MnIII-Peroxo adduct supported by a new tetradentate ligand shows acid-sensitive aldehyde deformylation reactivity
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99 GENERAL AND MISCELLANEOUS↗
Engineering topics
Rice, D.
Publications and source records attributed to Rice, D..
Investigation and Development of Data-Driven D-Region Model for HF Systems Impacts
Space Environment Corporation (SEC) and RP Consultants (RPC) are to develop and validate a weather-capable D region model for making High Frequency (HF) absorption predictions in support of the HF communications and radar communities. The weather-capable model will assimilate solar and earth space observations from NASA satellites. The model will account for solar-induced impacts on HF absorption, including X-rays, Solar Proton Events (SPE's), and auroral precipitation. The work plan includes: I . Optimize D-region model to quickly obtain ion and electron densities for proper HF absorption calculations. 2. Develop indices-driven modules for D-region ionization sources for low, mid, & high latitudes including X-rays, cosmic rays, auroral precipitation, & solar protons. (Note: solar spectrum & auroral modules already exist). 3. Setup low-cost monitors of existing HF beacons and add one single-frequency beacon. 4. Use PENEX HF-link database with HF monitor data to validate D-region/HF absorption model using climatological ionization drivers. 5. Develop algorithms to assimilate NASA satellite data of solar, interplanetary, and auroral observations into ionization source modules. 6. Use PENEX HF-link & HF-beacon data for skill score comparison of assimilation versus climatological D-region/HF absorption model. Only some satellites are available for the PENEX time period, thus, HF-beacon data is necessary. 7. Use HF beacon monitors to develop HF-link data assimilation algorithms for regional improvement to the D-region/HF absorption model.
Eccles, J. V.↗
Ground truth crop proportion summaries for US segments, 1976-1979
The original ground truth data was collected, digitized, and registered to LANDSAT data for use in the LACIE and AgRISTARS projects. The numerous ground truth categories were consolidated into fewer classes of crops or crop conditions and counted occurrences of these classes for each segment. Tables are presented in which the individual entries are the percentage of total segment area assigned to a given class. The ground truth summaries were prepared from a 20% sample of the scene. An analysis indicates that this size of sample provides sufficient accuracy for use of the data in initial segment screening.
Horvath, R.↗
Users manual for the US baseline corn and soybean segment classification procedure
A user's manual for the classification component of the FY-81 U.S. Corn and Soybean Pilot Experiment in the Foreign Commodity Production Forecasting Project of AgRISTARS is presented. This experiment is one of several major experiments in AgRISTARS designed to measure and advance the remote sensing technologies for cropland inventory. The classification procedure discussed is designed to produce segment proportion estimates for corn and soybeans in the U.S. Corn Belt (Iowa, Indiana, and Illinois) using LANDSAT data. The estimates are produced by an integrated Analyst/Machine procedure. The Analyst selects acquisitions, participates in stratification, and assigns crop labels to selected samples. In concert with the Analyst, the machine digitally preprocesses LANDSAT data to remove external effects, stratifies the data into field like units and into spectrally similar groups, statistically samples the data for Analyst labeling, and combines the labeled samples into a final estimate.
Horvath, R.↗