Uncertainty evaluation at three spatial scales for the NDVI-based VWC estimation method used in the SMAP algorithm

Vegetation water content (VWC) is the key input parameter for a soil moisture retrieval algorithm based on microwave remote sensing, and VWC uncertainty can limit the estimated accuracy of soil moisture. There has been little research on VWC algorithm development and validation in China, and the uncertainty of the VWC estimation method has not been well evaluated. Therefore, the aim of this study is to evaluate the uncertainty of the VWC estimation method used in the SMAP (Soil Moisture Active Passive) algorithm on three spatial scales (the point-scale, 30 m scale, and 1 km scale) for maize in northeast China. Results from three ground experimental datasets showed that the SMAP VWC estimation method was strongly biased with an average overestimation of 1.16 kg m^?2,1.04 kg m^?2, and 1.13 kg m^?2 for the point-scale, 30 m scale, and 1 km scale respectively, and maximum bias occurred in the mid-stage of maize. Also, a new power relationship between NDVI (Normalized Difference Vegetation Index) and VWC was proposed for the 30 m scale based on Sentinel 2 NDVI and field VWC values from 2017 experiment, with respective R² (coefficient of determination) and Root Mean Squared Error (RMSE) values of 0.80 and 0.67 kg m^?2. The results confirmed that this power relationship was still suitable for VWC estimation at the 1 km scale, and it has smaller bias than the original SMAP VWC method. Future work will be carried out to evaluate the applicability of this VWC estimation method over a lager region. It is expected that it can improve the accuracy of soil moisture by providing high precision VWC input parameters.     

Exact confidence intervals for the average causal effect on a binary outcome

Based on the physical randomization of completely randomized experiments, in a recent article in Statistics in Medicine, Rigdon and Hudgens propose two approaches to obtaining exact confidence intervals for the average causal effect on a binary outcome. They construct the first confidence interval by combining, with the Bonferroni adjustment, the prediction sets for treatment effects among treatment and control groups, and the second one by inverting a series of randomization tests. With sample size n, their second approach requires performing O(n⁴)randomization tests. We demonstrate that the physical randomization also justifies other ways to constructing exact confidence intervals that are more computationally efficient. By exploiting recent advances in hypergeometric confidence intervals and the stochastic order information of randomization tests, we propose approaches that either do not need to invoke Monte Carlo or require performing at most O(n²)randomization tests. We provide technical details and R code in the Supporting Information . Copyright © 2016 John Wiley & Sons, Ltd.     

A randomized study on the effect of modified behavioral activation treatment for depressive symptoms in rural left-behind elderly

Objective: To evaluate the effectiveness of a modified behavioral activation treatment (MBAT) intervention on reducing depressive symptoms in rural left-behind elderly.

Method: This is a randomized study registered in Chinese Clinical Trial Registry (ChiCTR-IOR-17011289). Eighty rural left-behind elderly people who had a Geriatric Depression Scale (GDS) score between 11 and 25 were randomly assigned to the intervention (n?=?40) and control group (n?=?40). The intervention group received both MBAT and regular treatment for 8 weeks while the control group received regular treatment. Both groups were assessed with the GDS, Beck Anxiety Inventory (BAI), and Oxford Happiness Questionnaire (OHQ) at baseline, immediately post-intervention, and at 3 months post-intervention.

Results: There were a total of 73 participants that completed the intervention. The scores of GDS and BAI decreased significantly, but the scores of OHQ increased significantly in the intervention group after 8 sessions of MBAT (P?<?.01). The reduction in depression symptoms after the intervention was maintained at the 3-month follow-up. Significant differences in GDS, BAI, and OHQ scores were observed between the intervention group and the control group (P?<?.01).

Conclusion: MBAT produced a significantly greater reduction in depressive symptoms than regular care in rural left-behind elderly.

Clinical or methodological significance of this article: A modified behavioral activation (BA) psychotherapy can significantly reduce the recurrence and seriousness of depression symptoms in the left-behind elderly with mild to moderate depression. This study also suggests that further study of the MBAT as an intervention will provide a direction for the management of mental health in rural left-behind elders.