Cotton Yield Estimate Using Sentinel-2 Data and an Ecosystem Model over the Southern US

High-resolution data with nearly global coverage from Sentinel-2 mission open a new era for crop growth monitoring and yield estimation from remote sensing. The objective of this study is to demonstrate the potential of using Sentinel-2 biophysical data combined with an ecosystem modeling approach for estimation of cotton yield in the southern United States (US). The Boreal Ecosystems Productivity Simulator (BEPS) ecosystem model was used to simulate the cotton gross primary production (GPP) over three Sentinel-2 tiles located in Mississippi, Georgia, and Texas in 2017. Leaf area index (LAI) derived from Sentinel-2 measurements and hourly meteorological data from Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) reanalysis were used to drive the ecosystem model. The simulated GPP values at 20-m grid spacing were aggregated to the county level (17 counties in total) and compared to the cotton lint yield estimates at the county level which are available from National Agricultural Statistics Service in the United States Department of Agriculture. The results of the comparison show that the BEPS-simulated cotton GPP explains 85% of variation in cotton yield. Our study suggests that the integration of Sentinel-2 LAI time series into the ecosystem model results in reliable estimates of cotton yield.

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Characterizing the spatiotemporal heterogeneity of the COVID-19 vaccination landscape

10.1101/2021.10.04.21263345 ◽

2021 ◽

Author(s):

Andrew Tiu ◽

Zachary Susswein ◽

Alexes Merritt ◽

Shweta Bansal

Keyword(s):

United States ◽

Vaccination Coverage ◽

Vaccination Campaign ◽

The United States ◽

County Level ◽

Spatial Clusters ◽

Southern Us ◽

The Us ◽

Target Locations ◽

County Scale

AbstractIt is critical that we maximize vaccination coverage across the United States so that SARS-CoV-2 transmission can be suppressed, and we can sustain the recent reopening of the nation. Maximizing vaccination requires that we track vaccination patterns to measure the progress of the vaccination campaign and target locations that may be undervaccinated. To improve efforts to track and characterize COVID-19 vaccination progress in the United States, we integrate CDC and state-provided vaccination data, identifying and rectifying discrepancies between these data sources. We find that COVID-19 vaccination coverage in the US exhibits significant spatial heterogeneity at the county level and statistically identify spatial clusters of undervaccination, all with foci in the southern US. Vaccination progress at the county level is also variable; many counties stalled in vaccination into June 2021 and few recovered by July, with transmission of the Delta variant rapidly rising. Using a comparison with a mechanistic growth model fitted to our integrated data, we classify vaccination dynamics across time at the county scale. Our findings underline the importance of curating accurate, fine-scale vaccination data and the continued need for widespread vaccination in the US, especially in the wake of the highly transmissible Delta variant.

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Validation of baseline and modified Sentinel-2 Level 2 Prototype Processor leaf area index retrievals over the United States

ISPRS Journal of Photogrammetry and Remote Sensing ◽

10.1016/j.isprsjprs.2021.02.020 ◽

2021 ◽

Vol 175 ◽

pp. 71-87

Author(s):

Luke A. Brown ◽

Richard Fernandes ◽

Najib Djamai ◽

Courtney Meier ◽

Nadine Gobron ◽

...

Keyword(s):

United States ◽

Leaf Area Index ◽

Leaf Area ◽

The United States ◽

Area Index ◽

Level 2 ◽

Sentinel 2

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Supplemental Material for Future-Oriented Tweets Predict Lower County-Level HIV Prevalence in the United States

Health Psychology ◽

10.1037/hea0000279.supp ◽

2015 ◽

Keyword(s):

United States ◽

The United States ◽

Hiv Prevalence ◽

County Level

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Introducing the United States Police-Shooting Database: A Multi-Level Bayesian Analysis of Racial Bias in Police Shootings at the County-Level in the United States, 2011-2014

SSRN Electronic Journal ◽

10.2139/ssrn.2534673 ◽

2014 ◽

Cited By ~ 1

Author(s):

Cody Ross

Keyword(s):

United States ◽

Bayesian Analysis ◽

Racial Bias ◽

The United States ◽

County Level ◽

Police Shootings ◽

Multi Level ◽

Police Shooting

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Effect of specific non-pharmaceutical intervention policies on SARS-CoV-2 transmission in the counties of the United States

Nature Communications ◽

10.1038/s41467-021-23865-8 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Bingyi Yang ◽

Angkana T. Huang ◽

Bernardo Garcia-Carreras ◽

William E. Hart ◽

Andrea Staid ◽

...

Keyword(s):

United States ◽

Home Visiting ◽

Leisure Activities ◽

The United States ◽

Causal Effects ◽

Basic Reproductive Number ◽

Reproductive Number ◽

County Level ◽

Metapopulation Model ◽

Pharmaceutical Interventions

AbstractNon-pharmaceutical interventions (NPIs) remain the only widely available tool for controlling the ongoing SARS-CoV-2 pandemic. We estimated weekly values of the effective basic reproductive number (Reff) using a mechanistic metapopulation model and associated these with county-level characteristics and NPIs in the United States (US). Interventions that included school and leisure activities closure and nursing home visiting bans were all associated with a median Reff below 1 when combined with either stay at home orders (median Reff 0.97, 95% confidence interval (CI) 0.58–1.39) or face masks (median Reff 0.97, 95% CI 0.58–1.39). While direct causal effects of interventions remain unclear, our results suggest that relaxation of some NPIs will need to be counterbalanced by continuation and/or implementation of others.

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Real-World Utilization of Oral Anticancer Agents Costs in Older Adults with Metastatic Renal Cell Carcinoma in the United States

Kidney Cancer ◽

10.3233/kca-210119 ◽

2021 ◽

pp. 1-13

Author(s):

Lauren E. Wilson ◽

Lisa Spees ◽

Jessica Pritchard ◽

Melissa A. Greiner ◽

Charles D. Scales ◽

...

Keyword(s):

United States ◽

Anticancer Agents ◽

Patient Characteristics ◽

The United States ◽

Socioeconomic Indicators ◽

Economic Implications ◽

Southern Us ◽

Race Ethnicity ◽

Nationally Representative ◽

Oral Anticancer Agents

Background: Substantial racial and socioeconomic disparities in metastatic RCC (mRCC) have persisted following the introduction of targeted oral anticancer agents (OAAs). The relationship between patient characteristics and OAA access and costs that may underlie persistent disparities in mRCC outcomes have not been examined in a nationally representative patient population. Methods: Retrospective SEER-Medicare analysis of patients diagnosed with mRCC between 2007–2015 over age 65 with Medicare part D prescription drug coverage. Associations between patient characteristics, OAA receipt, and associated costs were analyzed in the 12 months following mRCC diagnosis and adjusted to 2015 dollars. Results: 2,792 patients met inclusion criteria, of which 32.4%received an OAA. Most patients received sunitinib (57%) or pazopanib (28%) as their first oral therapy. Receipt of OAA did not differ by race/ethnicity or socioeconomic indicators. Patients of advanced age (> 80 years), unmarried patients, and patients residing in the Southern US were less likely to receive OAAs. The mean inflation-adjusted 30-day cost to Medicare of a patient’s first OAA prescription nearly doubled from $3864 in 2007 to $7482 in 2015, while patient out-of-pocket cost decreased from $2409 to $1477. Conclusion: Race, ethnicity, and socioeconomic status were not associated with decreased OAA receipt in patients with mRCC; however, residing in the Southern United States was, as was marital status. Surprisingly, the cost to Medicare of an initial OAA prescription nearly doubled from 2007 to 2015, while patient out-of-pocket costs decreased substantially. Shifts in OAA costs may have significant economic implications in the era of personalized medicine.

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