Sediment load prediction in Johor river: deep learning versus machine learning models

SD Latif, KL Chong, AN Ahmed, YF Huang… - Applied Water …, 2023 - Springer
Sediment transport is a normal phenomenon in rivers and streams, contributing significantly
to ecosystem production and preservation by replenishing vital nutrients and preserving …

A novel spatio-temporal cellular automata model coupling partitioning with CNN-LSTM to urban land change simulation

Y Zhou, C Huang, T Wu, M Zhang - Ecological Modelling, 2023 - Elsevier
Land use change (LUC) has gained attention as a core topic of global ecological
environment change research. The cellular automata (CA) model affects the global layout …

[HTML][HTML] Towards balanced development stage: Regulating the spatial pattern of agglomeration with collaborative optimal allocation of urban land

S Ma, Y Cai, D **e, X Zhang, Y Zhao - Cities, 2022 - Elsevier
Urban agglomeration is an important carrier that promotes urbanization into an advanced
stage, addressing its unbalanced development is an important task for the newly established …

Aboveground biomass estimates of tropical mangrove forest using Sentinel-1 SAR coherence data-The superiority of deep learning over a semi-empirical model

SM Ghosh, MD Behera - Computers & Geosciences, 2021 - Elsevier
The availability of advanced Machine Learning algorithms has made the estimation process
of biophysical parameters more efficient. However, the efficiency of those methods seldom …

Development Process, Quantitative Models, and Future Directions in Driving Analysis of Urban Expansion

X Guan, J Li, C Yang, W **ng - ISPRS International Journal of Geo …, 2023 - mdpi.com
Driving analysis of urban expansion (DAUE) is usually implemented to identify the driving
factors and their corresponding driving effects/mechanisms for the expansion processes of …

Integrating machine learning with Markov chain and cellular automata models for modelling urban land use change

O Okwuashi, CE Ndehedehe - Remote Sensing Applications: Society and …, 2021 - Elsevier
Modelling urban land use change is of profound concern to environmental scientists who
have found cellular automata models very attractive for simulating urban dynamics. The …

Estimation of aboveground carbon density of forests using deep learning and multisource remote sensing

F Zhang, X Tian, H Zhang, M Jiang - Remote Sensing, 2022 - mdpi.com
Forests are crucial in carbon sequestration and oxygen release. An accurate assessment of
forest carbon storage is meaningful for Chinese cities to achieve carbon peak and carbon …

[HTML][HTML] Urban expansion simulation and development-oriented zoning of rapidly urbanising areas: A case study of Hangzhou

Y Zhou, T Wu, Y Wang - Science of The Total Environment, 2022 - Elsevier
Sustainable urban development is the key to regional urban development policy-making.
Therefore, the comprehensive spatial zoning of rapidly urbanising areas is important. In this …

[HTML][HTML] A hybrid spatiotemporal convolution-based cellular automata model (ST-CA) for land-use/cover change simulation

J Geng, S Shen, C Cheng, K Dai - … Journal of Applied Earth Observation and …, 2022 - Elsevier
Accurate land-use/-cover change (LUCC) simulation is of great significance to issues closely
related to regional planning and policy-making. Many models have been committed to …

[HTML][HTML] Urban land use simulation and carbon-related driving factors analysis based on RF-CA in Shanghai, China

L Ye, S Zhao, H Yang, X Chuai, L Zhai - Ecological Indicators, 2024 - Elsevier
As global climate change intensifies, climate protection is important for the sustainable
development of human society. In the process of urbanization and industrialization, carbon …