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Mahmoud Saeedimoghaddam
Mahmoud Saeedimoghaddam
PhD, GIScience
Verified email at ucdavis.edu
Title
Cited by
Cited by
Year
Automatic extraction of road intersection points from USGS historical map series using deep convolutional neural networks
M Saeedimoghaddam, TF Stepinski
International Journal of Geographical Information Science 34 (5), 947-968, 2020
542020
Rényi’s spectra of urban form for different modalities of input data
M Saeedimoghaddam, TF Stepinski, A Dmowska
Chaos, Solitons & Fractals 139, 109995, 2020
62020
Modeling a spatio-temporal individual travel behavior using geotagged social network data: a case study of greater cincinnati
M Saeedimoghaddam, C Kim
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2017
42017
A probabilistic space-time prism to explore changes in white Stork habitat use in Iran
M Saeedimoghaddam, M Keyanpour-Rad, H Shafizadeh-Moghadam, ...
Ecological Indicators 78, 156-166, 2017
42017
An artificial neural network emulator of the rangeland hydrology and erosion model
M Saeedimoghaddam, G Nearing, M Hernandez, MA Nearing, ...
International Soil and Water Conservation Research, 2023
12023
Multiplicative random cascade models of multifractal urban structures
M Saeedimoghaddam, TF Stepinski
Physica A: Statistical Mechanics and its Applications 569, 125767, 2021
12021
Exploring the Effectiveness of the Urban Growth Boundaries in USA using the Multifractal Analysis of the Road Intersection Points, A Case Study of Portland, Oregon
M Saeedimoghaddam
University of Cincinnati, 2020
12020
An AI-First Framework for Digital Twins: Construction and Demonstration with a Land Surface Model
B Smith, C Pelissier, GS Nearing, C Cruz, D Raghunandan, ...
AGU23, 2023
2023
Understanding Drought Awareness from Web Data
M Rahman, SS Solis, T Harter, M Saeedimoghaddam, N Efron, G Nearing
EarthArXiv, 2023
2023
An Artificial Neural Network to Estimate the Foliar and Ground Cover Input Variables of the Rangeland Hydrology and Erosion Model
M Saeedimoghaddam, G Nearing, DC Goodrich, M Hernandez, ...
EarthArXiv, 2023
2023
Dynamic Attributes in Deep Learning Rainfall-Runoff Models to Address Non-Stationarity
L Qualls, J Frame, G Nearing, M Saeedimoghaddam
AGU Fall Meeting Abstracts 2021, H35ZB-03, 2021
2021
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Articles 1–11