In a digitalized era and with the rapid growth of computational skills and advancements, artificial intelligence and Machine Learning uses in various applications are gaining a rising interest from scholars and practitioners. As a fast-growing field of Artificial Intelligence, Machine Artificial Intelligence deals with smart designs, data mining and management for complex problem-solving based on experimental data on urban applications (land use and cover, configurations of the built environment and architectural design, etc.), but with few explorations and relevant studies.

In the context of tax sharing reform and land reform during the 1990s, local governments in China relied heavily on land finance. Local governments have fierce competition in attracting investment, omitting the development of green economy. Based on the data of industrial land sales and carbon dioxide emissions, this study constructed the panel data of 196 cities in China from 2007 to 2017 and analyzed the spatial and temporal evolution characteristics of urban industrial land price distortion and carbon emission intensity.

With continuous rises in GDP, land cover in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) has undergone a drastic change over the period 1990–2018. In this study, land use in the GBA was divided into six types: farmland, forestland, grassland, wetland, construction land, and unused land. We analyzed changes in spatiotemporal patterns according to region and type by using statistical analysis, spatial clustering, and hotspot analysis, focusing on the spatial characteristics of areas where land-use types changed with high frequency.

Baseflow is an essential component of runoff, which is the dominant water resource for the dry season. To better manage water resources, it is vital to investigate the links between the multiple influencing factors and the baseflow for better prediction in light of global changes. Previous studies have seldom separated these influencing factors in the analysis, making it difficult to determine their effect on the baseflow.

Global environmental changes are multifactorial and affected by multiple forms of land use. For this reason, and also in view of the current world climate scenario, they have become highly relevant and are subject to analysis and discussions on the best uses of land. The research presented here offers a systematic analysis on the priorities related to the multiple uses of land and their implications in urban planning. An exploratory and descriptive analysis is used with a qualitative approach based in a systematic literature review.

Seeking land use development strategies is an effective policy tool to support economic development, especially in developing countries. Previous studies evidence the indispensable role of urban construction land use (UCLU) in regional economic development. However, neglecting the two-stage characteristic and mismatch of UCLU could misinterpret the strategy. This study, considering a two-stage characteristic, aims to explore how land use development strategy affects economic development. First, we create a measure for UCLU mismatch.

Due to the rapid development of urbanization, land-use types have changed greatly, which has led to many ecological problems. Therefore, the current research objective is to solve the problems in existence in Jinan, so as to determine the existing landscape ecological risks and optimize the landscape structure.

Carbon emissions increase the risk of climate change. As one of the primary sources of carbon emissions, road traffic faces a significant challenge in terms of reducing carbon emissions. Many studies have been conducted to examine the impacts of cities on carbon emissions from the perspectives of urbanization, population size, and economics. However, a detailed understanding of the relationship between road traffic and urban carbon emissions is lacking due to the lack of a reasonable set of road traffic metrics.

Industrial agglomeration is one of the primary driving factors in city creation, and the improvement of urban land green use efficiency (ULGUE) is an important part in green development. This study concentrates on the impact of industrial agglomeration on ULGUE in the process of urbanization. Based on the panel data of 283 cities in China from 2003 to 2019, this paper constructs a super efficiency SBM-DEA model including unexpected outputs to evaluate ULGUE.

The supply of built-up land determines the depths of human activities, leading to the differences in scale and intensity of carbon emissions. However, the relationship between the composition of built-up land and carbon emissions has not been fully investigated. In response, this study collects the panel data of 88 cities along the Yangtze River Economic Belt, China, and uses the fixed effect model and system GMM model, to explore the impacts of specific subtypes of built-up land on carbon emissions averaged by economic output and urban land.

As a key part of the forest ecosystem, soil microorganisms play extremely important roles in maintaining the ecological environment and the security of water quality in reservoir areas. However, it is not clear whether there are differences in the functional diversity of soil microorganisms in different types of water-conservation forests in reservoir areas, and which factors affect the functional diversity of soil microorganisms.

More than 60% of the world’s ecosystem services have deteriorated over the past few decades. Studying the spatio-temporal fluctuations in ecosystem service value and its influencing factors is important for identifying regional ecosystem service value issues, upholding regional ecological harmony, and encouraging regionally healthy and coordinated sustainable development. Ecosystem service value has so far been studied primarily in relation to the effect of socioeconomic and physical–geographical variables.