Daniel P. Ames
Brigham Young University
137 Papers
445 Citations
Daniel P. Ames is an academic researcher from Brigham Young University. The author has contributed to research in topics: Computer science & Web service. The author has an hindex of 27, co-authored 129 publications. Previous affiliations of Daniel P. Ames include Idaho State University & Boise State University.
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Papers
Application of Vegetation Indices for Agricultural Crop Yield Prediction Using Neural Network Techniques
TL;DR: The goal of this paper was to investigate the strength of key spectral vegetation indices for agricultural crop yield prediction using neural network techniques and Log10 data transformation technique was used to enhance the prediction ability of the PVI models of years 1998, 1999, and 2001.
385
Introductory overview: Error metrics for hydrologic modelling – A review of common practices and an open source library to facilitate use and adoption
Elise K. Jackson,Wade Roberts,Benjamin Nelsen,Gustavious P. Williams,E. James Nelson,Daniel P. Ames +5 more
TL;DR: The open source HydroErr library is presented, implemented in Python and MATLAB®, which contains the error metric functions reported here to facilitate greater use of these metrics and encourage metric exploration related to relative metric strengths and weaknesses.
168
Using GIS analytics and social preference data to evaluate utility-scale solar power site suitability
TL;DR: In this paper, a GIS-based multi-criteria solar project siting study conducted in the southwestern United States with a unique social preference component is presented, where proximity raster layers were derived from features including roads, power lines, and rivers then overlain with 10 × 10 m raster terrain datasets including slope and potential irradiance to produce a high resolution map showing solar energy potential from “poor” to “excellent” for high potential counties across the southwest United States.
155
Position paper: Open web-distributed integrated geographic modelling and simulation to enable broader participation and applications
Min Chen,Alexey Voinov,Alexey Voinov,Daniel P. Ames,Albert J. Kettner,Jonathan L. Goodall,Anthony Jakeman,Michael Barton,Quillon Harpham,Susan Cuddy,Cecelia DeLuca,Songshan Yue,Jin Wang,Fengyuan Zhang,Yongning Wen,Guonian Lü +15 more
TL;DR: A conceptual framework is proposed to introduce a roadmap from a system design perspective, with potential use cases provided and a set of standards, a resource sharing environment, a collaborative integrated modelling environment, and a distributed simulation environment discussed.
Effective modeling for integrated water resource management: a guide to contextual practices by phases and steps and future opportunities
Jennifer Badham,Sondoss Elsawah,Sondoss Elsawah,Joseph H. A. Guillaume,Joseph H. A. Guillaume,Serena H. Hamilton,Serena H. Hamilton,Randall J. Hunt,Anthony Jakeman,Suzanne A. Pierce,Val Snow,Meghna Babbar-Sebens,Baihua Fu,Patricia Gober,Mary C. Hill,Takuya Iwanaga,Daniel P. Loucks,Wendy Merritt,Scott D. Peckham,Amy K. Richmond,Fateme Zare,Daniel P. Ames,Gabriele Bammer +22 more
TL;DR: Practice-focused guidance helps explain the detailed process of conducting IWRM modeling, including the role of contextual factors in shaping practices, and five key areas for future practice-related research are concluded.