Simulating urban land use change by integrating a convolutional neural network with vector-based cellular automata
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Simulating urban land use change by integrating a convolutional neural network with vector-based cellular automata
Authors
Keywords
-
Journal
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
Volume -, Issue -, Pages 1-25
Publisher
Informa UK Limited
Online
2020-01-15
DOI
10.1080/13658816.2020.1711915
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Mining transition rules of cellular automata for simulating urban expansion by using the deep learning techniques
- (2018) Jialv He et al. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
- Public Perception Analysis of Tweets During the 2015 Measles Outbreak: Comparative Study Using Convolutional Neural Network Models
- (2018) Jingcheng Du et al. JOURNAL OF MEDICAL INTERNET RESEARCH
- Multiple intra-urban land use simulations and driving factors analysis: a case study in Huicheng, China
- (2018) Dachuan Zhang et al. GIScience & Remote Sensing
- Experiences and issues of using cellular automata for assisting urban and regional planning in China
- (2017) Xia Li et al. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
- Simulating urban land-use changes at a large scale by integrating dynamic land parcel subdivision and vector-based cellular automata
- (2017) Yao Yao et al. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
- A future land use simulation model (FLUS) for simulating multiple land use scenarios by coupling human and natural effects
- (2017) Xiaoping Liu et al. LANDSCAPE AND URBAN PLANNING
- Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review
- (2017) Waseem Rawat et al. NEURAL COMPUTATION
- Comparison of Spatial Interpolation and Regression Analysis Models for an Estimation of Monthly Near Surface Air Temperature in China
- (2017) Mengmeng Wang et al. Remote Sensing
- Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
- (2016) Hoo-Chang Shin et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Capturing the varying effects of driving forces over time for the simulation of urban growth by using survival analysis and cellular automata
- (2016) Yimin Chen et al. LANDSCAPE AND URBAN PLANNING
- Characterization of neighborhood sensitivity of an irregular cellular automata model of urban growth
- (2015) Khila R. Dahal et al. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
- Construction of an ecological resistance surface model and its application in urban expansion simulations
- (2015) Yuyao Ye et al. Journal of Geographical Sciences
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Modeling urban growth with GIS based cellular automata and least squares SVM rules: a case study in Qingpu–Songjiang area of Shanghai, China
- (2015) Yongjiu Feng et al. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
- Urban Land Expansion and Sustainable Land Use Policy in Shenzhen: A Case Study of China’s Rapid Urbanization
- (2015) Jing Qian et al. Sustainability
- Simulating Urban Growth Using a Random Forest-Cellular Automata (RF-CA) Model
- (2015) Courage Kamusoko et al. ISPRS International Journal of Geo-Information
- A vector-based Cellular Automata model for simulating urban land use change
- (2014) Yi Lu et al. Chinese Geographical Science
- Modeling urban expansion policy scenarios using an agent-based approach for Guangzhou Metropolitan Region of China
- (2014) Guangjin Tian et al. ECOLOGY AND SOCIETY
- Simulation of land use/land cover change and its effects on the hydrological characteristics of the upper reaches of the Hanjiang Basin
- (2014) Zhimin Deng et al. Environmental Earth Sciences
- Quantifying spatiotemporal patterns of urban expansion in three capital cities in Northeast China over the past three decades using satellite data sets
- (2014) Yan Sun et al. Environmental Earth Sciences
- Modeling urban land-use dynamics in a fast developing city using the modified logistic cellular automaton with a patch-based simulation strategy
- (2013) Yimin Chen et al. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
- An Assessment of Internal Neural Network Parameters Affecting Image Classification Accuracy
- (2013) Libin Zhou et al. PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING
- China’s urban expansion from 1990 to 2010 determined with satellite remote sensing
- (2012) Lei Wang et al. CHINESE SCIENCE BULLETIN
- Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion
- (2012) Jamal Jokar Arsanjani et al. International Journal of Applied Earth Observation and Geoinformation
- Examining Land-Use/Land-Cover Change in the Lake Dianchi Watershed of the Yunnan-Guizhou Plateau of Southwest China with Remote Sensing and GIS Techniques: 1974–2008
- (2012) Yaolong Zhao et al. International Journal of Environmental Research and Public Health
- Cellular automata models for the simulation of real-world urban processes: A review and analysis
- (2010) Inés Santé et al. LANDSCAPE AND URBAN PLANNING
- Spatio-temporal dynamics and evolution of land use change and landscape pattern in response to rapid urbanization
- (2009) Jin S. Deng et al. LANDSCAPE AND URBAN PLANNING
- Discovering and evaluating urban signatures for simulating compact development using cellular automata
- (2008) Xia Li et al. LANDSCAPE AND URBAN PLANNING
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started