To investigate preeclampsia etiologies, we examined relationships between greenspace, air pollution, and neighborhood factors. Data were from hospital records and geocoded residences of 77,406 women in San Joaquin Valley, California from 2000 to 2006. Preeclampsia was divided into mild, severe, or superimposed onto pre-existing hypertension. Greenspace within 100 and 500 m residential buffers was estimated from satellite data using normalized difference vegetation index (NDVI). Air quality data were averaged over pregnancy from daily 24-h averages of nitrogen dioxide, particulate matter <10 µm (PM10) and <2.5 µm (PM2.5), and carbon monoxide. Neighborhood socioeconomic (SES) factors included living below the federal poverty level and median annual income using 2000 US Census data. Odds of preeclampsia were estimated using logistic regression. Effect modification was assessed using Wald tests. More greenspace (500 m) was inversely associated with superimposed preeclampsia (OR = 0.57). High PM2.5 and low SES were associated with mild and severe preeclampsia. We observed differences in associations between greenspace (500 m) and superimposed preeclampsia by neighborhood income and between greenspace (500 m) and severe preeclampsia by PM10, overall and among those living in higher SES neighborhoods. Less greenspace, high particulate matter, and high-poverty/low-income neighborhoods were associated with preeclampsia, and effect modification was observed between these exposures. Further research into exposure combinations and preeclampsia is warranted.

BACKGROUND:We investigated whether residing near more green space might reduce the risk of preeclampsia.METHODS:Participants were women who delivered a live, singleton birth between 1998 and 2011 in eight counties of the San Joaquin Valley in California. There were 7276 cases of preeclampsia divided into mild, severe, or superimposed on preexisting hypertension. Controls were 197,345 women who did not have a hypertensive disorder and delivered between 37 and 41 weeks. Green space was estimated from satellite data using Normalized Difference Vegetation Index (NDVI), an index calculated from surface reflectance at the visible and near-infrared wavelengths. Values closer to 1 denote a higher density of green vegetation. Average NDVI was calculated within a 50 m, 100 m, and 500 m buffer around each woman's residence. Odds ratios and 95% confidence intervals were estimated comparing the lowest and highest quartiles of mean NDVI to the interquartile range comparing each preeclampsia phenotype, divided into early (20-31 weeks) and late (32-36 weeks) preterm birth, to full-term controls.RESULTS:We observed an inverse association in the 500 m buffer for women in the top quartile of NDVI and a positive association for women in the lowest quartile of NDVI for women with superimposed preeclampsia. There were no associations in the 50 and 100 m buffers.CONCLUSION:Within a 500 m buffer, more green space was inversely associated with superimposed preeclampsia. Future work should explore the mechanism by which green space may protect against preeclampsia.

Antarctic continental shelf waters are the most biologically productive in the Southern Ocean. Although satellite‐derived algorithms report peak productivity during the austral spring/early summer, recent studies provide evidence for substantial late summer productivity that is associated with green colored frazil ice. Here we analyze daily Moderate Resolution Imaging Spectroradiometer satellite images for February and March from 2003 to 2017 to identify green colored frazil ice hot spots. Green frazil ice is concentrated in 11 of the 13 major sea ice production polynyas, with the greenest frazil ice in the Terra Nova Bay and Cape Darnley polynyas. While there is substantial interannual variability, green frazil ice is present over greater than 300,000 km2 during March. Late summer frazil ice‐associated algal productivity may be a major phenomenon around Antarctica that is not considered in regional carbon and ecosystem models.

The Landsat series of satellites provide a nearly continuous, high resolution data record of the Earth surface from the early 1970s through to the present. The public release of the entire Landsat archive, free of charge, along with modern computing capacity, has enabled Earth monitoring at the global scale with high spatial resolution. With the large data volume and seasonality varying across the globe, image selection is a particularly important challenge for regional and global multitemporal studies to remove the interference of seasonality from long term trends. This paper presents an automated method for selecting images for global scale lake mapping to minimize the influence of seasonality, while maintaining long term trends in lake surface area dynamics. Using historical meteorological data and a simple water balance model, we define the most stable period after the rainy season, when inflows equal outflows, independently for each Landsat tile and select images acquired during that ideal period for lake surface area mapping. The images selected using this method provide nearly complete global area coverage at decadal episodes for circa 2000 and circa 2014 from Landsat Enhanced Thematic Mapper Plus (ETM+) and Operational Land Imager (OLI) sensors, respectively. This method is being used in regional and global lake dynamics mapping projects, and is potentially applicable to any regional/global scale remote sensing application.

Inland lakes, important water resources, play a crucial role in the global water cycle and are sensitive to climate change and human activities. There clearly is a pressing need to understand temporal and spatial variations of lakes at global and continental scales. The recent operation of Landsat 8 extends the unprecedented Landsat record to over 40years, allowing long-term, large-scale lake dynamics mapping at high resolutions. Using our circa-2000 lake product derived from Landsat 7 images as a reference, this research produces a circa-2015 map of representative lake extents and distributions, and addresses seasonal and inter-annual lake area variability using Landsat 8 images acquired in lake stable seasons at a continental scale. Oceania is chosen here as a case study as it contains a large group of salt lakes that exhibit high area variability and has the most intensive image coverage during the first 2.5-year operation of Landsat 8. Accordingly, this paper describes an adaptive algorithm to automate lake mapping for various surface conditions using images acquired during lake stable seasons and a compositing scheme in the vector domain to generate a representative continental mosaic of lake extents from multi-temporal mapping. Our results demonstrate that these strategies and methods produce a highly reliable and representative composite of highly-variable lake extents across Oceania, and are potentially applicable to other large-scale lake mapping projects using multi-temporal data.

Author(s): Lyons, Evan Albert | Advisor(s): Sheng, Yongwei | Abstract: The boreal forest circles the high northern latitudes but it is far from a continuous carpet of evergreen trees. Rather, the boreal forest is a patchwork of land cover types in constant flux as they recover from wildfire and then are burned again. This fast turnover of land cover makes the boreal forest particularly susceptible to rapid change in response to climate. Furthermore, the boreal forest is an important component of the climate system that pumps heat into the atmosphere and significantly raises northern hemisphere temperatures year-round. As both a major component of the climate system and a sensitive indicator of climate change, the boreal forest is in a feedback loop. The direction of that feedback loop, positive or negative, depends largely on the strength of the land-atmosphere exchange of heat and momentum driven by forest cover and its spatial structure. That spatial structure has yet to be comprehensively measured. This dissertation used newly available, high resolution, satellite based forest cover data to quantify the heterogeneity of the boreal forest in North America. First, at the local scale, the pattern of forest cover patches within fires were found to be larger, more regularly shaped, and clustered than in unburned forest. The heterogeneity metrics also returned to pre-fire levels relatively quickly. At the continental scale, the landscape heterogeneity maps were analyzed by region, with respect to the northern extent of trees, and disturbance regimes. The boreal forest regions had smaller, more complicated forest patches, and no single dominant forest cover class which was significantly different than the temperate forests that border the region to the south. When compared to two preexisting maps of the boreal treeline, the patch cohesion metric indicated that the tundra ecoregion extended further south into the forested Central and Eastern Canada. Based on this finding, a new patch cohesion-based treeline was drawn which divides the boreal forest and tundra in a standard and repeatable way. Lastly, fires and lakes had the opposite influence on the heterogeneity metric contagion. Fires tended to decrease heterogeneity in the landscape because they were larger than the preexisting forest patches while lakes were smaller and broke up the landscape increasing heterogeneity. The heterogeneity maps produced as a part of this dissertation will continue to provide insight into the spatial pattern of the boreal forest in the future.

Regional- to global-scale lake maps can now be produced using existing technology and freely available data and serve as powerful tools for a variety of lake- and water-related studies. The accuracy of these studies depends in part on the accuracy of the lake map that they use. Mapping lakes using remote sensing requires a careful study of error and uncertainty. Errors in lake maps are caused by sensor-specific, lake-specific, and processing-specific factors. These can be further broken down to spatial, spectral/radiometric, and temporal factors. In this study, we analyse and compare these factors using modern and historical Landsat images along with intensive ground surveys of lakes in northern Alaska. Percentage error in lake area (relative to lake size) decreases for larger and more circular lakes, making a minimum size threshold an effective error mitigation practice. Image resampling involved in image transformation significantly increased error in lake area and is easily avoided by performing co-registration in the vector domain. Spectral properties varied for individual lakes due to depth, suspended sediment, vegetation, and other in situ factors, necessitating a normalized water index and independently derived threshold values for each lake. For lake change detection studies, spatially degrading a finer resolution image to the resolution of the coarser image (a common practice) does not significantly affect the difference in observed lake area. Due to the large numbers of lakes, particularly in the climatologically sensitive Arctic region, small errors in individual lake areas can compound to significantly impact results on regional to global scales. This study is intended to inform future static and multitemporal lake remote-sensing studies by evaluating errors and uncertainties in lake area, as measured by remote sensing.

The landscape on the Arctic Coastal Plain (ACP) of Alaska is dominated by thousands of thaw (thermokarst) lakes and associated drained thaw lake basins (DTLBs). Knowledge of the DTLBs benefits our understanding of thaw lake dynamics, carbon cycles, and paleo-climatic change on the ACP since the end of the Late Glacial. This study initializes the application of high-resolution digital elevation models (DEMs) into a systematic reconstruction of DTLBs on the western ACP and adjacent northern Arctic Foothills. The method combines a machine-based detection algorithm automating the delineation of basin paleoshorelines on IfSAR DEM data and a posterior quality control with the aid of high-resolution aerial photograph and Landsat-5 TM imagery. A total of ~3590km2 of thaw lakes and ~10130km2 of DTLBs were mapped, with an overall accuracy of 99.2% and a Kappa coefficient of 0.988. The delineated DTLB extents are conservative, as validated from eleven field-sampled paleoshorelines. A variety of topologic patterns such as merging, nesting, and overtopping are presented in the reconstructed DTLBs. Basin paleoshoreline levels are subject to average uncertainties of 0.4–0.7 m. The combined area of thaw lakes and DTLBs accounts for 57.1% of the western ACP and 23.2% of the northern Arctic Foothills in the study site. Regional analysis of several spatial and topographic characteristics demonstrates a distinct heterogeneity among the younger Outer Coastal Plain (YOCP), Outer Coastal Plain (OCP), Inner Coastal Plain (ICP), and the Arctic Foothills. Generally, the areal density of DTLBs decreases progressively on higher and older surfaces. The ICP has a lake–DTLB area ratio (0.37) greater than that in the other regions. DTLB bathymetry presents a positive correlation with surface elevation: basin maximum depths range from ~2.0m on the YOCP to ~ 8.0m on the Arctic Foothills. Given the reconstructed DTLBs, a total of 31.9 (±4.9) gigatons of net water drainage were estimated for the entire study area.

The coastal plain of Arctic Alaska contains many thousands of lakes developed in continuous permafrost, which are ice-free for only 3 -4 months each year. The spatial pattern of lake ice meltout for 1870 lakes (> 10 ha) in a similar to 9200km(2) study area near Barrow, Alaska, is analyzed using five Landsat scenes spanning a 35-year record. For each available year, a spectra-based clustering algorithm is used to differentiate water from ice during springtime meltout and is overlain on a common lake shoreline template to determine the percentage of ice covering each lake. Analysis of these 'e-cover ratios' for each scene reveals that there is pronounced interannual variation in the timing of lake ice meltout. The spatial pattern consistently demonstrates an increase in the percentage of ice coverage on lakes further north, reflecting the regional climatic gradient. However, the ice cover on many lakes near the northeastern coast persists for a substantially longer period into summer due to cooler temperatures associated with onshore winds from the Beaufort Sea. A similar maritime effect is not observed along the Chukchi Sea, and lake ice meltout is not delayed along this littoral zone.

ABSTRACTDetailed bathymetric data were collected for 28 thermokarst lakes across the Arctic Coastal Plain (ACP) of northern Alaska from areas with distinctly different surficial sediments and topography. Lakes found in the low‐relief coastal area have developed in marine silts that are ice‐rich in the upper 6–10 m. The lakes tend to be shallow (~ 2 m), of uniform depth and lack prominent littoral shelves. Further inland on the ACP, lakes have formed in relatively ice‐poor aeolian sand deposits. In this hilly terrain, average lake depth is less (~ 1 m) despite deeper (3–5 m) central pools. This bathymetry reflects the influence of broad, shallow littoral shelves where sand, eroded from bluffs at the lake margin, is deposited concurrently with deep penetration of the talik beneath the basin centre. Lakes in the ACP‐Arctic Foothills transition zone to the south have developed in loess uplands. These yedoma deposits are extremely ice‐rich, and residual lakes found inside old lake basins (alases) are generally 2–4 m deep, reflecting continued talik development and ground subsidence following drainage of the original lake. However, where the expanding lake encroaches on the flanks of the upland at actively eroding bluffs, near‐shore pools develop that can be 6–9 m deep. It appears that thawing of ice‐rich permafrost during lake expansion causes ground subsidence and formation of deep pools above ablating ice wedges. These data suggest that thermokarst lake morphometry largely depends on the characteristics of the substrate beneath the lake and the availability of sediments eroded at the lake margin. Copyright © 2012 John Wiley & Sons, Ltd.

ABSTRACTIn summer 2010, water temperature profile measurements were made in 12 thermokarst lakes along a 150‐km long north–south transect across the Arctic Coastal Plain of northern Alaska. In shallow lakes, gradual warming of the water column to 1–4°C begins at the lake bed during decay of the ice cover in spring. Rapid warming follows ice‐off, with water temperature responding synchronously to synoptic weather variations across the area. Regionally, ice‐off occurs 2–4 weeks later on lakes near the coast. Inland lakes are warmer (13°C) in mid‐summer than those near the coast (7°C), reflecting the regional climate gradient and the maritime effect. All lakes are well mixed and largely isothermal, with some thermal stratification (< 2°C) occurring during calm, sunny periods in deeper lakes. In deep (6–9 m) lake‐bed depressions that are likely ice‐wedge troughs, water cools by conduction to the colder sediments below, while concurrent warming occurs in the upper water column. A spatially dense sample of near‐surface temperature measurements was collected from one lake over a short period and shows warmer (2–3°C) temperatures on the upwind, sheltered end of the lake. This study demonstrates that climatic gradients, meteorological conditions and basin characteristics impact lake temperature dynamics. Copyright © 2012 John Wiley & Sons, Ltd.

Forest fires in Alaska and western Canada represent important sources of aerosols and trace gases in North America. Among the largest uncertainties when modeling forest fire effects are the timing and injection height of biomass burning emissions. Here we simulate CO and aerosols over North America during the 2004 fire season, using the GEOS-Chem chemical transport model. We apply different temporal distributions and injection height profiles to the biomass burning emissions, and compare model results with satellite-, aircraft-, and ground-based measurements. We find that averaged over the fire season, the use of finer temporal resolved biomass burning emissions usually decreases CO and aerosol concentrations near the fire source region, and often enhances long-range transport. Among the individual temporal constraints, switching from monthly to 8-day time intervals for emissions has the largest effect on CO and aerosol distributions, and shows better agreement with measured day-to-day variability. Injection height substantially modifies the surface concentrations and vertical profiles of pollutants near the source region. Compared with CO, the simulation of black carbon aerosol is more sensitive to the temporal and injection height distribution of emissions. The use of MISR- derived injection heights improves agreement with surface aerosol measurements near the fire source. Our results indicate that the discrepancies between model simulations and MOPITT CO measurements near the Hudson Bay can not be attributed solely to the representation of injection height within the model. Frequent occurrence of strong convection in North America during summer tends to limit the influence of injection height parameterizations of fire emissions in Alaska and western Canada with respect to CO and aerosol distributions over eastern North America.