas, while the lowest occurrence was observed in forests. Observed erosion decreased with increasing fractional vegetation cover, but with high rates of erosion even at 50–60% fractional cover. These findings indicate that methods to assess soil erosion need to be able to detect erosion under relatively dense vegetation cover. Model performance was good for prediction of erosion based on MODIS, with high accuracy (~89% for detection) and high overall precision (AUC = 0.97). The spatial predictions from this study will allow for better targeting of interventions to restore degraded land and are also important for assessing the dynamics of land health indicators such as soil organic carbon. Given the importance of soil erosion for land degradation and that the methodology gives robust results that can be rapidly replicated at scale, we would argue that soil erosion should be included as a key indicator in international conventions such as the United Nations Convention to Combat Desertification.
Tropical forests are under increasing pressure from human activity such as agriculture. However, in order to put effective conservation measures in place, local decision-makers must be able to precisely identify which areas of forest are most vulnerable. A new analysis method spearheaded by researchers from the French Agricultural Research Centre for International Development (CIRAD), the International Center for Tropical Agriculture (CIAT) and the University of Rennes-2 could hold the key.
Establishing a new business model based on science, data, transparency and accountability and conducive to strong partnerships with the private sector is a major focus for FAO, the Organization's Director-General Qu Dongyu today told private sector representatives at a meeting on the margins of the 74th session of the UN General Assembly. "The world needs a strong, efficient and dynamic FAO. And FAO needs strong reliable partnerships with you," said the FAO chief. The meeting provided a platform to discuss and strengthen partnerships for realizing the much-needed transformation in food systems, and mobilizing all available technologies, innovations, knowledge and expertise to achieve positive impact at scale in the agriculture sectors.