Building a Data Set over 12 Globally Distributed Sites to Support the Development of Agriculture Monitoring Applications with Sentinel-2

Developing better agricultural monitoring capabilities based on Earth Observation data is critical for strengthening food production information and market transparency. The Sentinel-2 mission has the optimal capacity for regional to global agriculture monitoring in terms of resolution (10–20 meter), revisit frequency (five days) and coverage (global). In this context, the European Space Agency launched in 2014 the “Sentinel­2 for Agriculture” project, which aims to prepare the exploitation of Sentinel-2 data for agriculture monitoring through the development of open source processing chains for relevant products. The project generated an unprecedented data set, made of “Sentinel-2 like” time series and in situ data acquired in 2013 over 12 globally distributed sites. Earth Observation time series were mostly built on the SPOT4 (Take 5) data set, which was specifically designed to simulate Sentinel-2. They also included Landsat 8 and RapidEye imagery as complementary data sources. Images were pre-processed to Level 2A and the quality of the resulting time series was assessed. In situ data about cropland, crop type and biophysical variables were shared by site managers, most of them belonging to the “Joint Experiment for Crop Assessment and Monitoring” network. This data set allowed testing and comparing across sites the methodologies that will be at the core of the future “Sentinel­2 for Agriculture” system.Instituto de Clima y AguaFil: Bontemps, Sophie. Université Catholique de Louvain. Earth and Life Institute; BélgicaFil: Arias, Marcela. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Cara, Cosmin. CS Romania S.A.; RumaniaFil: Dedieu, Gérard. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Guzzonato, Eric. CS Systèmes d’Information; FranciaFil: Hagolle, Olivier. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Inglada, Jordi. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Matton, Nicolas. Université Catholique de Louvain. Earth and Life Institute; BélgicaFil: Morin, David. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Popescu, Ramona. CS Romania S.A.; RumaniaFil: Rabaute, Thierry. CS Systèmes d’Information; FranciaFil: Savinaud, Mickael. CS Systèmes d’Information; FranciaFil: Sepulcre, Guadalupe. Université Catholique de Louvain. Earth and Life Institute; BélgicaFil: Valero, Silvia. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Ahmad, Ijaz. Pakistan Space and Upper Atmosphere Research Commission. Space Applications Research Complex. National Agriculture Information Center Directorate; PakistánFil: Bégué, Agnès. Centre de Coopération Internationale en Recherche Agronomique pour le Développerment; FranciaFil: Wu, Bingfang. Chinese Academy of Sciences. Institute of Remote Sensing and Digital Earth; República de ChinaFil: De Abelleyra, Diego. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; ArgentinaFil: Diarra, Alhousseine. Université Cadi Ayyad. Faculté des Sciences Semlalia; MarruecosFil: Dupuy, Stéphane. Centre de Coopération Internationale en Recherche Agronomique pour le Développerment; FranciaFil: French, Andrew. United States Department of Agriculture. Agricultural Research Service. Arid Land Agricultural Research Center; ArgentinaFil: Akhtar, Ibrar ul Hassan. Pakistan Space and Upper Atmosphere Research Commission. Space Applications Research Complex. National Agriculture Information Center Directorate; PakistánFil: Kussul, Nataliia. National Academy of Sciences of Ukraine. Space Research Institute and State Space Agency of Ukraine; UcraniaFil: Lebourgeois, Valentine. Centre de Coopération Internationale en Recherche Agronomique pour le Développerment; FranciaFil: Le Page, Michel. Université Cadi Ayyad. Faculté des Sciences Semlalia. Laboratoire Mixte International TREMA; Marruecos. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Newby, Terrence. Agricultural Research Council; SudáfricaFil: Savin, Igor. V.V. Dokuchaev Soil Science Institute; RusiaFil: Verón, Santiago Ramón. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; ArgentinaFil: Koetz, Benjamin. European Space Agency. European Space Research Institute; ItaliaFil: Defourny, Pierre. Université Catholique de Louvain. Earth and Life Institute; Bélgic

Geographical variation in relationships between parental body size and offspring phenotype at birth

BACKGROUND: Size and body proportions at birth are partly determined by maternal body composition, but most studies of mother-baby relationships have only considered the effects of maternal height and weight on offspring birth weight, and few have examined the size of effects. Paternal size and body composition also play a role, primarily through the fetal genome, although few studies have investigated relationships with neonatal phenotype. METHODS: Data from the UK, Finland, India, Sri Lanka, China, DR Congo, Nigeria and Jamaica were used to investigate the effects of maternal measures (derived at 30 weeks' gestation, n=16,418), and also paternal size (n=3,733) on neonatal phenotype, for singleton, live-born, term births. RESULTS: After accounting for variation in maternal size and shape across populations, differences in neonatal phenotype were markedly reduced. Mother-baby relationships were similar across populations, although some were stronger in developing countries. Maternal height was generally the strongest predictor of neonatal length, maternal head circumference of neonatal head and maternal skinfold thickness of neonatal skinfolds. Relationships with maternal arm muscle area were generally weak. Effects of paternal height and body mass index were weaker than the equivalent maternal measurements in most studies. CONCLUSIONS: Differences in maternal body composition account for a large part of the geographical variation in neonatal phenotype. The size of the effects of all maternal measures on neonatal phenotype suggests that nutrition at every stage of the mother's life cycle may influence fetal growth. Further research is needed into father-baby relationships and the genetic mechanisms that influence fetal growth

Geographical variation in relationships between parental body size and offspring phenotype at birth

BACKGROUND: Size and body proportions at birth are partly determined by maternal body composition, but most studies of mother-baby relationships have only considered the effects of maternal height and weight on offspring birth weight, and few have examined the size of effects. Paternal size and body composition also play a role, primarily through the fetal genome, although few studies have investigated relationships with neonatal phenotype. METHODS: Data from the UK, Finland, India, Sri Lanka, China, DR Congo, Nigeria and Jamaica were used to investigate the effects of maternal measures (derived at 30 weeks' gestation, n=16,418), and also paternal size (n=3,733) on neonatal phenotype, for singleton, live-born, term births. RESULTS: After accounting for variation in maternal size and shape across populations, differences in neonatal phenotype were markedly reduced. Mother-baby relationships were similar across populations, although some were stronger in developing countries. Maternal height was generally the strongest predictor of neonatal length, maternal head circumference of neonatal head and maternal skinfold thickness of neonatal skinfolds. Relationships with maternal arm muscle area were generally weak. Effects of paternal height and body mass index were weaker than the equivalent maternal measurements in most studies. CONCLUSIONS: Differences in maternal body composition account for a large part of the geographical variation in neonatal phenotype. The size of the effects of all maternal measures on neonatal phenotype suggests that nutrition at every stage of the mother's life cycle may influence fetal growth. Further research is needed into father-baby relationships and the genetic mechanisms that influence fetal growth

Geographical variation in neonatal phenotype

BACKGROUND: Recent studies have shown associations between size and body proportions at birth and health outcomes throughout the life cycle, but there are few data on how neonatal phenotype varies in different populations around the world. METHODS: Data from the UK, Finland, India, Sri Lanka, China, DR Congo, Nigeria, and Jamaica (n=22,067) were used to characterize geographical differences in phenotype in singleton, live-born newborns. Measurements included birth weight, placental weight, length, head, chest, abdominal and arm circumferences, and skinfolds.RESULTS: Neonates in Europe were the largest, followed by Jamaica, East Asia (China), then Africa and South Asia. Birth weight varied widely (mean values 2,730-3,570 g), but in contrast, head circumference was similar in all except China (markedly smaller). The main difference in body proportions between populations was the head to length ratio, with small heads relative to length in China and large heads relative to length in South Asia and Africa. CONCLUSIONS: These marked geographical differences in neonatal phenotype need to be considered when investigating determinants of fetal growth, and optimal phenotype for short-term and long-term outcomes

Structural conservation of Lassa virus glycoproteins and recognition by neutralizing antibodies

Lassa fever is an acute hemorrhagic fever caused by the zoonotic Lassa virus (LASV). The LASV glycoprotein complex (GPC) mediates viral entry and is the sole target for neutralizing antibodies. Immunogen design is complicated by the metastable nature of recombinant GPCs and the antigenic differences among phylogenetically distinct LASV lineages. Despite the sequence diversity of the GPC, structures of most lineages are lacking. We present the development and characterization of prefusion-stabilized, trimeric GPCs of LASV lineages II, V, and VII, revealing structural conservation despite sequence diversity. High-resolution structures and biophysical characterization of the GPC in complex with GP1-A-specific antibodies suggest their neutralization mechanisms. Finally, we present the isolation and characterization of a trimer-preferring neutralizing antibody belonging to the GPC-B competition group with an epitope that spans adjacent protomers and includes the fusion peptide. Our work provides molecular detail information on LASV antigenic diversity and will guide efforts to design pan-LASV vaccines

Near real-time agriculture monitoring at national scale at parcel resolution: Performance assessment of the Sen2-Agri automated system in various cropping systems around the world

The convergence of new EO data flows, new methodological developments and cloud computing infrastructure calls for a paradigm shift in operational agriculture monitoring. The Copernicus Sentinel-2 mission providing a systematic 5-day revisit cycle and free data access opens a completely new avenue for near real-time crop specific monitoring at parcel level over large countries. This research investigated the feasibility to propose methods and to develop an open source system able to generate, at national scale, cloud-free composites, dynamic cropland masks, crop type maps and vegetation status indicators suitable for most cropping systems. The so-called Sen2-Agri system automatically ingests and processes Sentinel-2 and Landsat 8 time series in a seamless way to derive these four products, thanks to streamlined processes based on machine learning algorithms and quality controlled in situ data. It embeds a set of key principles proposed to address the new challenges arising from countrywide 10m resolution agriculture monitoring. The full-scale demonstration of this system for three entire countries (Ukraine, Mali, South Africa) and five local sites distributed across the world was a major challenge met successfully despite the availability of only one Sentinel-2 satellite in orbit. In situ data were collected for calibration and validation in a timely manner allowing the production of the four Sen2-Agri products over all the demonstration sites. The independent validation of the monthly cropland masks provided for most sites overall accuracy values higher than 90%, and already higher than 80% as early as the mid-season. The crop type maps depicting the 5 main crops for the considered study sites were also successfully validated: overal