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2DLEAF

    A 2D mechanistic model of CO2 and water vapor movement in a leaf and photosynthesis.

    STARFM

      The STARFM algorithm uses comparisons of one or more pairs of observed Landsat/MODIS maps, collected on the same day, to predict maps at Landsat-scale on other MODIS observation dates. STARFM was initially developed at the NASA Goddard Space Flight Center by Dr. Feng Gao. This version (v1.2) has been greatly improved in computing efficiency (e.g. one run for multiple dates and parallel computing) for large-area processing (Gao et al., 2015). Additional improvements (e.g. Landsat and MODIS images co-registration, daily MODIS nadir BRDF-adjusted reflectance) in the operational data fusion system (Wang et al., 2014) are beyond the STARFM program and are not included in this package. Improvement and continuous maintenance are being undertaken in the USDA-ARS Hydrology and Remote Sensing Laboratory (HRSL), Beltsville, MD by Dr. Feng Gao.

      DRIFTSIM

        DRIFTSIM can be used to determine the effects of major drift-causing factors on the mean drift distances up to 656 feet from the release point for individual water droplets or classes of droplets.

        DepositScan

          DepositScan is a scanning program that can quickly evaluate spray deposit distribution on water sensitive paper or Kromekote cards. The program consists of a set of custom plugins that are used by an image-processing program to produce a number of measurements useful for expressing spray deposit distribution. The DepositScan program offers a convenient solution for on-the-spot evaluation of spray quality even under field working conditions.

          Code from: Using cameras for precise measurement of two-dimensional plant features

            Images are used frequently in plant phenotyping to capture measurements. This chapter offers a repeatable method for capturing two-dimensional measurements of plant parts in field or laboratory settings using a variety of camera styles (cellular phone, DSLR), with the addition of a printed calibration pattern. The method is based on calibrating the camera using information available from the EXIF tags from the image, as well as visual information from the pattern. Code is provided to implement the method, as well as a dataset for testing. We include steps to verify protocol correctness by imaging an artifact. The use of this protocol for two-dimensional plant phenotypoing will allow data capture from different cameras and environments, with comparison on the same physical scale.

            Genomes To Fields 2016

              Phenotypic, genotypic, and environment data for the 2016 field season: The data is stored in [CyVerse](http://datacommons.cyverse.org/browse/iplant/home/shared/commons_repo/curated/GenomesToFields_G2F_2016_Data_Mar_2018).

              Genomes To Fields 2015

                Phenotypic, genotypic, and environment data for the 2015 field season: The data is stored in [CyVerse](http://datacommons.cyverse.org/browse/iplant/home/shared/commons_repo/curated/Carolyn_Lawrence_Dill_G2F_Mar_2017).

                Genomes To Fields 2014

                  Phenotypic, genotypic, and environment data for the 2014 field season: The data is stored in [CyVerse](http://datacommons.cyverse.org/browse/iplant/home/shared/commons_repo/curated/Carolyn_Lawrence_Dill_G2F_Nov_2016_V.3).

                  Genomes To Fields (G2F) Inbred Ear Imaging Data 2017

                    A subset of ~30 inbreds were evaluated in 2014 and 2015 to develop an image based ear phenotyping tool. The data is stored in [CyVerse](http://datacommons.cyverse.org/browse/iplant/home/shared/commons_repo/curated/Edgar_Spalding_G2F_Inbred_Ear_Imaging_June_2017).