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10 results for “Greening trends”
Beyond 'greening' and 'browning': trends in grassland ground cover fractions across Eurasia that account for spatial and temporal autocorrelation
<p class="MsoNormal">Grassland ecosystems cover up to 40% of the global land area and provide many ecosystem services directly supporting the livelihoods of over 1 billion people. Monitoring long‑term changes in grasslands is crucial for food security, biodiversity conservation, achieving Land Degradation Neutrality goals, and modelling the global carbon budget. Although long-term grassland monitoring using remote sensing is extensive, it is typically based on a single vegetation index and does not account for temporal and spatial autocorrelation, which means that some trends are falsely identified while others are missed. Our goal was to analyze trends in grasslands in Eurasia, the largest continuous grassland ecosystems on Earth. To do so, we calculated Cumulative Endmember Fractions (annual sums of monthly ground cover fractions) derived from MODIS 2002–2020 time series and applied a new statistical approach PARTS that explicitly accounts for temporal and spatial autocorrelation in trends. We examined trends in green vegetation, non-photosynthetic vegetation, and soil ground cover fractions considering their independent change trajectories and relations among fractions over time. We derived temporally-uncorrelated pixel-based trend maps and statistically tested whether observed trends could be explained by elevation, land cover, SPEI3, climate, country, and their combinations, all while accounting for spatial autocorrelation. We found no statistical evidence for a decrease in vegetation cover in grasslands in Eurasia. Instead, there was a significant map-level increase in non‑photosynthetic vegetation across the region and local increases in green vegetation with a concomitant decrease in soil fraction. Independent environmental variables affected trends significantly, but effects varied by region. Overall, our analyses show in a statistically robust manner that Eurasian grasslands have changed considerably over the past two decades. Our approach enhances remote‑sensing‑based monitoring of trends in grasslands so that underlying processes can be discerned.</p>
Data for "False trends in Landsat-based vegetation greenness due to increased image availability over time"
<p>Raster data used in this following paper : "False trends in Landsat-based vegetation greenness due to increased image availability over time". The dataset includes observed greening trends for the European Alps, and sum of observations in the european alps and the arctic.</p>
Data from: Landsat-based greening trends in alpine ecosystems are inflated by multidecadal increases in summer observations
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Beyond ‘greening’ and ‘browning’: trends in grassland ground cover fractions across Eurasia that account for spatial and temporal autocorrelation
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Soil moisture and GPP trends across the Avocado "Green Gold" Belt in central Mexico (2001-2018)
<p>Data processing in RStudio for soil moisture and Gross Primary Productivity trends across the Avocado “Green Gold” Belt in central Mexico (2001-2018).</p>
Data from: Grazing and climate interact to regulate greening trends in Mediterranean grasslands
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Greenness Trends and Carbon Stocks of Mangrove Forests Across Mexico, 2001-2015
This dataset provides estimates of greenness trends, above- and belowground carbon stocks, and climate variables of the persistent mangrove forests on the coasts of Mexico (PMFM) at a 1 km resolution from 2001 through 2015. Data are available as one-time estimates or across the temporal range; typically as monthly summaries. One-time estimates of aboveground carbon and soil organic carbon stocks for the PMFM derived from existing sources are provided. Also included are the monthly mean normalized difference vegetation index (NDVI) from MOD13A3 used to derive greenness trends, monthly mean air temperature, and total monthly precipitation from Daymet for 2001-2015 across the PMFM. Other files include the distribution and coverage of PMFM across Mexico. Distributions are provided as four categories of PMFM: (1) Arid mangroves with Surface Water as main input, along the Gulf of California and Pacific Coast (ARsw); (2) humid mangroves with surface water input along the Pacific Coast (HUsw-Pa); (3) humid mangroves with surface water input along the coast of the Gulf of Mexico (HUsw-Gf); (4) humid mangroves with groundwater input along the Gulf of Mexico and Caribbean Sea (HUgw). These data provide a baseline for national monitoring programs, carbon accounting models, and greenness trends in coastal wetlands.
ABoVE: Lake Growing Season Green Surface Reflectance Trends, AK and Canada, 1984-2019
This dataset provides an annual time series of Landsat green surface reflectance and the derived annual trend during the growing season (June and July) for 472,890 lakes across the ABoVE Extended Study Domain from 1984 to 2019. The reflectance data are from Landsat-5, Landsat-7, and Landsat-8 sensors for the green band (center wavelength 560 nm). Over 270,000 Landsat scenes were evaluated and quality assured to be cloud-free and over water. Lakes were selected from HydroLAKES, a global database of lakes of at least 10 ha. Lake surface reflectance was extracted from a 3-by-3-pixel area centered on each lake centroid from the selected Landsat scenes determined from lake polygons. This dataset demonstrates changes in lake color over time in the arctic and boreal regions of North America. Color is relevant for understanding physical, ecological, and biogeochemical processes in some of the world’s highest concentrations of lakes where climate change may have significant impacts.
ABoVE: Landsat Vegetation Greenness Trends, Boreal Forest Biome, 1985-2019
This dataset provides information on interannual trends in annual maximum vegetation greenness from 1985 to 2019 for recently undisturbed areas in the boreal forest biome. Multi-decadal changes in remotely sensed vegetation greenness provide evidence of an emerging boreal biome shift driven by climate warming. Annual maximum vegetation greenness was assessed at about 100,000 random sample locations using an ensemble of spectral vegetation indices (NDVI, EVI2, kNDVI, and NIRv) derived from Landsat products. The dataset provides raster data summarizing vegetation greenness trends for sample locations stratified by Ecological Land Unit in GeoTIFF format. These raster data span the circum-hemispheric boreal forest biome between 45 to 70 degrees north at 300 m resolution. Estimates of uncertainty were generated using Monte Carlo simulations. Interannual trends in annual maximum vegetation greenness from 1985 to 2019 and 2000 to 2019 are provided for sample locations with adequate data for time series analysis; these data are in comma-separated values (CSV) format.
The Present and Future Trend of Green Credit: A Bibliometric Approach
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.