Dataset Information

Estimating Spatial and Temporal Trends in Environmental Indices Based on Satellite Data: A Two-Step Approach.

ABSTRACT: This paper presents a method for employing satellite data to evaluate spatial and temporal patterns in environmental indices of interest. In the first step, linear regression coefficients are extracted for each area in the image. These coefficients are then employed as a response variable in a boosted regression tree with geographic coordinates as explanatory variables. Here, a two-step approach is described in the context of a substantive case study comprising 30 years of satellite derived fractional green vegetation cover for a large region in Queensland, Australia. In addition to analysis of the entire image and timeframe, separate analyses are undertaken over decades and over sub-regions of the study region. The results demonstrate both the utility of the approach and insights into spatio-temporal trends in green vegetation for this site. These findings support the feasibility of using the proposed two-step approach and geographic coordinates in the analysis of satellite derived indices over space and time.

SUBMITTER: Colin B

PROVIDER: S-EPMC6359653 | biostudies-other | 2019 Jan

REPOSITORIES: biostudies-other

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Estimating Spatial and Temporal Trends in Environmental Indices Based on Satellite Data: A Two-Step Approach.

Colin Brigitte B Mengersen Kerrie K

Sensors (Basel, Switzerland) 20190117 2

This paper presents a method for employing satellite data to evaluate spatial and temporal patterns in environmental indices of interest. In the first step, linear regression coefficients are extracted for each area in the image. These coefficients are then employed as a response variable in a boosted regression tree with geographic coordinates as explanatory variables. Here, a two-step approach is described in the context of a substantive case study comprising 30 years of satellite derived frac ...[more]

PMID: 30658405

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Project description:BackgroundResearch suggests that geographic location may affect ovarian cancer (OC) outcomes. Insurance status often remains an important predictor of outcomes. The Affordable Care Act was enacted in 2010 to expand access to affordable health insurance. Our objective was to examine spatiotemporal trends in OC treatment nonadherence and disease-specific mortality in California (USA) among women diagnosed with OC.MethodsNewly diagnosed epithelial OC cases between 1996 and 2017 were identified from the California Cancer Registry. Spatiotemporal trends in adherence to treatment guidelines were examined using generalized additive models and OC-specific mortality using Cox proportional hazards additive models. Prediction grids covering California were used to display the odds ratios (ORs) and hazard ratios of location using the median value for the study area as the referent value. Seven overlapping 5-year periods and 2 larger ones (pre- and post-2013) were assessed. Analyses were stratified according to stage (early vs advanced) and used P = .05 to determine statistical significance.ResultsStatistically significant spatial patterns in treatment nonadherence were observed for every time period examined (P < .001). Odds of treatment nonadherence associated with geographic location were highest among women with early-stage OC in southern Los Angeles County during 2014-2017 (OR max = 3.89, confidence interval = 1.04 to 7.61). For women with advanced-stage OC, residing in northern California was generally associated with lower odds ratios, whereas southern California was associated with higher odds ratios, with higher odds in the latter time period (OR range = 0.53-1.84 in 1996-2012 vs 0.49-2.37 in 2013-2017). Geographic location was not a statistically significant predictor of mortality.ConclusionsResidential location was statistically significantly associated with treatment received in California, with spatial patterns varying over time but not OC-specific mortality. Changes in insurance status over time were accompanied by shifts in population demographics and increased travel distances to receive care.

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Dataset Information

Estimating Spatial and Temporal Trends in Environmental Indices Based on Satellite Data: A Two-Step Approach.

Publications

Estimating Spatial and Temporal Trends in Environmental Indices Based on Satellite Data: A Two-Step Approach.

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