Mapping leaf nitrogen and leaf area index in European landscapes using high spatial resolution satellite data and the REGularized canopy reFLECtance (REGFLEC) model

Leaf biochemistry and biophysical parameters are important for simulating soil‐vegetation‐atmosphere exchanges of energy, water, CO2 and ammonia. The accumulation of leaf nitrogen (N) in vegetation canopies is a major component of the ecosystem N balance, and leaf N concentration and leaf area index (LAI) are important determinants of the maximum CO2 uptake by plants and trees. In NEU, high spatial resolution remote sensing data from the SPOT satellite were acquired to prepare maps of leaf N and LAI for 5 European landscapes. Mapping was conducted using the REGFLEC model which is an automatic and image‐based methodology developed for regional chlorophyll (Cab) and LAI estimation (ie. Houborg and Andersen, JARS 3, 2009). REGFLEC combines models for atmospheric correction (6S), canopy reflectance (ACRM) and leaf optics (PROSPECT). Model performance previously proved promising in Denmark and in Maryland, USA. In this study, REGFLEC performance is evaluated and discussed using field measurements of leaf N, SPADmeter data and LAI in Denmark, Poland, Scotland, the Netherlands and Italy. The inverse model estimations of soil reflectance parameters and canopy parameters are discussed in relation to the prevailing soil types and vegetation characteristics of land cover classes across the 5 European landscapes

CubeSat constellations provide enhanced crop phenology and digital agricultural insights using daily leaf area index retrievals

Satellite remote sensing has great potential to deliver on the promise of a data-driven agricultural revolution, with emerging space-based platforms providing spatiotemporal insights into precisionlevel attributes such as crop water use, vegetation health and condition and crop response to management practices. Using a harmonized collection of high-resolution Planet CubeSat, Sentinel-2, Landsat-8 and additional coarser resolution imagery from MODIS and VIIRS, we exploit a multisatellite data fusion and machine learning approach to deliver a radiometrically calibrated and gap-filled time-series of daily leaf area index (LAI) at an unprecedented spatial resolution of 3 m. The insights available from such high-resolution CubeSat-based LAI data are demonstrated through tracking the growth cycle of a maize crop and identifying observable within-field spatial and temporal variations across key phenological stages. Daily LAI retrievals peaked at the tasseling stage, demonstrating their value for fertilizer and irrigation scheduling. An evaluation of satellite-based retrievals against field-measured LAI data collected from both rain-fed and irrigated fields shows high correlation and captures the spatiotemporal development of intra- and inter-field variations. Novel agricultural insights related to individual vegetative and reproductive growth stages were obtained, showcasing the capacity for new high-resolution CubeSat platforms to deliver actionable intelligence for precision agricultural and related applications

The future of Earth observation in hydrology

In just the past 5 years, the field of Earth observation has progressed beyond the offerings of conventional space-agency-based platforms to include a plethora of sensing opportunities afforded by CubeSats, unmanned aerial vehicles (UAVs), and smartphone technologies that are being embraced by both for-profit companies and individual researchers. Over the previous decades, space agency efforts have brought forth well-known and immensely useful satellites such as the Landsat series and the Gravity Research and Climate Experiment (GRACE) system, with costs typically of the order of 1 billion dollars per satellite and with concept-to-launch timelines of the order of 2 decades (for new missions). More recently, the proliferation of smart-phones has helped to miniaturize sensors and energy requirements, facilitating advances in the use of CubeSats that can be launched by the dozens, while providing ultra-high (3-5 m) resolution sensing of the Earth on a daily basis. Start-up companies that did not exist a decade ago now operate more satellites in orbit than any space agency, and at costs that are a mere fraction of traditional satellite missions. With these advances come new space-borne measurements, such as real-time high-definition video for tracking air pollution, storm-cell development, flood propagation, precipitation monitoring, or even for constructing digital surfaces using structure-from-motion techniques. Closer to the surface, measurements from small unmanned drones and tethered balloons have mapped snow depths, floods, and estimated evaporation at sub-metre resolutions, pushing back on spatio-temporal constraints and delivering new process insights. At ground level, precipitation has been measured using signal attenuation between antennae mounted on cell phone towers, while the proliferation of mobile devices has enabled citizen scientists to catalogue photos of environmental conditions, estimate daily average temperatures from battery state, and sense other hydrologically important variables such as channel depths using commercially available wireless devices. Global internet access is being pursued via high-altitude balloons, solar planes, and hundreds of planned satellite launches, providing a means to exploit the "internet of things" as an entirely new measurement domain. Such global access will enable real-time collection of data from billions of smartphones or from remote research platforms. This future will produce petabytes of data that can only be accessed via cloud storage and will require new analytical approaches to interpret. The extent to which today's hydrologic models can usefully ingest such massive data volumes is unclear. Nor is it clear whether this deluge of data will be usefully exploited, either because the measurements are superfluous, inconsistent, not accurate enough, or simply because we lack the capacity to process and analyse them. What is apparent is that the tools and techniques afforded by this array of novel and game-changing sensing platforms present our community with a unique opportunity to develop new insights that advance fundamental aspects of the hydrological sciences. To accomplish this will require more than just an application of the technology: in some cases, it will demand a radical rethink on how we utilize and exploit these new observing systems

Stakeholder ownership: a theoretical framework for cross national understanding and analyses of stakeholder involvement in issues of substance use, problem use and addiction

This project contributes to understanding of the role of different stakeholder groups in the formulation and implementation of policy in the addictions field in Austria, Denmark, Finland, Italy, Poland and the UK. It comprises a number of case studies which draw on a range of theoretical frameworks to examine stakeholder dynamics at international, national and local levels. Mainly qualitative methods were used: interviews, policy and documentation analyses, webcrawler network analysis, and simple surveys; one case study was based on a survey only. The case studies fall into four main categories: three focus on controversial issues in drug treatment policy and practice – opioid substitution treatment, drug consumption rooms, and heroin assisted treatment; three look at stakeholder activity in alcohol control and public health; one pilot case study considers the potential role of researchers in the development of a scientific network around gambling; and one looks at the role of nurses in implementing brief interventions. In addition, themes explored across case studies included the role of evidence and stakeholder activity, drug users as stakeholders, and the role of external stakeholders on national policy. Professional stakeholders at implementation level and families and drug users as stakeholders are also considered. The case studies revealed that, in many instances, the addictions field is characterised by tensions between groups, by entrenched relationships between some addiction-specific stakeholder groups and powerful political stakeholders, and by the dominance of some forms of evidence over other forms of knowledge. Science and scientists are only influential in policy terms if their scientific findings ‘fit’ with the wider political context. Nevertheless, at least within the European context, there are opportunities for new stakeholder groups to emerge and gain policy salience and there are opportunities for stakeholders to challenge prevailing frames of understanding the addictions and prevailing modes of responding to problems of substance misuse and addiction

Exploring hydro-meteorological drought patterns over the Greater Horn of Africa (1979-2014) using remote sensing and reanalysis products

Spatio-temporal patterns of hydrological droughts over the Greater Horn of Africa (GHA) are explored based on total water storage (TWS) changes derived from time-variable gravity field solutions of Gravity Recovery And Climate Experiment (GRACE, 2002-2014), together with those simulated by Modern Retrospective Analysis for Research Application (MERRA, 1980-2014). These hydrological extremes are then related to meteorological drought events estimated from observed monthly precipitation products of Global Precipitation Climatology Center (GPCC, 1979-2010) and Tropical Rainfall Measuring Mission (TRMM, 1998-2014). The major focus of this contribution lies on the application of spatial Independent Component Analysis (sICA) to extract distinguished regions with similar rainfall and TWS with similar overall trend and seasonality. Rainfall and TWS are used to estimate Standard Precipitation Indices (SPIs) and Total Storage Deficit Indices (TSDIs), respectively that are employed to characterize frequency and intensity of hydro-meteorological droughts over GHA. Significant positive (negative) changes in monthly rainfall over Ethiopia (Sudan) between 2002 and 2010 leading to a significant increase in TWS over the central GHA region were noted in both MERRA and GRACE TWS (2002-2014). However, these trends were completely reversed in the long-term (1980-2010) records of rainfall (GPCC) and TWS (MERRA). The four independent hydrological sub-regions extracted based on the sICA (i.e., Lake Victoria Basin, Ethiopia-Sudanese border, South Sudan, and Tanzania) indicated fairly distinct temporal patterns that matched reasonably well between precipitation and TWS changes. While meteorological droughts were found to be consistent with most previous studies in all sub-regions, their impacts are clearly observed in the TWS changes resulting in multiple years of extreme hydrological droughts. Correlations between SPI and TSDI were found to be significant over Lake Victoria Basin, South Sudan, and Tanzania. The low correlations between SPI and TSDI over Ethiopia are likely related to inconsistency between TWS and precipitation signals. Further, we found that hydrological droughts in these regions were significantly associated with Indian Ocean Dipole (IOD) events while El Niño Southern Oscillation (ENSO) plays a secondary role