The automated registration and orthorectification package (AROP) uses precisely registered and orthorectified Landsat data (e.g., GeoCover or recently released free Landsat Level 1T data from the USGS EROS data center) as the base image to co-register, orthorectify and reproject (if needs) the warp images from other data sources, and thus make geo-referenced time-series images consistent in the geographic extent, spatial resolution, and projection. The co-registration, orthorectification and reprojection processes were integrated and thus image is only resampled once. This package has been tested on the Landsat Multi-spectral Scanner (MSS), TM, Enhanced TM Plus (ETM+) and Operational Land Imager (OLI), Terra ASTER, CBERS CCD, IRS-P6 AWiFS, and Sentinel-2 Multispectral Instrument (MSI) data.
The Bushland Reference ET calculator was developed at the USDA-ARS Conservation and Production Research Laboratory, Bushland, Texas. Although it was designed and developed for use mainly by producers and crop consultants to manage irrigation scheduling, it can also be used in educational training, research, and other practical application. It uses the ASCE Standardized Reference Evapotranspiration (ET) Equation for calculating grass and alfalfa reference ET at hourly and daily time steps. This program uses the more complex equation for estimating clear-sky solar radiation provided in Appendix D of the ASCE-EWRI ET Manual. Users have the option of using single set or time series weather data to calculate reference ET. Daily reference ET can be calculated either by summing the hourly ET values for a given day or by using averages of the climatic data.
This paper provides: (1) a summary of the available climate data in Hawai‘i including a detailed description of the various meteorological observation networks and data accessibility, and (2) a quality-controlled meteorological dataset across the Hawaiian Islands for the 25-year period 1990-2014. The dataset draws on observations from 471 climate stations and includes rainfall, maximum and minimum surface air temperature, relative humidity, wind speed, downward shortwave and longwave radiation data.
Data from: Forest harvest dataset for northern Colorado Rocky Mountains (1984–2015) generated from a Landsat time series and existing forest harvest records
This dataset provides a shapefile containing approximately 3500 polygons with the location, extent, size, and year of clearcut harvest events occurring between 1984 and 2015 in forested areas of northern Colorado.
To assess the magnitude of greenhouse gas (GHG) fluxes, nutrient runoff and leaching from dairy barnyards and to characterize factors controlling these fluxes, nine barnyards were built at the U.S. Dairy Forage Research Center Farm in Prairie du Sac, WI (latitude 43.33N, longitude 89.71W). The barnyards were designed to simulate outdoor cattle-holding areas on commercial dairy farms in Wisconsin. Each barnyard was approximately 7m x 7m; areas of barnyards 1-9 were 51.91, 47.29, 50.97, 46.32, 45.64, 46.30, 48.93, 48.78, 46.73 square meters, respectively. Factors investigated included three different surface materials (bark, sand, soil) and timing of cattle corralling. Each barnyard included a gravity drainage system that allowed leachate to be pumped out and analyzed. Each soil-covered barnyard also included a system to intercept runoff at the perimeter and drain to a pumping port, similar to the leachate systems.
The LDMI experiment (Low-Disturbance Manure Incorporation) was designed to evaluate nutrient losses with conventional and improved liquid dairy manure management practices in a corn silage (Zea mays) / rye cover-crop (Secale cereale) system. The improved manure management treatments were designed to incorporate manure while maintaining crop residue for erosion control. Field observations included greenhouse gas (GHG) fluxes from soil, soil nutrient concentrations, crop growth and harvest biomass and nutrient content, as well as monitoring of soil physical and chemical properties. Observations from LDMI have been used for parameterization and validation of computer simulation models of GHG emissions from dairy farms (Gaillard et al., submitted). The LDMI experiment was performed as part of the Dairy CAP.