Kelly R. Thorp

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a r t i c l e i n f o Keywords: Crop model CSM DSSAT Genetic algorithm Hyperspectral LAI Model inversion Nitrogen Optimization PEST PROSAIL Simulation Wheat Yield Remote sensing technology can rapidly provide spatial information on crop growth status, which ideally could be used to invert radiative transfer models or ecophysiological models for estimating a(More)
A novel geospatial tool box named Geospatial Simulation (GeoSim) has been developed, which can be used to manage point-based model simulations at multiple locations using geospatial data within a geographic information system (GIS). The objectives of this paper were to describe GeoSim and demonstrate its use. GeoSim has been developed as a plug-in for(More)
[1] Observing system simulation experiments were used to investigate ensemble Bayesian state-updating data assimilation of observations of leaf area index (LAI) and soil moisture ( ) for the purpose of improving single-season wheat yield estimates with the Decision Support System for Agrotechnology Transfer (DSSAT) CropSim-Ceres model. Assimilation was(More)
Crop growth models have recently been implemented to study precision agriculture questions within the framework of a decision support system (DSS) that automates simulations across management zones. Model calibration in each zone has occurred by automatically optimizing select model parameters to minimize error between measured and simulated yield over(More)
Most studies assessing chlorophyll fluorescence (ChlF) have examined leaf responses to environmental stress conditions using active techniques. Alternatively, passive techniques are able to measure ChlF at both leaf and canopy scales. However, the measurement principles of both techniques are different, and only a few datasets concerning the relationships(More)
Since corn plant stand density is important for optimizing crop yield, several researchers have recently developed ground‐based systems for automatic measurement of this crop growth parameter. Our objective was to use data from such a system to assess the potential for estimation of corn plant stand density using remote sensing images. Aerial hyperspectral(More)
Nitrate leaching in the unsaturated zone poses a risk to groundwater, whereas nitrate in tile drainage is conveyed directly to streams. We developed metamodels (MMs) consisting of artificial neural networks to simplify and upscale mechanistic fate and transport models for prediction of nitrate losses by drains and leaching in the Corn Belt, USA. The two(More)