PhenoCam images from ARSLTARMDCR site, Caroline County, Maryland, USA since 2017
This data set consists of repeat digital imagery from a tower-mounted digital camera (hereafter, PhenoCam) maintained by the USDA-ARS Hydrology Remote Sensing Laboratory (HRSL) in the Lower Chesapeake Bay (LCB) watershed. HRSL is a member of the PhenoCam network, which has as its mission to serve as a long-term, continental-scale, phenological observatory. Imagery is uploaded to the PhenoCam server every 30 minutes.
PhenoCam images from ARSOPE3LTAR site, Beltsville Agricultural Research Center, Maryland, USA since 2017
This data set consists of repeat digital imagery from a tower-mounted digital camera (hereafter, PhenoCam) maintained by the USDA-ARS Hydrology Remote Sensing Laboratory (HRSL) in the Lower Chesapeake Bay (LCB) watershed. HRSL is a member of the PhenoCam network, which has as its mission to serve as a long-term, continental-scale, phenological observatory. Imagery is uploaded to the PhenoCam server every 30 minutes.
Gridded 20-Year Parameterization of a Stochastic Weather Generator (CLIGEN) for South American and African Continents at 0.25 Arc Degree Resolution
CLImate GENerator (CLIGEN) is a stochastic weather generator that produces daily and sub-daily timeseries of weather variables. The resulting timeseries are statistically similar to observed timeseries considering various temporal scales and climate factors. This dataset consisting of CLIGEN inputs may be used to generate timeseries at any point in a 0.25 arc degree resolution grid covering South American and African continents.
Agricultural land use by field: Upper Mississippi River Basin 2010-2020
This database is structured around individual farm fields as the unit of record, providing a framework that enables land use to be assessed at the same scale that agricultural land uses shift, at an annual time step, and at the scale at which conservation practices are implemented. It is beneficial to document agricultural land cover and its rates of change to understand responses of watershed, landscape, and agroecosystem processes to changes in land use and to identify viable approaches that can be customized for local adoption and mitigate environmental impacts from agricultural production.
Agricultural land use by field: Nebraska 2010-2020
This database is structured around individual farm fields as the unit of record, providing a framework that enables land use to be assessed at the same scale that agricultural land uses shift, at an annual time step, and at the scale at which conservation practices are implemented. It is beneficial to document agricultural land cover and its rates of change to understand responses of watershed, landscape, and agroecosystem processes to changes in land use and to identify viable approaches that can be customized for local adoption and mitigate environmental impacts from agricultural production.
Agricultural land use by field: Illinois 2010-2020
This database is structured around individual farm fields as the unit of record, providing a framework that enables land use to be assessed at the same scale that agricultural land uses shift, at an annual time step, and at the scale at which conservation practices are implemented. It is beneficial to document agricultural land cover and its rates of change to understand responses of watershed, landscape, and agroecosystem processes to changes in land use and to identify viable approaches that can be customized for local adoption and mitigate environmental impacts from agricultural production.
Agricultural land use by field: Wisconsin 2010-2019
This database is structured around individual farm fields as the unit of record, providing a framework that enables land use to be assessed at the same scale that agricultural land uses shift, at an annual time step, and at the scale at which conservation practices are implemented. It is beneficial to document agricultural land cover and its rates of change to understand responses of watershed, landscape, and agroecosystem processes to changes in land use and to identify viable approaches that can be customized for local adoption and mitigate environmental impacts from agricultural production.
Agricultural land use by field: Minnesota 2010-2019
This database is structured around individual farm fields as the unit of record, providing a framework that enables land use to be assessed at the same scale that agricultural land uses shift, at an annual time step, and at the scale at which conservation practices are implemented. It is beneficial to document agricultural land cover and its rates of change to understand responses of watershed, landscape, and agroecosystem processes to changes in land use and to identify viable approaches that can be customized for local adoption and mitigate environmental impacts from agricultural production.