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Crop yield, soil data, pest surveillance, livestock, food composition, precision farming
17,770 datasets
NASA's dataset provides high-resolution (0.5m) estimates of tree canopy cover across the entire state of Vermont for the year 2016. The data was created using Object-Based Image Analysis (OBIA) techniques on remotely sensed imagery, followed by a detailed manual review at a 1:3000 scale to correct errors. This mapping was part of the Vermont High-Resolution Land Cover project.
Soil types are mapped globally at a 0.5-degree latitude by 0.5-degree longitude grid. The dataset contains 106 soil units derived from Zobler's 1986 assessment of the FAO/UNESCO Soil Map of the World. It was converted from a 1-degree resolution source by NASA and retains continent-specific soil property information.
1,125 homogenized soil profiles from three major institutions form a foundational resource for global modeling. Each georeferenced profile includes soil horizon data, classification under FAO-UNESCO legends, and analytical methods. This dataset underpinned the International Geosphere-Biosphere Programme's Global Pedon Database.
A 1-km resolution prototype dataset maps Amazonian vegetation as continuous fields, not discrete classes, using 1992-93 AVHRR data. Each pixel contains five percentage estimates for tree cover, leaf longevity, and leaf type, with values ranging from 10 to 80 percent. This approach captures variability and transition zones within the Large Scale Biosphere-Atmosphere Experiment in Amazonia study area.
A 450-km^2 study in the eastern Amazon combined field measurements and Landsat ETM+ satellite imagery to quantify forest canopy damage from selective logging. Reduced-impact logging caused consistently less canopy damage than conventional methods, with half of the canopy openings closing within one year of regrowth. This is the first regional-scale study to integrate field data, satellite observations, and spectral mixture models to track canopy recovery up to 3.5 years post-harvest.
586 paired fecal samples from healthy adults across multiple independent cohorts undergoing resistant starch dietary interventions. The dataset, authored by Biao Dong and last updated in May 2026, analyzes reproducible gut microbial responses and validates findings in inflammatory bowel disease populations. It includes differential abundance analysis, co-occurrence network results, and machine learning classification outcomes.
586 paired fecal samples from healthy adults across multiple independent cohorts undergoing resistant starch dietary interventions. The dataset, authored by Biao Dong and last updated in May 2026, analyzes gut microbiota composition to identify reproducible microbial responses and their potential clinical relevance in inflammatory bowel disease.
586 paired fecal samples from healthy adults across multiple independent cohorts show a consistent reduction in gut microbial alpha diversity with resistant starch supplementation. The data, processed through a unified bioinformatics pipeline, identifies 22 taxa consistently depleted, including putative immunostimulatory pathobionts like Ruminococcus gnavus. Author Biao Dong published this analysis on figshare under a CC-BY-4.0 license, with a last update in May 2026.
From 1986 to 1996, this dataset documents a long-term yield optimization experiment in an 8.25-hectare Norway spruce forest in northern Sweden. It contains stand characteristics, above- and below-ground biomass, and Net Primary Productivity (NPP) allocation data for both fertilized/irrigated and control plots, alongside climate data from 1991-1995. The data show that after ten years, volume growth in treated stands was almost four times that of the control, with total NPP in 1995 reaching 902 g/m²/year for treated stands versus 291 g/m²/year for controls.
Southern Africa's 1-km resolution vegetation data from 1992-93 estimates percent tree cover, leaf longevity, and leaf type as continuous fields, not discrete classes. Created by the University of Maryland's LGRSS using NOAA AVHRR data, this prototype dataset provides parameters for carbon cycle and land cover models. Each pixel value represents a percentage between 10 and 80 for five distinct vegetation characteristics.
Abdoul Kader Ilboudo's study provides linked human-animal data on Crimean-Congo hemorrhagic fever virus (CCHFV) exposure in rural Burkina Faso. The dataset includes serological results and associated factors for 717 livestock farmers and 2,295 animals (cattle, sheep, goats) from 149 households across 16 villages. It was last updated on 2026-05-04 and is available under a CC-BY-4.0 license.
Thirty groundwater samples from the Collo Plain in northeastern Algeria were analyzed for major physicochemical parameters. The data includes pH values from 6.90 to 7.90 and electrical conductivity from 1356 to 3388 μS/cm, used to compute a weighted Irrigation Water Quality Index (IWQI). Author Faouzi Zahi published the dataset on figshare in May 2026, integrating hydrochemical analysis with GIS and remote sensing.
Thirty groundwater samples from the Collo Plain in northeastern Algeria were analyzed for major physicochemical parameters to compute an Irrigation Water Quality Index (IWQI). The dataset includes IWQI values ranging from 35.5 to 87.9 and spatial distribution maps created using GIS and geostatistical interpolation. It was authored by Faouzi Zahi and last updated in May 2026.
Survey data from 11,437 community-dwelling Chinese adults aged 65 years and older, collected in 2018 via the Chinese Longitudinal Healthy Longevity Survey. The study, authored by Xixing Xu, investigates associations between flexitarian diets and neuropsychiatric outcomes like depression and cognitive impairment.
2019–2024 longitudinal data on 4,198 Salmonella isolates from cattle, pigs, chickens, and ducks in South Korea. The dataset includes serovar distribution, antimicrobial resistance profiles, and molecular characterization of colistin resistance genes. It was authored by Md. Sekendar Ali and shared on figshare in 2026.
524 patients from a two-center retrospective cohort study (2020–2023) were analyzed by Wenjie Chen. The dataset supports research on the Triglyceride-Cholesterol-Body Weight Index (TCBI) and its association with stroke-heart syndrome and 90-day functional outcomes after endovascular treatment.
A 54.5 KB document by Nan Cong describes a method for identifying tea plantations using Sentinel-1 radar and Sentinel-2 optical satellite imagery. The study quantitatively identified April as the optimal temporal window for discriminating tea trees from spectrally similar vegetation like rubber and natural forests. Model optimization improved classification accuracy from 87.1% to 89.1%.
47 peer-reviewed studies on produce washing, covering 23 produce items and 79 pesticides, were analyzed. The dataset contains 1,100 individual reduction-efficacy data points for four washing methods: rinsing with tap water, soaking in tap water, soaking in a baking soda solution, and soaking in vinegar/acetic acid. It was created by Dayna de Montagnac and last updated on 2026-04-30.
47 peer-reviewed studies provide data on the effectiveness of household washing methods for reducing pesticide residues on 23 produce items. The dataset includes 1,100 individual reduction-efficacy data points for rinsing with tap water, soaking in tap water, baking soda solution, and vinegar/acetic acid. Dayna de Montagnac compiled this scoping review, last updated in April 2026.
A scoping review dataset aggregating results from 47 peer-reviewed studies on the effectiveness of household methods for reducing pesticide residues on fruits and vegetables. The dataset includes 1,100 individual reduction-efficacy data points across four washing methods: rinsing with tap water, soaking in tap water, soaking in baking soda solution, and soaking in vinegar or acetic acid. It was authored by Dayna de Montagnac and last updated on 2026-04-30.