Loading...
Loading...
Cell biology, microbiology, ecology, biodiversity, species data, evolutionary biology
24,520 datasets
State-wide vegetation cover datasets classify perennial woody vegetation from Landsat imagery at 30-meter resolution. Produced annually by Landgate, the data spans from 1988 to the present and distinguishes between forest and sparse woody vegetation categories based on cover density and height.
State-wide vegetation cover datasets of perennial woody vegetation based on Landsat imagery (30m ground pixel) are produced annually with data starting in 1988 to current. The classification of woody perennial vegetation is provided in two classes, one forest category meeting the vegetation structural requirement for 20% cover density and 2m height at maturity, and a sparse woody vegetation category identifying areas with 5- 20% vegetation cover.
Western Australia's state-wide vegetation cover dataset provides annual classifications of perennial woody vegetation from 1988 onward, derived from Landsat imagery with 30-meter ground pixels. Landgate produces the data, classifying vegetation into forest and sparse woody categories based on cover density and height thresholds.
Western Australia's state-wide vegetation cover data classifies perennial woody vegetation from annual Landsat imagery starting in 1988. The dataset provides two structural classes: forest meeting 20% cover density and 2m height, and sparse woody vegetation with 5-20% cover. It is produced by Landgate and updated annually.
1988 to present annual state-wide datasets classify perennial woody vegetation from Landsat imagery at 30-meter resolution. The data provides two structural classes: forest meeting 20% cover density and 2m height, and sparse woody vegetation with 5-20% cover. Produced by Landgate, the series supports long-term land monitoring.
Vegetation Cover 2019 is a state-wide dataset classifying perennial woody vegetation from Landsat imagery. Landgate produced it, providing annual data from 1988 onward. The classification uses two structural categories based on cover density and height.
State-wide vegetation cover datasets classify perennial woody vegetation from Landsat imagery at 30-meter resolution. Produced annually by Landgate, the data series extends from 1988 to the present. The classification includes two categories: forest meeting structural requirements and sparse woody vegetation.
1988 to present annual state-wide datasets classify perennial woody vegetation from 30-meter Landsat imagery. Landgate produces two structural classes: forest meeting 20% cover and 2m height thresholds, and sparse woody vegetation with 5-20% cover.
ACTGOV Shrub Bed Assets is a polygon dataset showing the locations of shrub beds in the Australian Capital Territory. Assets are owned or managed by City Services and the Parks and Conservation Service. Attributes include location description, suburb, asset sub type, and landscaping details.
Landgate produces state-wide annual vegetation cover datasets for Western Australia from 1988 to present. The classification identifies perennial woody vegetation in two structural classes: forest meeting 20% cover density and 2m height, and sparse woody vegetation with 5-20% cover. Data is derived from 30-meter resolution Landsat imagery.
Australia is covered by this digital topographic map series at a scale of 1:250,000, comprising 516 standard and 50 special map sheets. The series, published by Geoscience Australia, shows natural and constructed features including roads, railways, vegetation, hydrography, and 50-meter contours. Data uses GDA94/GDA2020 datum, AHD height datum, and UTM projection, and was last updated in March 2026.
Sedimentological data reconstructs glaciological and oceanographic environmental changes off the George V Coast during the Late Pleistocene and Holocene. The dataset, hosted by Geoscience Australia, focuses on the evolution of a sediment drift deposit in a deep trough on the shelf. It was last updated on 2026-05-14.
Spatiotemporal analysis of bacterial communities in an anaerobic–anoxic–oxic (A2O) wastewater treatment plant in Tokyo and the receiving Tama River. The dataset includes 16S rRNA gene analysis and ion chromatography data used to monitor bacterial composition and nutrient concentrations across seasonal temperature variations. It was authored by Akifumi Nishida and last updated on 2026-04-15.
13.9 KB of ion chromatography data from a study investigating bacterial dynamics and nutrient removal in an anaerobic-anoxic-oxic (A2O) wastewater treatment plant in Tokyo. The dataset, authored by Akifumi Nishida and last updated in April 2026, was used to assess nutrient removal effectiveness across seasonal temperature variations and the impact of treated wastewater on the Tama River's bacterial communities. It likely contains measurements of nutrient concentrations like nitrate and ammonium.
Tokyo, Japan, is the geographic scope for this dataset of sampling site coordinates from a study on bacterial dynamics in an anaerobic–anoxic–oxic (A2O) wastewater treatment plant and the receiving Tama River. The dataset, 11.6 KB in size, was authored by Akifumi Nishida and last updated on April 15, 2026. It supports research on nutrient removal efficiency and the impact of treated wastewater on riverine bacterial communities.
Tokyo's A2O wastewater treatment plant data includes tank capacities and residence times, supporting a study of bacterial community dynamics and nutrient removal. The dataset is 9.1 KB in size, authored by Akifumi Nishida, and was last updated on April 15, 2026. The study used 16S rRNA gene analysis and ion chromatography to monitor bacterial composition and nutrient concentrations across seasonal temperature variations.
Canadian Food Inspection Agency analyzed 3,173 samples of chocolate-based confectionaries for Salmonella, total coliforms, and generic E. coli between April 2016 and March 2018. Salmonella and generic E. coli were not detected in any samples, while high coliform levels were found in 3 samples. The agency conducted follow-up inspections and sampling.
A targeted survey analyzed 59 samples of cold brewed coffee for bacterial pathogens. The Canadian Food Inspection Agency conducted the survey between April 1, 2018 and March 31, 2019, testing for Salmonella, E. coli O157, Aerobic Colony Count, and generic E. coli. No Salmonella, E. coli O157, or generic E. coli were detected, while Aerobic Colony Counts were found in 15 samples.
Cryo-EM maps and models and PDB validation reports for the eukaryotic RNase MRP ribonucleoprotein complex, authored by Ming Lei and released under CC-BY-4.0. The dataset is a 539.3 MB ZIP file last updated on May 19, 2026.
A collection of 139,231 wildlife images across 122 species and sub-species labels, aggregated from multiple online sources. The dataset was created by Horama and last updated on 2026-04-29. Images are stored in Parquet shards compatible with HuggingFace's Image feature for direct decoding.