The urban agglomeration at the Yangtze River Delta is one of the six most developed and populated urban agglomerations in the world. In recent years, with accelerating urbanization, the land use has changed significantly. Excessive construction aggravates ecological fragility.
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.
This paper explores the specific “authoritarian” type of adaptive governance of urban regeneration using the example of Guangzhou city as the frontier of China’s reforms.
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.
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 major human activity, urbanization exerts a strong impact on the fragile ecosystem in the Hindu Kush Himalayas (HKH) region. To maintain sustainable development, reliable data on urban land change are required to assess the impact of urbanization.
Assessing the impacts and drivers of urban expansion on terrestrial carbon storage (TCS) is important for urban ecology and sustainability; however, a unified accounting standard for carbon intensity and research on the drivers and economic value of TCS changes are lacking.
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.
With the intensification of the contradiction between living space and population growth, it is necessary to improve the effectiveness of urban residential land allocation.
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.
