Racial, Ethnic, and Socioeconomic Disparities in Multiple Measures of Blue and Green Spaces in the United States

Environmental Health Perspectives, Год журнала: 2023, Номер 131(1)

Опубликована: Янв. 1, 2023

BACKGROUND: Several studies have evaluated whether the distribution of natural environments differs between marginalized and privileged neighborhoods.However, most restricted their analyses to a single or handful cities used different environment measures.OBJECTIVES: We are inequitably distributed based on socioeconomic status (SES) race/ethnicity in contiguous United States.METHODS: obtained SES data (2015-2019) for all U.S. Census tracts.For each tract, we calculated Normalized Different Vegetation Index (NDVI) 2020, NatureScore (a proprietary measure quantity quality elements) 2019, park cover blue space 1984-2018.We generalized additive models with adjustment potential confounders spatial autocorrelation evaluate associations NDVI, NatureScore, cover, odds containing tracts (n = 71,532) urban 45,338).To compare effect estimates, standardized so that beta coefficients presented percentage increase decrease standard deviation (SD).RESULTS: Tracts higher had space.For example, highest median household income quintile NDVI [44.8% SD (95% CI: 42.8, 46.8)] [16.2% 13.5, 19.0)] compared lowest quintile.Across tracts, lower non-Hispanic White individuals Hispanic were associated NatureScore.In observed weak positive Black cover; did not find any clear Hispanics.

Язык: Английский

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Need and vision for global medium-resolution Landsat and Sentinel-2 data products

Remote Sensing of Environment, Год журнала: 2023, Номер 300, С. 113918 - 113918

Опубликована: Ноя. 27, 2023

Язык: Английский

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Thematic accuracy assessment of the NLCD 2019 land cover for the conterminous United States

GIScience & Remote Sensing, Год журнала: 2023, Номер 60(1)

Опубликована: Март 1, 2023

The National Land Cover Database (NLCD), a product suite produced through the MultiResolution Characteristics (MRLC) consortium, is an operational land cover monitoring program. Starting from base year of 2001, NLCD releases database every 2-3-years. recent release NLCD2019 extends to 18 years. We implemented stratified random sample collect reference data for 2016 and 2019 components at Level II I classification hierarchy. For both dates, overall accuracies (OA) were 77.5% ± 1% (± value standard error) when agreement was defined as match between map label primary only, increased 87.1% 0.7% either or alternate label. At hierarchy, OA 83.1% 0.9% 90.3% also included in 5% higher compared component NLCD2016 only. No improvement realized by User's (UA) forest loss grass gain were>70% label, UA generally<50% all other change themes. Producer's (PA) water conducted post-analysis review map-reference identify patterns disagreement, these findings are discussed context potential adjustments mapping collection procedures that may lead improved accuracy going forward.

Язык: Английский

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High-frequency time series comparison of Sentinel-1 and Sentinel-2 satellites for mapping open and vegetated water across the United States (2017–2021)

Remote Sensing of Environment, Год журнала: 2023, Номер 288, С. 113498 - 113498

Опубликована: Фев. 15, 2023

Frequent observations of surface water at fine spatial scales will provide critical data to support the management aquatic habitat, flood risk and quality. Sentinel-1 Sentinel-2 satellites can such observations, but algorithms are still needed that perform well across diverse climate vegetation conditions. We developed inundation for Sentinel-2, respectively, 12 sites conterminous United States (CONUS), covering a total >536,000 km2 representing hydrologic landscapes. Each scene in 5-year (2017–2021) time series was classified into open water, vegetated non-water 20 m resolution using variables from as derived topographic weather datasets. The algorithm distinct model explore if where two could potentially be integrated single high-frequency series. Within each model, (vegetated palustrine, lacustrine, riverine wetlands) classes were mapped. models validated imagery WorldView PlanetScope. Classification accuracy high period, with an omission commission error only 3.1% 0.9% 0.5% algorithm, respectively. Vegetated lower, expected given class represents mixed pixels. showed higher (10.7% 7.9% error) relative (28.4% 16.0% error). Patterns over proportion area mapped or by charted correlated subset all sites. Our results improve temporal resolution, sensor-specific differences, sensitivity structure versus pixel color, complicate integration mixed-pixel, water. methods here 5-day (Sentinel-2 algorithm) 12-day (Sentinel-1 steps our understanding short- long-term response land use drivers different ecoregions.

Язык: Английский

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Combining expert and crowd-sourced training data to map urban form and functions for the continental US

Scientific Data, Год журнала: 2020, Номер 7(1)

Опубликована: Авг. 11, 2020

Abstract Although continental urban areas are relatively small, they major drivers of environmental change at local, regional and global scales. Moreover, especially vulnerable to these changes owing the concentration population their exposure a range hydro-meteorological hazards, emphasizing need for spatially detailed information on urbanized landscapes. These data be consistent in content scale provide holistic description layouts address different user needs. Here, we map United States into Local Climate Zone (LCZ) types 100 m spatial resolution using expert crowd-sourced information. There 10 LCZ types, each associated with set relevant variables such that represents valuable database properties. benchmarked against continental-wide existing novel geographic databases form. We anticipate dataset provided here will useful researchers practitioners assess how configuration, size, shape cities impact important human outcomes.

Язык: Английский

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The Boreal–Arctic Wetland and Lake Dataset (BAWLD)

Earth system science data, Год журнала: 2021, Номер 13(11), С. 5127 - 5149

Опубликована: Ноя. 5, 2021

Abstract. Methane emissions from boreal and arctic wetlands, lakes, rivers are expected to increase in response warming associated permafrost thaw. However, the lack of appropriate land cover datasets for scaling field-measured methane circumpolar scales has contributed a large uncertainty our understanding present-day future emissions. Here we present Boreal–Arctic Wetland Lake Dataset (BAWLD), dataset based on an expert assessment, extrapolated using random forest modelling available spatial climate, topography, soils, conditions, vegetation, surface water extents dynamics. In BAWLD, estimate fractional coverage five wetland, seven lake, three river classes within 0.5 × 0.5∘ grid cells that northern tundra biomes (17 % global surface). Land were defined criteria ensured distinct among classes, as indicated by co-developed comprehensive flux observations. wetlands occupied 3.2 106 km2 (14 domain) with 95 confidence interval between 2.8 3.8 km2. Bog, fen, bog most abundant wetland covering ∼ 28 each total area, while highest-methane-emitting marsh 5 12 %, respectively. Lakes, include all lentic open-water ecosystems regardless size, covered 1.4 (6 domain). Low-methane-emitting lakes (>10 km2) glacial jointly represented 78 lake high-emitting peatland yedoma 18 4 Small (<0.1 glacial, peatland, combined 17 area but disproportionally overall 0.15 0.38 Rivers streams estimated 0.12 (0.5 domain), which 8 was high-methane-emitting headwaters drain organic-rich landscapes. Distinct combinations spatially co-occurring identified across BAWLD domain, allowing mapping “wetscapes” have characteristic emission magnitudes sensitivities climate change at regional scales. With provide avoids double-accounting includes intervals class. As such, will be suitable many hydrological biogeochemical upscaling efforts region, particular those aimed improving assessments current Data freely https://doi.org/10.18739/A2C824F9X (Olefeldt et al., 2021).

Язык: Английский

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Smokey the Beaver: beaver‐dammed riparian corridors stay green during wildfire throughout the western United States

Ecological Applications, Год журнала: 2020, Номер 30(8)

Опубликована: Сен. 3, 2020

Beaver dams are gaining popularity as a low-tech, low-cost strategy to build climate resiliency at the landscape scale. They slow and store water that can be accessed by riparian vegetation during dry periods, effectively protecting ecosystems from droughts. Whether or not this protection extends wildfire has been discussed anecdotally but examined in scientific context. We used remotely sensed Normalized Difference Vegetation Index (NDVI) data compare greenness areas with without beaver damming wildfire. include five large wildfires of varying burn severity dominant landcover settings western United States our analysis. found beaver-dammed corridors relatively unaffected when compared similar damming. On average, decrease NDVI fire is 3.05 times it beaver. However, plant rebounded year after regardless activity. Thus, we conclude that, while activity does necessarily play role post-fire resilience, significant resistance refugia creation.

Язык: Английский

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Mapping twenty years of corn and soybean across the US Midwest using the Landsat archive

Scientific Data, Год журнала: 2020, Номер 7(1)

Опубликована: Сен. 15, 2020

Field-level monitoring of crop types in the United States via Cropland Data Layer (CDL) has played an important role improving production forecasts and enabling large-scale study agricultural inputs outcomes. Although CDL offers type maps across conterminous US from 2008 onward, such are missing many Midwestern states or uneven quality before 2008. To fill these data gaps, we used now-public Landsat archive cloud computing services to map corn soybean at 30 m resolution Midwest 1999-2018. Our training were 2008-2018, validated predictions on 1999-2007 where available, county-level acreage statistics, state-level rotation statistics. The corn-soybean maps, which call Corn-Soy (CSDL), publicly hosted Google Earth Engine also available for download online.

Язык: Английский

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Driving Factors and Future Prediction of Land Use and Cover Change Based on Satellite Remote Sensing Data by the LCM Model: A Case Study from Gansu Province, China

Sensors, Год журнала: 2020, Номер 20(10), С. 2757 - 2757

Опубликована: Май 12, 2020

Land use and cover change (LUCC) is an important issue affecting the global environment, climate change, sustainable development. Detecting predicting LUCC, a dynamic process, its driving factors will help in formulating effective land planning policy suitable for local conditions, thus supporting socioeconomic development environmental protection. In this study, taking Gansu Province as case study example, we explored LUCC pattern mechanism from 1980 to 2018, predicted 2030 using integrated LCM (Logistic-Cellular Automata-Markov chain) model data satellite remote sensing. The results suggest that was more reasonable second stage (2005 2018) compared with first (1980 2005). This because large area of green lands protected by ecological engineering stage. From general, natural were main force influencing changes Gansu, while effects not significant slow economy. Landscape indices analysis indicated under protection scenario would be favorable than historical trend scenario. Besides, present suggested arid semiarid could well detected model. hopefully provide theoretical instructions future management, new methodology reference regions.

Язык: Английский

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Validation of baseline and modified Sentinel-2 Level 2 Prototype Processor leaf area index retrievals over the United States

ISPRS Journal of Photogrammetry and Remote Sensing, Год журнала: 2021, Номер 175, С. 71 - 87

Опубликована: Март 14, 2021

The Sentinel-2 Level 2 Prototype Processor (SL2P) is made available to users for the retrieval of vegetation biophysical variables including leaf area index (LAI) from Multispectral Instrument (MSI) data within Sentinel Application Platform (SNAP). A limited number validation exercises have indicated SL2P LAI retrievals frequently meet user requirements over agricultural environments, but perform comparatively poorly heterogeneous canopies such as forests. Recently, a modified version was developed, using directional scattering factor (DASF) constrain an alternative regularisation (SL2P-D). Whilst makes use prior information on expected canopy conditions, SL2P-D trained uniform distributions input parameters define radiative transfer model (RTM) simulations. Using in situ measurements through Copernicus Ground Based Observations Validation (GBOV) service, we performed extensive and 19 sites throughout United States. For effective (LAIe), demonstrated good overall performance (RMSD = 0.50, NRMSD 31%, bias −0.10), with all meeting Sentinels Science (SEN4SCI) uncertainty homogeneous (cultivated crops, grasslands, pasture/hay shrub/scrub), whilst underestimation occurred (deciduous forest, evergreen mixed woody wetlands). reduced bias, slightly improving when compared 0.48, 30%, −0.05), indicating its approach appears offer some advantages information, especially at LAIe > 3. Additionally, resulted 32% more valid than SL2P, largest differences observed < 1. against opposed yielded similar patterns poorer 1.08 1.13, 49% 52%, −0.64 −0.68) because RTM used by does not account foliage clumping. In addition themselves, examined relationship between predicted uncertainties retrieved LAI. With respect LAIe, SL2P's were conservative, underestimating only 35% cases, those unbiased.

Язык: Английский

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