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Amin Tayyebi
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2020 – today
- 2022
- [j11]Hanieh Shojaei
, Saeed Nadi
, Hossein Shafizadeh-Moghadam
, Amin Tayyebi, John L. van Genderen
:
An efficient built-up land expansion model using a modified U-Net. Int. J. Digit. Earth 15(1): 148-163 (2022)
2010 – 2019
- 2017
- [j10]Amin Tayyebi
, Samuel J. Smidt
, Bryan C. Pijanowski:
Long-Term Land Cover Data for the Lower Peninsula of Michigan, 2010-2050. Data 2(2): 16 (2017) - [j9]Hossein Shafizadeh-Moghadam
, Ali Asghari
, Amin Tayyebi, Mohammad Taleai
:
Coupling machine learning, tree-based and statistical models with cellular automata to simulate urban growth. Comput. Environ. Urban Syst. 64: 297-308 (2017) - [j8]Hossein Shafizadeh-Moghadam
, Amin Tayyebi, Mohammad Ahmadlou, Mahmoud Reza Delavar, Mahdi Hasanlou
:
Integration of genetic algorithm and multiple kernel support vector regression for modeling urban growth. Comput. Environ. Urban Syst. 65: 28-40 (2017) - 2016
- [j7]Amin Tayyebi
, Timothy D. Meehan, Jeffrey Dischler, Gary Radloff, Michael Ferris
, Claudio Gratton
:
SmartScape™: A web-based decision support system for assessing the tradeoffs among multiple ecosystem services under crop-change scenarios. Comput. Electron. Agric. 121: 108-121 (2016) - [j6]Jamal Jokar Arsanjani
, Linda See, Amin Tayyebi
:
Assessing the suitability of GlobeLand30 for mapping land cover in Germany. Int. J. Digit. Earth 9(9): 873-891 (2016) - [j5]Amin Tayyebi
, Amir Hossein Tayyebi, Jamal Jokar Arsanjani
, Hossein Shafizadeh-Moghadam
, Hichem Omrani
:
FSAUA: A framework for sensitivity analysis and uncertainty assessment in historical and forecasted land use maps. Environ. Model. Softw. 84: 70-84 (2016) - 2014
- [j4]Amin Tayyebi
, Bryan C. Pijanowski
:
Modeling multiple land use changes using ANN, CART and MARS: Comparing tradeoffs in goodness of fit and explanatory power of data mining tools. Int. J. Appl. Earth Obs. Geoinformation 28: 102-116 (2014) - [j3]Bryan C. Pijanowski
, Amin Tayyebi
, Jarrod Doucette, Burak K. Pekin
, David Braun, James Plourde:
A big data urban growth simulation at a national scale: Configuring the GIS and neural network based Land Transformation Model to run in a High Performance Computing (HPC) environment. Environ. Model. Softw. 51: 250-268 (2014) - [j2]Amin Tayyebi
, Bryan C. Pijanowski, Marc Linderman, Claudio Gratton
:
Comparing three global parametric and local non-parametric models to simulate land use change in diverse areas of the world. Environ. Model. Softw. 59: 202-221 (2014) - [j1]Amin Tayyebi
, Phillips Christian Perry, Amir Hossein Tayyebi:
Predicting the expansion of an urban boundary using spatial logistic regression and hybrid raster-vector routines with remote sensing and GIS. Int. J. Geogr. Inf. Sci. 28(4): 639-659 (2014) - 2013
- [b1]Amin Tayyebi:
Simulating Land Use Land Cover Change Using Data Mining and Machine Learning Algorithms. Purdue University, USA, 2013
Coauthor Index
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