Relatively little attention has been paid to examining the spatial expansion features of cities at various tiers at the regional level in China, especially those located in central and western regions of the country. Based on Landsat satellite imagery from four years—1980, 1990, 2000, and 2010, this paper investigates the spatio-temporal pattern of urban land expansion and its influencing factors in the Wuhan Urban Agglomeration (WUA) in central China. The research found that the total area of urban land expanded from 203.66 km² in 1980 to 1370.07 km² in 2010, and that urban land areas increased by 423.82, 167.42, and 574.93 km² in the periods 1980–1990, 1990–2000, and 2000–2010 respectively, exhibiting significant fluctuation between the different periods studied. Geographically, this spatial expansion pattern was characterised by conspicuous concentrations and regional imbalances across the overall study period. Whilst these spatio-temporal differences were found to be closely related to industrialisation, urban population growth, land-use policies, urbanisation guidelines (governmental plans and regulations addressing urbanisation), and national development strategy, the dominant mechanisms driving those differences varied over time. In response, the paper presents an urban-rural and regional integration strategy, with the aim of avoiding economic gaps and the inefficient utilisation of various resources in the urban agglomeration areas.

Forest Ecological Security (FES) means coordinated development of forest ecosystems, social economies, and the forest environment. In this paper, we evaluate FES in Beijing under different designed scenarios using a dynamic systems model and find that first, the initial FES index value (in Scenario 0) increased to its highest level of 0.529 in 2012, but declined slightly to 0.485 by 2020. Second, in Scenarios 1–4, the FES index value reached 0.545, 0.516, 0.585 and 0.637 respectively in 2020, which was enhanced in varying degrees when compared with Scenario 0. The simulation shows the implementation of forest management policies, socioeconomic development and environmental management combine to affect the FES in Beijing. The FES could develop into a good state when the productivity of forest resources, the stability of forest environments and the orderly development of the social economy are carefully maintained (in Scenario 4). This research could provide decision-making in support of the overall improvement of forest conditions while promoting sustainable forestry in Beijing.

A large body of recent studies—from both inside and outside of China—are devoted to the understanding of China’s regional inequality. The current study introduces “the spatial field model” to achieve comprehensive evaluation and multi-scale analysis of regional inequality. The model is based on the growth pole theory, regional interaction theory, and energy space theory. The spatial field is an abstract concept that defines the potential energy difference that is formed in the process of a regional growth pole driving the economic development of peripheral areas through transportation and communication corridors. The model is able to provide potentially more precise regional inequality estimates and generates isarithmic maps that will provide highly intuitive and visualized presentations. The model is applied to evaluate the spatiotemporal pattern of economic inequality in China from 2000 to 2012 amongst internal eastern-central-western regions as well as north-south regions at three geographical scales—i.e., inter-province, inter-city, and inter-county. The results indicate that the spatial field model could comprehensively evaluate regional inequality, provide aesthetically pleasing and highly adaptable presentations based on a pixel-based raster, and realise the multi-scale analyses of the regional inequality. The paper also investigates the limitations and extensions of the spatial field model in future application.

In this study, an inexact stochastic fuzzy programming (ISFP) model is proposed for land-use allocation (LUA) and environmental/ecological planning at a watershed level, where uncertainties associated with land-use parameters, benefit functions, and environmental/ecological requirements are described as discrete intervals, probabilities and fuzzy sets. In this model, an interval stochastic fuzzy programming model is used to support quantitative optimization under uncertainty. Complexities in land-use planning systems can be systematically reflected, thus applicability of the modeling process can be highly enhanced. The proposed method is applied to planning land use/ecological balance in Poyang Lake watershed, China. The objective of the ISFP is maximizing net benefit from the LUA system and the constraints including economic constraints, social constraints, land suitability constraints, environmental constraints, ecological constraints and technical constraints. Modeling results indicate that the desired system benefit will be between [15.17, 18.29] × 10¹² yuan under the minimum violating probabilities; the optimized areas of commercial land, industrial land, agricultural land, transportation land, residential land, water land, green land, landfill land and unused land will be optimized cultivated land, forest land, grass land, water land, urban land, unused land and landfill will be [228234, 237844] ha, [47228, 58451] ha, [20982, 23718] ha, [33897, 35280] ha, [15215, 15907] ha, [528, 879] ha and [1023, 1260] ha. These data can be used for generating decision alternatives under different scenarios and thus help decision makers identify desired policies under various system-reliability constraints of ecological requirement and environmental capacity. Tradeoffs between system benefits and constraint-violation risks can be tackled. They are helpful for supporting (a) decision of land-use allocation and government investment; (b) formulation of local policies regarding ecological protection, environment protection and economic development; (c) analysis of interactions among economic benefits, system reliability and ecological requirements.

Since the goals of carbon peaking and carbon neutrality have been established, forest carbon sinks have garnered significant attention. As a fundamental component of forest carbon sinks, the quality of forest land significantly influences the carbon sink capacity of forests. This study utilized Kaizhou District, Chongqing City, a typical forest area as a case study, and used the correction method, factor method, CASA model, landscape ecology indexes, and canonical correlation analysis to evaluate the level of forest land quality and reveal the spatial distribution pattern and influencing mechanisms of forest land quality. The results showed that: (i) The quality index of public welfare forest land was distributed in [37.89, 148.15], and each quality level was diversified in space. The quality index of commodity forest land was distributed in [40.00, 92.67], and some high-quality forest land appeared in the transition zone of each region; (ii) The forest land quality index and the amount of net primary productivity passed the correlation test. Primary net productivity was higher on forest land with a high-quality index and lower on forest area with a low-quality index; (iii) public welfare forest land was mainly positively affected by community structure, average annual precipitation, average annual temperature, and soil moisture. Commodity forest land was mainly positively affected by average annual temperature, soil moisture, and slope aspect. However, landform had a significant negative impact on the two types of forest land. Given these findings, we also proposed a series of measures aimed at promoting the sustainable development of research on regional forest land.