Lakes in arid regions play an important role in regional water cycles and are a vital economic resource, but can fluctuate widely in area and volume. This study demonstrates the use of a multisensor ...satellite remote sensing method for the comprehensive monitoring of lake surface areas, water levels, and volume for the Toshka Lakes in southern Egypt, from lake formation in 1998 to mid-2017. Two spectral water indices were used to construct a daily time-series of surface area from the Advanced Very High Resolution Radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS), validated by higher-resolution Landsat images. Water levels were obtained from analysis of digital elevation models from the Shuttle Radar Topography Mission (SRTM) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), validated with ICESat Geoscience Laser Altimeter System (GLAS) laser altimetry. Total lake volume peaked at 26.54 × 109 m3 in December 2001, and declined to 0.76 × 109 m3 by August 2017. Evaporation accounted for approximately 86% of the loss, and groundwater recharge accounted for 14%. Without additional inflows, the last remaining lake will likely disappear between 2020 and 2022. The Enhanced Lake Index, a water index equivalent to the Enhanced Vegetation Index, was found to have lower noise levels than the Normalized Difference Lake Index. The results show that multi-platform satellite remote sensing provides an efficient method for monitoring the hydrology of lakes.
Covariate‐adjusted randomization (CAR) can reduce the risk of covariate imbalance and, when accounted for in analysis, increase the power of a trial. Despite CAR advances, stratified randomization ...remains the most common CAR method. Matched randomization (MR) randomizes treatment assignment within optimally identified matched pairs based on covariates and a distance matrix. When participants enroll sequentially, sequentially matched randomization (SMR) randomizes within matches found “on‐the‐fly” to meet a pre‐specified matching threshold. However, pre‐specifying the ideal threshold can be challenging and SMR yields less‐optimal matches than MR. We extend SMR to allow multiple participants to be randomized simultaneously, to use a dynamic threshold, and to allow matches to break and rematch if a better match later enrolls (sequential rematched randomization; SRR). In simplified settings and a real‐world application, we assess whether these extensions improve covariate balance, estimator/study efficiency, and optimality of matches. We investigate whether adjusting for more covariates can be detrimental upon covariate balance and efficiency as is the case of traditional stratified randomization. As secondary objectives, we use the case study to assess how SMR schemes compare side‐by‐side with common and related CAR schemes and whether adjusting for covariates in the design can be as powerful as adjusting for covariates in a parametric model. We find each SMR extension, individually and collectively, to improve covariate balance, estimator efficiency, study power, and quality of matches. We provide a case‐study where CAR schemes with randomization‐based inference can be as and more powerful than non‐CAR schemes with parametric adjustment for covariates.
Randomization is the foundation of any clinical trial involving treatment comparison. It helps mitigate selection bias, promotes similarity of treatment groups with respect to important known and ...unknown confounders, and contributes to the validity of statistical tests. Various restricted randomization procedures with different probabilistic structures and different statistical properties are available. The goal of this paper is to present a systematic roadmap for the choice and application of a restricted randomization procedure in a clinical trial.
We survey available restricted randomization procedures for sequential allocation of subjects in a randomized, comparative, parallel group clinical trial with equal (1:1) allocation. We explore statistical properties of these procedures, including balance/randomness tradeoff, type I error rate and power. We perform head-to-head comparisons of different procedures through simulation under various experimental scenarios, including cases when common model assumptions are violated. We also provide some real-life clinical trial examples to illustrate the thinking process for selecting a randomization procedure for implementation in practice.
Restricted randomization procedures targeting 1:1 allocation vary in the degree of balance/randomness they induce, and more importantly, they vary in terms of validity and efficiency of statistical inference when common model assumptions are violated (e.g. when outcomes are affected by a linear time trend; measurement error distribution is misspecified; or selection bias is introduced in the experiment). Some procedures are more robust than others. Covariate-adjusted analysis may be essential to ensure validity of the results. Special considerations are required when selecting a randomization procedure for a clinical trial with very small sample size.
The choice of randomization design, data analytic technique (parametric or nonparametric), and analysis strategy (randomization-based or population model-based) are all very important considerations. Randomization-based tests are robust and valid alternatives to likelihood-based tests and should be considered more frequently by clinical investigators.
The Red Sea was witness to important events during human history, including the first long steps in a trade network (the spice route) that would drive maritime technology and shape geopolitical ...fortunes for thousands of years. Punt was a pivotal early node in the rise of this enterprise, serving as an important emporium for luxury goods, including sacred baboons (
), but its location is disputed. Here, we use geospatial variation in the oxygen and strontium isotope ratios of 155 baboons from 77 locations to estimate the geoprovenance of mummified baboons recovered from ancient Egyptian temples and tombs. Five Ptolemaic specimens of
(404-40 BC) showed evidence of long-term residency in Egypt prior to mummification, consistent with a captive breeding program. Two New Kingdom specimens of
were sourced to a region that encompasses much of present-day Ethiopia, Eritrea, and Djibouti, and portions of Somalia and Yemen. This result is a testament to the tremendous reach of Egyptian seafaring during the 2nd millennium BC. It also corroborates the balance of scholarly conjecture on the location of Punt.
There has been little rigorous investigation of the transferability of existing empirical water clarity models developed at one location or time to other lakes and dates of imagery with differing ...conditions. Machine learning methods have not been widely adopted for analysis of lake optical properties such as water clarity, despite their successful use in many other applications of environmental remote sensing. This study compares model performance for a random forest (RF) machine learning algorithm and a simple 4-band linear model with 13 previously published empirical non-machine learning algorithms. We use Landsat surface reflectance product data aligned with spatially and temporally co-located in situ Secchi depth observations from northeastern USA lakes over a 34-year period in this analysis. To evaluate the transferability of models across space and time, we compare model fit using the complete dataset (all images and samples) to a single-date approach, in which separate models are developed for each date of Landsat imagery with more than 75 field samples. On average, the single-date models for all algorithms had lower mean absolute errors (MAE) and root mean squared errors (RMSE) than the models fit to the complete dataset. The RF model had the highest pseudo-R2 for the single-date approach as well as the complete dataset, suggesting that an RF approach outperforms traditional linear regression-based algorithms when modeling lake water clarity using satellite imagery.
Marine-terminating outlet glaciers discharge mass through iceberg calving, submarine melting, and meltwater run-off. While calving can be quantified by in situ and remote-sensing observations, ...meltwater run-off, the subglacial transport of meltwater, and submarine melting are not well constrained due to inherent difficulties observing the subglacial and proglacial environments at tidewater glaciers. Remote-sensing and in situ measurements of surface sediment plumes, and their suspended sediment concentration (SSC), have been used as a proxy for glacier meltwater run-off. However, this relationship between satellite reflectance and SSC has predominantly been established using land-terminating glaciers. Here, we use two Svalbard tidewater glaciers to establish a well-constrained relationship between Landsat-8 surface reflecance and SSC and argue that it can be used to measure relative meltwater run-off at tidewater glaciers throughout a summer melt season. We find the highest correlation between SSCs and Landsat-8 surface reflectance by using the red + NIR band combination (r
2
= 0.76). The highest correlation between SSCs and in situ field spectrometer measurements is in the 740-800 nm wavelength range (r
2
= 0.85), a spectral range not currently measured by Landsat. Additionally, we find that in situ and Landsat-8 measurements for surface reflectance of SSCs are not interchangeable and therefore establish a relationship for each detection method. We then use the Landsat-8 relationship to calculate total surface sediment load, finding a strong correlation between total surface sediment load and a proxy for meltwater run-off (r
2
≥ 0.89). Our results establish a new metric to calculate SSCs from Landsat-8 surface reflectance and demonstrate how the SSC of subglacial sediment plumes can be used to monitor relative seasonal meltwater discharge at tidewater glaciers.
Aeolian soil erosion is responsible for erosional landforms, or deflation patches, that are ubiquitous in the Kangerlussuaq region of West Greenland. Deflation patches are identifiable as bare ...regions within a mosaic of shrub and graminoid tundra, and have the potential to alter regional carbon cycling and vegetation dynamics. Understanding the spatial distribution of deflation patches is an important first step in establishing the drivers, controls, and ecological impacts of wind erosion in the region. Using high-resolution WorldView-2 satellite imagery, we created a land cover classification and percentage vegetation cover map to investigate the regional distribution and variability of deflation patches. Across the study area, deflation patches account for 22 percent of the terrestrial land surface and occur in greater density closer to the Greenland Ice Sheet (GrIS). Farther away from the GrIS, local topography plays a larger role in determining the distribution of deflation patches, with wind erosion tending to occur on steep south-southeast-facing slopes. Parallels between the distribution of deflation patches and local wind patterns suggest that katabatic winds are an important driver behind deflation patch occurrence. Within deflation patches, graminoid cover increases with distance from the GrIS, due either to a lesser degree of erosion or to a longer recovery time. In the context of recent circumpolar shrub expansion, deflation might locally limit the dominance of shrubs by creating habitat more suitable for graminoids and is an important factor to consider when predicting vegetation changes in West Greenland.
The prevalence of Lyme disease and other tick-borne diseases is dramatically increasing across the United States. While the rapid rise in Lyme disease is clear, the causes of it are not. Modeling ...Ixodes scapularis Say (Acari: Ixodidae), the primary Lyme disease vector in the eastern United States, presents an opportunity to disentangle the drivers of increasing Lyme disease, including climate, land cover, and host populations. We improved upon a recently developed compartment model of ordinary differential equations that simulates I. scapularis growth, abundance, and infection with Borrelia burgdorferi (Spirochaetales: Spirochaetaceae) by adding land cover effects on host populations, refining the representation of growth stages, and evaluating output against observed data. We then applied this model to analyze the sensitivity of simulated I. scapularis dynamics across temperature and land cover in the northeastern United States. Specifically, we ran an ensemble of 232 simulations with temperature from Hanover, New Hampshire and Storrs, Connecticut, and land cover from Hanover and Cardigan in New Hampshire, and Windsor and Danielson in Connecticut. Consistent with observations, simulations of I. scapularis abundance are sensitive to temperature, with the warmer Storrs climate significantly increasing the number of questing I. scapularis at all growth stages. While there is some variation in modeled populations of I. scapularis infected with B. burgdorferi among land cover distributions, our analysis of I. scapularis response to land cover is limited by a lack of observations describing host populations, the proportion of hosts competent to serve as B. burgdorferi reservoirs, and I. scapularis abundance.
Using street view data, in replace of remotely sensed (RS) data, to study the health impact of greenspace has become popular. However, direct comparisons of these two methods of measuring greenspace ...are still limited, and their findings are inconsistent. On the other hand, almost all studies of greenspace focus on urban areas. The effectiveness of greenspace in rural areas remains to be investigated. In this study, we compared measures of greenspace based on the Google Street View data with those based on RS data by calculating the correlation between the two and evaluating their associations with birth outcomes. Besides the direct measures of greenness, we also compared the measures of environmental diversity, calculated with the two types of data. Our study area consists of the States of New Hampshire and Vermont, USA, which are largely rural. Our results show that the correlations between the two types of greenness measures were weak to moderate, and the greenness at an eye‐level view largely reflects the immediate surroundings. Neither the street view data‐ nor the RS data‐based measures identify the influence of greenspace on birth outcomes in our rural study area. Interestingly, the environmental diversity was largely negatively associated with birth outcomes, particularly gestational age. Our study revealed that in rural areas, the effectiveness of greenspace and environmental diversity may be considerably different from that in urban areas.
Plain Language Summary
Few studies directly compare the health impact of greenspace measured by two different methods in rural areas, one based on Google Street View data and the other based on remotely sensed data. To fill in the blank, we conducted the comparison in this study by calculating the correlation between the measurements of greenness and environmental diversity based on these two different data and evaluating the associations between these variables and birth outcomes in New Hampshire and Vermont, which are mostly rural areas of the United States. As a result, (a) the difference between the two types of greenspace was weak to moderate; (b) neither of the greenness measurements by two different data were significantly associated with birth outcomes, whereas environmental diversity measurements by two different data were largely negatively associated with gestation; (c) the effectiveness of greenspace and environmental diversity measured in rural areas may differ significantly from that in urban areas.
Key Points
We compared two methods for measuring greenspace in rural areas based on Google Street View data and remote sensing data, respectively
The comparison was conducted by calculating the correlation between the two and their associations with birth outcomes in NH and VT, USA
There is a considerable difference between the two types of greenspace measures, and neither significantly impacts birth outcomes
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