Geometric Quality Testing of the WorldView-2 Image Data Acquired over the JRC Maussane Test Site using ERDAS LPS, PCI Geomatics and Keystone digital photogrammetry software packages - Inital Findings

This report presents the geometric quality results recorded for the five samples of the WorldView-2 Basic and Standard (processing level 1A and 2A) imagery acquired over the JRC Maussane Test Site. Different mathematical models of the WV2 sensor were tested, i.e. RPC-based and rigorous models implemented into PCI Geomatics, Keystone Spacemetric, and ERDAS IMAGINE& LPS software based on the following auxiliary data: - several configurations (eg. 9, 6, 4) of equally distributed GCPs of 0.1m<RMSEx,y,z<0.6m; - DEM of 2m grid and RMSEz=0.6m; - 12 well-distributed independent check points (ICPs) of RMSEx,y,z<0.6m. The preliminary results of the analysis show that the 1-D RMSE of the WV2 image characterised by large off-nadir angle, i.e. greater than 30 degrees (or elevation angle less than 56 deg) is close to or below the 2.5m EU acceptable threshold. Further testing is required, especially for less accurate DTM data, diverse terrains and images characterised by high satellite inclination angle. Consequently, this report recommends that at least 6 (or 9 in areas with terrain slope diversity or high off-nadir angle) well-distributed ground control points during the WV2 sensor modelling phase using the Rational Functions mathematical model should be used. The rigorous model requires a minimum 9 or more ground control points. Accuracy requirements for auxiliary date, i.e. ground control points and DEM, given in ¿Guidelines for Best Practice and Quality Checking of Ortho Imagery¿ should be strictly followed.JRC.DG.G.3-Monitoring agricultural resource

THEOS Geometric Image Quality Testing - Initial Findings

This report summarizes the initial outcome of the geometric quality testing of the panchromatic, pan-sharpening and multispectral THEOS images (level 1A and 2A) acquired over the JRC Maussane Test Site for the Common Agriculture Policy (CAP) Control with Remote Sensing (CwRS) Programme. Based on the limited K2, THEOS and DMCII sample images that were made available to us the THEOS PAN orthoimage can reach 2m accuracy provided that a dedicated rigorous model based on at least 9 well-defined, well-distributed ground control points (GCPs) of high accuracy (i.e. RMSEx,y < 0.90m) is applied; while the orthorectified THEOS 1B MS product accuracy can reach 6.8m, provided that a dedicated rigorous model based on at least 9 well-distributed GCPs of appropriate accuracy is appliedJRC.DG.G.3-Monitoring agricultural resource

Geometric Quality Testing of the WorldView-2 Image Data Acquired over the JRC Maussane Test Site using ERDAS LPS, PCI Geomatics and Keystone digital photogrammetry software packages – Initial Findings with ANNEX

This report presents the geometric quality results recorded for the five samples of the WorldView-2 Basic and Standard (processing level 1A and 2A) imagery acquired over the JRC Maussane Test Site. In order to quantify the influence of ground control points and the incidence angle on orthoimage geolocation accuracy, several configurations of well-distributed GCPs (of 0.1m<RMSEx,y,z<0.6m) were set up, and the WV2 images characterised by various off-nadir angles were tested. Accuracy investigations were performed using different mathematical models of the WV2 sensor were tested, i.e. RPC-based and rigorous models implemented into PCI Geomatics, Keystone Spacemetric, and ERDAS IMAGINE& LPS software based on the accurate DEM of 2m grid and RMSEz=0.6m. The horizontal accuracy assessment included computing the Root Mean Square Error (RMSE) of the residuals between the positions measured on the final product (orthoimage) and the reference positions of the 12 well-distributed independent Check Points (of RMSEx,y,z<0.6m) for each horizontal component (East, North). The results lead to the following main conclusions: The one-dimensional RMS error based on the manual measurement of a set of well-distributed Independent Check Points (ICPs) on the WV2 orthoimage: • is sensitive to the number of GCPs and decreases with increasing number of GCPs (fig. 9,10); • increases with increasing off-nadir angle and can reach the value of 2.5 WV-2 pixels for 30°(or higher) off-nadir angle provided 4-9 well-distributed GCPs with mean RMSEx,y < 0.6m and a DTM with 0.6m vertical accuracy is used (fig. 15, 16, 17, 18); • falls within the CwRS prime sensor accuracy criteria, i.e. an absolute 1-D RMSE of < 2.5m, based on 4 (or more) well-distributed GCPs with mean RMSEx,y < 0.6m, provided a DTM with 0.6m vertical accuracy used. The report recommends that at least 6 (or 9 in areas with terrain slope diversity and/or high off-nadir angle) well-distributed ground control points during the WV2 sensor modelling phase using the Rational Functions mathematical model should be used. The rigorous model requires a minimum 9 or more ground control points. Accuracy requirements for auxiliary date, i.e. ground control points and DEM, given in ‘Guidelines for Best Practice and Quality Checking of Ortho Imagery’ should be strictly followed.JRC.H.4-Monitoring agricultural resource

Sensitivity of the WorldView-2 satellite orthoimage horizontal accuracy with respect to sensor orientation method, number and distribution of ground control points, satellite off-nadir angles and strip length

Imagery acquired by the WorldView-2 (WV2) sensor is of potential interest to the Control with Remote Sensing (CwRS) Programme of the European Commission and therefore needs to be assessed. In details, the horizontal accuracy of the orthoimages which can be derived from WV2 imagery have to be concerned, recalling that in order to qualify WV2 as a Very High Resolution (VHR) prime sensor (i.e. a sensor suitable for measuring parcel areas to the accuracy requested by the Common Agriculture Policy - CAP regulation), the CwRS guidelines requires that the one-dimensional RMSE error (i.e. in the East and North components) measured on the external Check Points - CPs for any orthoimage should not exceed 2.5 m. This report summarizes the results regarding the orientation tests of the five WorldView-2 Panchromatic (WV2 PAN) images acquired over the JRC Maussane Test Site (Provence, Southern France), two Pan-sharpened (WV2 PANSHP) images (COSE_MODE_1) acquired over Cosenza Test Site (Southern Italy) and 9 Pan-sharpned (WV2 PANSHP) scenes (COSE_MODE_3) acquired over Cosenza Test Site (Southern Italy), carried out with Geomatica (PCI Geomatics), ERDAS Imagine 2011 and SISAR software, using both Rigorous model and Rational Polynomial Functions (RPFs) model with Rational Polynomial Coefficients (RPCs). The Hold-Out-Validation accuracy assessment method (HOV) was considered, computing the Root Mean Square Error (RMSE) of the residuals between the estimated and the reference positions of the Check Points (CPs) for each horizontal component (East, North) varying the number of the GCPs. In addition the Leave-One-Out Cross Validation (LOOCV) method was been used to identify possible outliers.JRC.H.4-Monitoring Agricultural Resource

Consensus guidelines for the use and interpretation of angiogenesis assays

The formation of new blood vessels, or angiogenesis, is a complex process that plays important roles in growth and development, tissue and organ regeneration, as well as numerous pathological conditions. Angiogenesis undergoes multiple discrete steps that can be individually evaluated and quantified by a large number of bioassays. These independent assessments hold advantages but also have limitations. This article describes in vivo, ex vivo, and in vitro bioassays that are available for the evaluation of angiogenesis and highlights critical aspects that are relevant for their execution and proper interpretation. As such, this collaborative work is the first edition of consensus guidelines on angiogenesis bioassays to serve for current and future reference

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants

Summary Background Comparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents. Methods For this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence. Findings We pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m2. In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became progressively less healthy compared with their comparators as they grew older by not growing as tall (eg, boys in Austria and Barbados, and girls in Belgium and Puerto Rico) or gaining too much weight for their height (eg, girls and boys in Kuwait, Bahrain, Fiji, Jamaica, and Mexico; and girls in South Africa and New Zealand). In other countries, growing children overtook the height of their comparators (eg, Latvia, Czech Republic, Morocco, and Iran) or curbed their weight gain (eg, Italy, France, and Croatia) in late childhood and adolescence. When changes in both height and BMI were considered, girls in South Korea, Vietnam, Saudi Arabia, Turkey, and some central Asian countries (eg, Armenia and Azerbaijan), and boys in central and western Europe (eg, Portugal, Denmark, Poland, and Montenegro) had the healthiest changes in anthropometric status over the past 3·5 decades because, compared with children and adolescents in other countries, they had a much larger gain in height than they did in BMI. The unhealthiest changes—gaining too little height, too much weight for their height compared with children in other countries, or both—occurred in many countries in sub-Saharan Africa, New Zealand, and the USA for boys and girls; in Malaysia and some Pacific island nations for boys; and in Mexico for girls. Interpretation The height and BMI trajectories over age and time of school-aged children and adolescents are highly variable across countries, which indicates heterogeneous nutritional quality and lifelong health advantages and risks