| 11. |
- Duncanson, Laura, et al.
(författare)
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Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission
- 2022
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Ingår i: Remote Sensing of Environment. - : Elsevier BV. - 0034-4257 .- 1879-0704. ; 270
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Tidskriftsartikel (refereegranskat)abstract
- NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.
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| 12. |
- Duncanson, K., et al.
(författare)
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Impact of weight management nutrition interventions on dietary outcomes in children and adolescents with overweight or obesity : a systematic review with meta-analysis
- 2021
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Ingår i: Journal of human nutrition and dietetics. - : Wiley. - 0952-3871 .- 1365-277X. ; 34:1, s. 147-177
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The impact of obesity interventions on dietary intake in children and adolescents with overweight or obesity is unclear. This systematic review aimed to investigate the impact of the dietary component of weight management interventions on the change in diet in children and adolescents with overweight or obesity.METHODS: Eligible randomised controlled trials (RCTs) published between 1975 and 2020 were identified by a systematic search following Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Meta-analyses of eligible study outcomes were performed using statistical software. A multilevel random effects model was used with three significant random effects fitted using restricted maximum likelihood estimation.RESULTS: This review identified 109 RCTs, including 95 that reported at least one statistically significant dietary outcome change and 14 reporting no significant dietary change. Results from the meta-analyses (n = 29 studies) indicated that, compared to control groups, intervention groups achieved significantly greater reductions in mean total energy intake at ≤6 months (-194 kcal day-1 , 95% confidence interval = -275.80 to -112.90 kcal day-1 , P < 0.001) and up to 12 months (-112 kcal day-1 95% confidence interval = -218.92 to -5.83 kcal day-1 ) P = 0.038), increases in fruit and/or vegetable intakes over 2-12 months (n = 34, range +0.6 to +1.5 servings day-1 ) and reductions in consumption of sugar-sweetened beverages (n = 28, range -0.25 to -1.5 servings day-1 ) at 4-24 months follow-up.CONCLUSIONS: Obesity interventions with a dietary component have a modest but sustained impact on reducing total energy intake and improving intakes of specific food groups in children and adolescents with overweight or obesity. High quality RCTs that are powered to detect change in diet as a primary outcome are warranted.
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