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.

Analyses of the scale and structural characteristics of construction land serve as the basis for optimizing the spatial pattern of territorial planning. Existing studies have focused mainly on the horizontal expansion of urban construction land.

Urban land optimization in urban agglomerations plays an important role in promoting territorial spatial planning to achieve high-quality development, land ecological suitability (LES) is one of the important variables influencing its urbanization and needs to be considered in urban growth simulation and modeling. This research proposed a multi-objective urban land optimization (MULO) model based on the non-dominated sorting genetic algorithm II (NSGA-II) which integrates the LES assessment.

In recent years, the rapid improvement in the urbanization level of the Central Plains urban agglomeration is bound to bring about significant changes in urban land expansion and economic development. However, at present, there is little attention paid to the research on the spatiotemporal interaction characteristics of urban expansion and the interaction between urban expansion and economic development in this region, and existing research lacks a geographical analysis perspective.

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.

Urbanization alters land uses and creates heterogeneous environmental conditions in cities and their surroundings, which may directly or indirectly impact soil microorganisms. However, how urbanization affects soil bacterial diversity and community composition, particularly in different land use types, remains largely unknown. In this study, we collected 36 soil samples (18 forest and 18 grass soils) along a rural-suburban-urban gradient in Chang-Zhu-Tan agglomeration.

As the most intuitive manifestation of land use/land cover change, the spatio-temporal evolution of landscape patterns has significant implications for optimizing regional landscape pattern and land use management. Based on multi-period remote sensing data, we selected an optimal scale (570 m) and used the geographic detector model to analyze the spatio-temporal changes in the landscape pattern of a typical hilly area (Yujiang District, Yingtan City, Jiangxi Province) in southern China.

This paper addresses a forest harvesting problem with adjacency constraints, including additional environmental constraints to protect wildlife habitats and minimize infrastructure deployment costs. To this end, we propose an integer programming model to include those considerations during the optimization of the harvest regime of a Mexican forest. The model considered was based on the Unit Restriction Model, a benchmark approach that merges the management units before the optimization process.

Gymnocarpos przewalskii is a rare Tertiary relict species, mainly distributed in desert areas of northwestern China. Changes in rainfall have a significant impact on the physiological characteristics of desert plants. In the present study, the effects of five simulated rainfall levels on the gas exchange parameters, chlorophyll fluorescence characteristics, and antioxidant system of G. przewalskii were studied. The results show that with increased rainfall the net photosynthetic rate (Pn) and transpiration rate increase significantly.

This paper addresses a forest harvesting problem with adjacency constraints, including additional environmental constraints to protect wildlife habitats and minimize infrastructure deployment costs. To this end, we propose an integer programming model to include those considerations during the optimization of the harvest regime of a Mexican forest. The model considered was based on the Unit Restriction Model, a benchmark approach that merges the management units before the optimization process.