Map** the landscape and roadmap of geospatial artificial intelligence (GeoAI) in quantitative human geography: An extensive systematic review

S Wang, X Huang, P Liu, M Zhang, F Biljecki… - International Journal of …, 2024 - Elsevier
This paper brings a comprehensive systematic review of the application of geospatial
artificial intelligence (GeoAI) in quantitative human geography studies, including the …

Greening the knowledge-based economies: Harnessing natural resources and innovation in information and communication technologies for green growth

Z Wang, Y Huang, V Ankrah, J Dai - Resources Policy, 2023 - Elsevier
The quest for green growth through the sustainable use of natural resources (NRs) and
innovation in information and communication technologies (IICTs) has gained the utmost …

A novel hybrid machine learning model for prediction of CO2 using socio-economic and energy attributes for climate change monitoring and mitigation policies

S Kumar - Ecological informatics, 2023 - Elsevier
Industrial development has contributed to carbon emissions majorly, resulting in high
concentrations of greenhouse gases (GHGs) in the environment leading to climate change …

Enhancing CO2 emissions prediction in Africa: A novel approach integrating enviroeconomic factors and nature-inspired neural network in the presence of unit root

S Mati, AJ Baita, GY Ismael, SG Abdullahi, A Samour… - Renewable Energy, 2024 - Elsevier
The prediction of CO 2 emissions is critical for designing sustainable environmental policies
and meeting the Sustainable Development Goals, particularly those related to climate …

Forecasting the ecological footprint of G20 countries in the next 30 years

RM Eufrasio Espinosa, SC Lenny Koh - Scientific reports, 2024 - nature.com
Abstract The Ecological Footprint evaluates the difference between the availability of
renewable resources and the extent of human consumption of these resources. Over the …

[HTML][HTML] Forecasting biocapacity and ecological footprint at a worldwide level to 2030 using neural networks

MA Moros-Ochoa, GY Castro-Nieto… - Sustainability, 2022 - mdpi.com
Constant environmental deterioration is a problem widely addressed by multiple
international organizations. However, given the current economic and technological …

Predicting carbon dioxide emissions in the United States of America using machine learning algorithms

BP Chukwunonso, I Al-Wesabi, L Shixiang… - … Science and Pollution …, 2024 - Springer
Carbon dioxide (CO2) emissions result from human activities like burning fossil fuels. CO2 is
a greenhouse gas, contributing to global warming and climate change. Efforts to reduce …

Estimation and prediction of ecological footprint using tourism development indices top tourist destination countries

A Roumiani, A Basir Arian, H Mahmoodi… - Sustainable …, 2023 - Wiley Online Library
During the last two decades, the ecological footprint (EF) has had various fluctuations and
has been associated with an upward trend, which can be a concern. This research aims to …

Predicting the impacts of key development indices on the ecological footprint in Afghanistan using deep learning

AB Arian, MN Nazary, AZ Karimi, M Obiad - International Journal of …, 2025 - Springer
Evaluating the ecological footprint (EF) is one of the objectives of nations worldwide, playing
a vital role in preserving their environmental resources. This check aims to predict the …

RETRACTED ARTICLE: Impact optical communication model in sustainable building construction over the carbon footprint detection using quantum networks

X Li, T Wang, L Li - Optical and Quantum Electronics, 2023 - Springer
From an urban planning perspective, accurately predicting urban block carbon emissions
(UBCE) based on built environment factors is a good way to minimize UBCE as well as …