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Agricultural, Climate, and Water Management Data for Australia’s Murray–Darling Basin

Agricultural, Climate, and Water Management Data for Australia’s Murray–Darling Basin

carol.reyes.dulong
Open Dataset
Creators: Will Rafey, UCLA Department of Economics
Publication Date: 2023-01-18
Creators: Will Rafey, UCLA Department of Economics

This dataset collection compiles key information on agriculture, climate, and water resource management in Australia’s Murray–Darling Basin. It brings together information from multiple sources, including ABARES, the Bureau of Meteorology (BoM), and the Australian Water Markets Report (AWMR). The collection includes crop calendars and coefficients, irrigation production estimates (GVIAP), monthly climate indicators such as rainfall and evapotranspiration, and economic data on water prices and allocations. Geospatial boundary files and supporting metadata are also provided to enable spatial and temporal analysis. The collection supports research on agricultural planning, water use efficiency, and environmental policy in the basin.

Geospatial and Environmental Exposure Data for U.S. Census-Based Analysis (2000–2016)

Geospatial and Environmental Exposure Data for U.S. Census-Based Analysis (2000–2016)

carol.reyes.dulong
Open Dataset
Creators: Janet Currie, Princeton University; John Voorheis, United States Census Bureau; Reed Walker, University of California-Berkeley
Publication Date: 2022-12-20
Creators: Janet Currie, Princeton University; John Voorheis, United States Census Bureau; Reed Walker, University of California-Berkeley

This dataset collection contains publicly available geospatial, environmental, and demographic data used to examine the relationship between PM2.5 exposure and population characteristics across the United States from 2000 to 2016. It includes annual satellite-based and monitor-based PM2.5 estimates (Di et al., EPA, van Donkelaar), county-level nonattainment status under the Clean Air Act, and geographic boundary files for U.S. states, census blocks, and commuting zones. Demographic data at the tract and block level are provided via IPUMS NHGIS and the U.S. Census Bureau. These files are designed for spatial matching, environmental exposure assignment, and policy-related research on air quality and health disparities.

Environmental and Socioeconomic Indicators across Indian Districts

Environmental and Socioeconomic Indicators across Indian Districts

carol.reyes.dulong
Open Dataset
Creators: Eyal G. Frank, University of Chicago. Harris School of Public Policy; Anant Sudarshan, University of Warwick: Department of Economics
Publication Date: 2024-06-26
Creators: Eyal G. Frank, University of Chicago. Harris School of Public Policy; Anant Sudarshan, University of Warwick: Department of Economics

This dataset collection brings together harmonized data on environmental, demographic, agricultural, health, and geographic characteristics across India. It includes district- and state-level information on bird habitat overlaps, pharmaceutical sales, livestock counts, water quality, weather patterns, and medical infrastructure, alongside population census data from multiple years. The files also incorporate geographic shapefiles, administrative boundary keys, and classifications such as coastal districts. Together, these files provide a structured, multi-dimensional view of India’s social and ecological landscape across time and space.

USGS Earth Explorer

USGS Earth Explorer

jona.frroku
Open Dataset
Creators: U.S. Geological Survey (USGS)
Publication Date: 1972
Creators: U.S. Geological Survey (USGS)

USGS Earth Explorer is a powerful search platform that provides free access to satellite imagery, aerial photography, and remote sensing data. With its extensive archive, the Earth Explorer offers data from various satellites like Landsat, Sentinel, and ASTER. The platform’s extensive archive encompasses data from multiple satellite missions, with each mission contributing a significant volume of data. For instance, Landsat 9 alone collects up to 750 scenes per day, and together with Landsat 8, they add nearly 1,500 new scenes daily to the USGS archive. Given that each Landsat scene is approximately 1 GB in size, the daily data addition from these two satellites alone can be estimated at around 1.5 TB. The number of observations within Earth Explorer is continually increasing as satellites like Landsat 8 and 9 are operational and consistently capturing data. Landsat 9, for example, collects as many as 750 scenes per day, and together with Landsat 8, they add nearly 1,500 new scenes daily to the USGS archive. The temporal coverage of datasets accessible via Earth Explorer varies depending on the specific mission or dataset. For instance, the Landsat program offers a historical archive dating back to 1972, providing over five decades of Earth observation data. Structurally, Earth Explorer organizes its datasets based on the source and type of data. For example, Landsat data is categorized by satellite and processing level, including Level-1 and Level-2 products, with varying spatial resolutions. Similarly, other datasets are organized according to their respective missions and data characteristics, allowing users to efficiently locate and utilize the data relevant to their specific needs.

ESA’s Sentinel Data

ESA’s Sentinel Data

jona.frroku
Open Dataset
Creators: European Space Agency (ESA)
Publication Date: 2014
Creators: European Space Agency (ESA)

The Sentinel satellite constellation provides Earth observation data under the Copernicus program, offering free and open access to a wide range of environmental information. The data covers various spectral, spatial, and temporal scales, enabling applications in environmental monitoring, land-use change, climate research, disaster management, and ocean observation. Sentinel-1 is equipped with C-band Synthetic Aperture Radar (SAR) that provides all-weather, day-and-night radar imagery, making it particularly useful for monitoring land and ocean surfaces, including applications like mapping, forestry, soil moisture estimation, and sea-ice observations. Sentinel-2 features a multispectral optical sensor capturing 13 spectral bands, offering high-resolution imagery (up to 10 meters), which is ideal for land cover classification, agricultural monitoring, and disaster management. Sentinel-3 carries multiple instruments to measure sea-surface topography, sea and land surface temperature, and ocean and land color, supporting ocean forecasting, environmental and climate monitoring, and land-use change detection. The data volume varies depending on the specific mission and product type. Sentinel-1 data files range from 1 GB to 6 GB per scene, depending on the observation mode and product type. Sentinel-2 Level-1C products, which cover a 100×100 km area, range from approximately 500 MB to 1 GB. Sentinel-3 product sizes vary widely depending on the instrument and processing level, ranging from several megabytes to over a gigabyte per product. The number of observations is continually increasing as the satellites remain operational and continuously capture data. Sentinel-1 revisits each region every 6 to 12 days, depending on the observation mode. Sentinel-2 provides global coverage of land surfaces every 5 days with its two satellites, Sentinel-2A and Sentinel-2B. Sentinel-3 offers a near-daily revisit for optical instruments, with shorter revisit times for altimetry measurements. Sentinel-1A was launched in April 2014, followed by Sentinel-1B in April 2016, and Sentinel-1C in December 2024. Sentinel-2A was launched in June 2015, Sentinel-2B in March 2017, and Sentinel-2C in September 2024. Sentinel-3A was launched in February 2016, and Sentinel-3B followed in April 2018.

NOAA (National Oceanic and Atmospheric Administration) Class

NOAA (National Oceanic and Atmospheric Administration) Class

jona.frroku
Open Dataset
Creators: National Oceanic and Atmospheric Administration (NOAA)
Publication Date: 1970
Creators: National Oceanic and Atmospheric Administration (NOAA)

NOAA’s CLASS (Comprehensive Large Array-data Stewardship System) is a web-based data repository that archives and distributes environmental data collected by various NOAA satellites and missions. CLASS provides access to a variety of data types, including:Environmental satellite data, weather data, other datasets. CLASS archives data from various NOAA satellite missions and instruments, including the Advanced Very High Resolution Radiometer (AVHRR), which captures global cloud cover, sea surface temperatures, and vegetation indices; the Geostationary Operational Environmental Satellites (GOES), which provide real-time weather monitoring and forecasting data; and the Joint Polar Satellite System (JPSS), which offers global environmental data for weather forecasting and climate monitoring. A key feature of CLASS is its role in long-term data preservation, ensuring that environmental information remains accessible for climate research and historical analyses. The system also provides user-friendly access, offering search and retrieval capabilities that allow users to locate and download specific datasets efficiently. The temporal coverage of datasets within CLASS varies by instrument and mission. AVHRR data is available from the late 1970s to the present, GOES data coverage starts from the 1970s and continues to current operations, and JPSS data has been available since 2011.

Sentinel Hub

Sentinel Hub

jona.frroku
Open Dataset
Creators: Sinergise
Publication Date: 1970
Creators: Sinergise

Sentinel Hub provides access to satellite imagery from various missions, including Sentinel-1, Sentinel-2, and Landsat satellites. It offers tools for visualizing, analyzing, and processing satellite data. Sentinel Hub provides access to a wide array of satellite imagery, including data from the Copernicus Sentinel missions (e.g., Sentinel-1, Sentinel-2), Landsat series, and commercial providers like PlanetScope. This extensive dataset supports diverse applications such as agriculture, forestry, land monitoring, and emergency response. The platform offers on-the-fly processing capabilities, allowing users to perform complex analyses without the need for local computational resources. This feature streamlines workflows and accelerates data processing tasks. Users can create custom processing scripts using Sentinel Hub’s scripting language, enabling tailored data analyses and visualization outputs to meet specific project requirements. Sentinel Hub provides access to historical satellite imagery dating back to the launch dates of respective missions. For instance, Sentinel-2 data is available from 2015 onwards, enabling users to analyze changes over the past decade.

Planet Labs

Planet Labs

jona.frroku
Open Dataset
Creators: Planet Labs Inc.
Publication Date: 2014
Creators: Planet Labs Inc.

Planet Labs offers high-resolution satellite imagery from its fleet of small satellites (Dove and SkySat). The platform provides access to detailed and frequent imagery for various applications such as monitoring and analysis. The satellites collect data across multiple spectral bands, including Red, Green, Blue, and Near-Infrared (NIR), facilitating diverse analyses such as vegetation health assessment and land cover classification. The constellation’s design allows for frequent revisits, with PlanetScope achieving near-daily coverage and SkySat capable of sub-daily tasking, essential for applications requiring up-to-date information. Planet Labs collects imagery covering up to 300 million square kilometers daily, resulting in a vast number of observations over time. PlanetScope imagery dates back to 2014, with 8-band data available from 2020. The RapidEye constellation, acquired by Planet Labs, provided imagery from 2009 until its retirement in 2020. In total, the dataset has data in a size exceeding 10 PB. Planet Labs’ dataset covers several sub-datasets, each corresponding to different satellite constellations and imaging capabilities:​

  • PlanetScope: Consists of hundreds of small satellites capturing imagery at approximately 3.7-meter resolution across four multispectral bands (Red, Green, Blue, NIR). This dataset supports applications like agricultural monitoring, forest management, and environmental assessment. ​

  • SkySat: Comprises around 15 satellites providing high-resolution imagery at 50-centimeter resolution, with capabilities for sub-daily tasking. SkySat data is valuable for detailed analyses, including infrastructure monitoring and urban planning. ​

  • RapidEye (Retired): Included five satellites that operated from 2009 to 2020, delivering 5-meter resolution imagery across five spectral bands (Blue, Green, Red, Red Edge, NIR). RapidEye data was utilized for applications such as land use mapping and crop monitoring

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