RF-CLASS: Remote-sensing-based Flood Crop Loss Assessment Service System

The Remote-sensing-based Flood Crop Loss Assessment Service System (RF-CLASS) is an Earth Observation (EO) based flood crop loss assessment cyber-service system operated by the Center for Spatial Information Science and Systems (CSISS), George Mason University. RF-CLASS supports flood-related crop statistics and insurance decision-making.

Maps and Multimedia

Data from: Quality controlled research weather data – USDA-ARS, Bushland, Texas

The dataset contains 15-minute mean weather data from the USDA-ARS Conservation and Production Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU) research weather station, Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL) for all days in 2016. The data are from sensors deployed at standard heights over grass that is irrigated and mowed during the growing season to reference evapotranspiration standards.

Agroecosystems & Environment

NAL Agricultural Thesaurus and Glossary

The NAL Agricultural Thesaurus (NALT) was first released by the National Agricultural Library in 2002, with in-depth coverage of agriculture, biology, and related disciplines. It contains over 135,000 terms, including 63,000 cross references, and is arranged into 17 subject categories which are used to…

Ag Data Commons

pySnobal

Spatial Modeling for Resources Framework (SMRF) was developed at the USDA Agricultural Research Service (ARS) in Boise, ID, and was designed to increase the flexibility of taking measured weather data and distributing the point measurements across a watershed.

Agroecosystems & Environment

Automated Water Supply Model (AWSM)

Automated Water Supply Model (AWSM) was developed at the USDA Agricultural Research Service in Boise, ID, to streamline the workflow used to forecast the water supply of multiple water basins.

Spatial Modeling for Resources Framework (SMRF)

Spatial Modeling for Resources Framework (SMRF) was developed at the USDA Agricultural Research Service (ARS) in Boise, ID, and was designed to increase the flexibility of taking measured weather data and distributing the point measurements across a watershed.

Agroecosystems & Environment

Data from: Agro-environmental consequences of shifting from nitrogen- to phosphorus-based manure management of corn.

This experiment was designed to measure greenhouse gas (GHG) fluxes and related agronomic characteristics of a long-term corn-alfalfa rotational cropping system fertilized with manure (liquid versus semi-composted separated solids) from dairy animals. Different manure-application treatments were sized to fulfill two conditions: (1) an application rate to meet the agronomic soil nitrogen requirement of corn (“N-based” without manure incorporation, more manure), and (2) an application rate to match or to replace the phosphorus removal by silage corn from soils (“P-based” with incorporation, less manure). In addition, treatments tested the effects of liquid vs. composted-solid manure, and the effects of chemical nitrogen fertilizer. The controls consisted of non-manured inorganic N treatments (sidedress applications). These activities were performed during the 2014 and 2015 growing seasons as part of the Dairy Coordinated Agricultural Project, or Dairy CAP, as described below. The data from this experiment give insight into the factors controlling GHG emissions from similar cropping systems, and may be used for model calibration and validation after careful evaluation of the flagged data.

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