Leveraging the Power of SAR Observations for Forest Monitoring Systems

Earth observations from Synthetic Aperture Radar (SAR) can provide unique information related to forest structure and condition. Despite the many advantages of SAR, particularly where clouds impede optical observations, a knowledge gap has prevented the applied remote sensing community from harnessing its full potential. Here, we discuss the results of a collaboration between SERVIR, a joint program between NASA and the U.S. Agency for International Development (USAID), and SilvaCarbon, the United States' contribution to the Global Forest Observation Initiative, to build global capacity in using SAR for forest monitoring and biomass estimation. This includes primarily the creation of 1) The SAR Handbook: Comprehensive Methodologies for Forest Monitoring and Biomass Estimation, 2) a series of international hands-on trainings and training materials, 3) quick-reference guides illustrating SAR concepts, and 4) animated videos explaining how SAR works. The SERVIR-Global community joined efforts to develop a hands-on guide to support decision-makers in the forestry community to leverage the power of SAR technology to better protect and manage forest resources. We worked with world-renowned SAR experts to provide targeted trainings and develop the SAR Handbook. This handbook consists of approachable theoretical background and applied content that contributes to filling the knowledge gap in the applied use of SAR technology for forestry applications. We hope that forest managers and remote sensing specialists will use these materials to benefit from currently available SAR datasets, as well as prepare for future SAR missions, such as NISAR and BIOMASS. Since its release on April 11, 2019, the SAR Handbook has been accessed more than 100,000 times in less than a month, demonstrating the remote sensing community's urgent need and interest to learn and use SAR

Leveraging the Power of SAR Observations for Forest Monitoring Systems

Earth observations from Synthetic Aperture Radar (SAR) can provide unique information related to forest structure and condition. Despite the many advantages of SAR, particularly where clouds impede optical observations, a knowledge gap has prevented the applied remote sensing community from harnessing its full potential. Here, we discuss the results of a collaboration between SERVIR, a joint program between NASA and the U.S. Agency for International Development (USAID), and SilvaCarbon, the United States contribution to the Global Forest Observation Initiative, to build global capacity in using SAR for forest monitoring and biomass estimation. This includes primarily the creation of 1) The SAR Handbook: Comprehensive Methodologies for Forest Monitoring and Biomass Estimation, 2) a series of international hands-on trainings and training materials, 3) quick-reference guides illustrating SAR concepts, and 4) animated videos explaining how SAR works. The SERVIR-Global community joined efforts to develop a hands-on guide to support decision-makers in the forestry community to leverage the power of SAR technology to better protect and manage forest resources. We worked with world-renowned SAR experts to provide targeted trainings and develop the SAR Handbook. This handbook consists of approachable theoretical background and applied content that contributes to filling the knowledge gap in the applied use of SAR technology for forestry applications. We hope that forest managers and remote sensing specialists will use these materials to benefit from currently available SAR datasets, as well as prepare for future SAR missions, such as NISAR and BIOMASS. Since its release on April 11, 2019, the SAR Handbook has been accessed more than 100,000 times in less than a month, demonstrating the remote sensing communitys urgent need and interest to learn and use SAR

Clinical risk factors of adverse outcomes among women with COVID-19 in the pregnancy and postpartum period: A sequential, prospective meta-analysis

OBJECTIVE: This sequential, prospective meta-analysis (sPMA) sought to identify risk factors among pregnant and postpartum women with COVID-19 for adverse outcomes related to: disease severity, maternal morbidities, neonatal mortality and morbidity, adverse birth outcomes. DATA SOURCES: We prospectively invited study investigators to join the sPMA via professional research networks beginning in March 2020. STUDY ELIGIBILITY CRITERIA: Eligible studies included those recruiting at least 25 consecutive cases of COVID-19 in pregnancy within a defined catchment area. STUDY APPRAISAL AND SYNTHESIS METHODS: We included individual patient data from 21 participating studies. Data quality was assessed, and harmonized variables for risk factors and outcomes were constructed. Duplicate cases were removed. Pooled estimates for the absolute and relative risk of adverse outcomes comparing those with and without each risk factor were generated using a two-stage meta-analysis. RESULTS: We collected data from 33 countries and territories, including 21,977 cases of SARS-CoV-2 infection in pregnancy or postpartum. We found that women with comorbidities (pre-existing diabetes, hypertension, cardiovascular disease) versus those without were at higher risk for COVID-19 severity and pregnancy health outcomes (fetal death, preterm birth, low birthweight). Participants with COVID-19 and HIV were 1.74 times (95% CI: 1.12, 2.71) more likely to be admitted to the ICU. Pregnant women who were underweight before pregnancy were at higher risk of ICU admission (RR 5.53, 95% CI: 2.27, 13.44), ventilation (RR 9.36, 95% CI: 3.87, 22.63), and pregnancy-related death (RR 14.10, 95% CI: 2.83, 70.36). Pre-pregnancy obesity was also a risk factor for severe COVID-19 outcomes including ICU admission (RR 1.81, 95% CI: 1.26,2.60), ventilation (RR 2.05, 95% CI: 1.20,3.51), any critical care (RR 1.89, 95% CI: 1.28,2.77), and pneumonia (RR 1.66, 95% CI: 1.18,2.33). Anemic pregnant women with COVID-19 also had increased risk of ICU admission (RR 1.63, 95% CI: 1.25, 2.11) and death (RR 2.36, 95% CI: 1.15, 4.81). CONCLUSION: We found that pregnant women with comorbidities including diabetes, hypertension, and cardiovascular disease were at increased risk for severe COVID-19-related outcomes, maternal morbidities, and adverse birth outcomes. We also identified several less commonly-known risk factors, including HIV infection, pre-pregnancy underweight, and anemia. Although pregnant women are already considered a high-risk population, special priority for prevention and treatment should be given to pregnant women with these additional risk factors

Clinical risk factors of adverse outcomes among women with COVID-19 in the pregnancy and postpartum period: a sequential, prospective meta-analysis

Objective This sequential, prospective meta-analysis (sPMA) sought to identify risk factors among pregnant and postpartum women with COVID-19 for adverse outcomes related to: disease severity, maternal morbidities, neonatal mortality and morbidity, adverse birth outcomes. Data sources We prospectively invited study investigators to join the sPMA via professional research networks beginning in March 2020. Study eligibility criteria Eligible studies included those recruiting at least 25 consecutive cases of COVID-19 in pregnancy within a defined catchment area. Study appraisal and synthesis methods We included individual patient data from 21 participating studies. Data quality was assessed, and harmonized variables for risk factors and outcomes were constructed. Duplicate cases were removed. Pooled estimates for the absolute and relative risk of adverse outcomes comparing those with and without each risk factor were generated using a two-stage meta-analysis. Results We collected data from 33 countries and territories, including 21,977 cases of SARS-CoV-2 infection in pregnancy or postpartum. We found that women with comorbidities (pre-existing diabetes, hypertension, cardiovascular disease) versus those without were at higher risk for COVID-19 severity and pregnancy health outcomes (fetal death, preterm birth, low birthweight). Participants with COVID-19 and HIV were 1.74 times (95% CI: 1.12, 2.71) more likely to be admitted to the ICU. Pregnant women who were underweight before pregnancy were at higher risk of ICU admission (RR 5.53, 95% CI: 2.27, 13.44), ventilation (RR 9.36, 95% CI: 3.87, 22.63), and pregnancy-related death (RR 14.10, 95% CI: 2.83, 70.36). Pre-pregnancy obesity was also a risk factor for severe COVID-19 outcomes including ICU admission (RR 1.81, 95% CI: 1.26,2.60), ventilation (RR 2.05, 95% CI: 1.20,3.51), any critical care (RR 1.89, 95% CI: 1.28,2.77), and pneumonia (RR 1.66, 95% CI: 1.18,2.33). Anemic pregnant women with COVID-19 also had increased risk of ICU admission (RR 1.63, 95% CI: 1.25, 2.11) and death (RR 2.36, 95% CI: 1.15, 4.81). Conclusion We found that pregnant women with comorbidities including diabetes, hypertension, and cardiovascular disease were at increased risk for severe COVID-19-related outcomes, maternal morbidities, and adverse birth outcomes. We also identified several less commonly-known risk factors, including HIV infection, pre-pregnancy underweight, and anemia. Although pregnant women are already considered a high-risk population, special priority for prevention and treatment should be given to pregnant women with these additional risk factors

Clinical risk factors of adverse outcomes among women with COVID-19 in the pregnancy and postpartum period: A sequential, prospective meta-analysis.

OBJECTIVE This sequential, prospective meta-analysis (sPMA) sought to identify risk factors among pregnant and postpartum women with COVID-19 for adverse outcomes related to: disease severity, maternal morbidities, neonatal mortality and morbidity, adverse birth outcomes. DATA SOURCES We prospectively invited study investigators to join the sPMA via professional research networks beginning in March 2020. STUDY ELIGIBILITY CRITERIA Eligible studies included those recruiting at least 25 consecutive cases of COVID-19 in pregnancy within a defined catchment area. STUDY APPRAISAL AND SYNTHESIS METHODS We included individual patient data from 21 participating studies. Data quality was assessed, and harmonized variables for risk factors and outcomes were constructed. Duplicate cases were removed. Pooled estimates for the absolute and relative risk of adverse outcomes comparing those with and without each risk factor were generated using a two-stage meta-analysis. RESULTS We collected data from 33 countries and territories, including 21,977 cases of SARS-CoV-2 infection in pregnancy or postpartum. We found that women with comorbidities (pre-existing diabetes, hypertension, cardiovascular disease) versus those without were at higher risk for COVID-19 severity and pregnancy health outcomes (fetal death, preterm birth, low birthweight). Participants with COVID-19 and HIV were 1.74 times (95% CI: 1.12, 2.71) more likely to be admitted to the ICU. Pregnant women who were underweight before pregnancy were at higher risk of ICU admission (RR 5.53, 95% CI: 2.27, 13.44), ventilation (RR 9.36, 95% CI: 3.87, 22.63), and pregnancy-related death (RR 14.10, 95% CI: 2.83, 70.36). Pre-pregnancy obesity was also a risk factor for severe COVID-19 outcomes including ICU admission (RR 1.81, 95% CI: 1.26,2.60), ventilation (RR 2.05, 95% CI: 1.20,3.51), any critical care (RR 1.89, 95% CI: 1.28,2.77), and pneumonia (RR 1.66, 95% CI: 1.18,2.33). Anemic pregnant women with COVID-19 also had increased risk of ICU admission (RR 1.63, 95% CI: 1.25, 2.11) and death (RR 2.36, 95% CI: 1.15, 4.81). CONCLUSION We found that pregnant women with comorbidities including diabetes, hypertension, and cardiovascular disease were at increased risk for severe COVID-19-related outcomes, maternal morbidities, and adverse birth outcomes. We also identified several less commonly-known risk factors, including HIV infection, pre-pregnancy underweight, and anemia. Although pregnant women are already considered a high-risk population, special priority for prevention and treatment should be given to pregnant women with these additional risk factors