江苏省人口产业结构与环境污染的关系研究

对江苏省1990年至2003年人口产业结构及环境污染的指标进行量化分析研究，建立了江苏省人口产业结构与环境污染之间的关系模型，并对影响污染物排放量的人口产业指标进行了分析。     

山东省人口重心迁移研究

采用人口重心模型,在GIS技术支持下着重对1989-2005年山东省人口重心迁移特征进行了研究,并在此基础上分析人口重心迁移的主要影响因素。结果显示,山东省人口重心接近几何中心,人口重心自东北向西南方向迁移的趋势明显,其移动轨迹呈现出一定的曲折和波动。山东省人口重心迁移受自然、社会经济和政策等多种因素的影响。     

基于加权平均增长法的人口预测模型在土地利用规划中的应用

通过对加权平均增长法、回归方程法及灰色系统法等3种人口预测模型特点的分析比较,分别建立模型对田阳县的人口发展进行了计算和预测。测算出加权平均增长法的预测结果与其人口发展的实际最为接近,得出加权平均增长法是土地利用规划工作中比较理想的人口预测方法。     

人口—产业—资源协同发展对贫困的影响研究——以湖南武陵山片区为例

基于2006—2015年湖南武陵山片区33个县市区的面板数据,构建子系统有序度模型和复合系统协同度模型,选择系统序参量,对该地区的人口、产业和资源的协同发展水平进行测度,利用ArcGIS10.4软件对协同发展水平的时空格局进行分析,再结合计量模型实证检验协同发展水平对贫困的影响。研究结果表明:湖南武陵山片区的人口—产业—资源协同发展水平持续提高,但片区内各县市人口—产业—资源协同发展水平的增长速度存在较大的差异,区域整体协同发展程度不高。计量分析结果表明,人口—产业—资源的协同发展对贫困减缓有显著的正向影响。根据研究结论,提出提高人口—产业—资源协同发展水平以提高扶贫效率的相关政策建议。     

人口城镇化与经济增长、生态环境关系的实证分析

随着我国城镇化进程加快,转变经济增长方式、加强生态环境保护日益受到人们的关注。通过构建生态环境指标体系,对广东省韶关市人口城镇化率与人均GDP、人口城镇化率与生态环境综合得分运用单位根检验、协整检验、Granger因果关系检验,建立回归模型进行实证分析。结果表明,人口城镇化并不是韶关经济增长的主要原因,人口城镇化与生态环境之间存在负影响。因此,加快新型城镇化建设的步伐对韶关市具有重要意义。     

陕西省人口城镇化与土地城镇化动态耦合研究

以陕西省10个地级市为研究对象,运用熵值法构建了人口城镇化与土地城镇化时空耦合协调发展的测度指标体系,利用时间序列线性回归模型和耦合协调发展度模型对2003—2014年陕西省人口城镇化与土地城镇化的耦合时空特征与空间分异特征进行研究。结果表明:1人口城镇化与土地城镇化耦合协调不断优化完善,但城市之间差异明显,中心外围发展模式明显。2耦合协调发展水平接近的城市空间集聚现象明显。3由于经济发展水平、交通基础设施水平、政策导向等因素影响,导致陕西省人口城镇化与土地城镇化耦合协调发展度空间分异。     

长江中游地区人口分布特征及其影响因素

人口分布受到自然本底要素和社会因素等方面的约束，研究人口分布特征及其影响因素，有助于增强对区域人地关系的理解。本文基于第五、六、七次县级尺度的人口普查数据，结合重心分析、标准差椭圆、热点分析等方法分析长江中游地区人口分布及集聚特征，利用地理加权回归模型探究不同因素对人口分布的影响特征。结果表明：(1)长江中游地区人口重心向东南方向迁移，方向变化不明显，且人口分布呈现“多核心”格局，聚集趋势加强。(2)2000—2020年长江中游地区人口分布热点趋于集聚，冷点变化不明显。(3)长江中游地区人口分布格局是地形条件、水资源条件、区位条件、经济水平等因素共同作用的结果。其中，离地级行政中心的距离对人口分布的影响最大，河网密度次之，然后是坡度和人均GDP，不同因素对人口分布的影响具有时空异质性。     

多维度高质量城镇化对能源消费碳排放的传导机制研究

碳排放研究一直是国际气候变化领域研究的热点,高质量的城镇化有利于碳排放减少及全球气候变化减缓。本文从人口、土地、经济三个维度构建高质量城镇化评价指标体系,对2005—2019年中国30个省域的高质量城镇化水平进行评价,在理论机制分析的基础上利用中介效应模型验证了三个维度高质量城镇化对能源消费碳排放的中介效应。结果表明：不同维度的高质量城镇化水平对碳排放的影响不同,当前的人口高质量城镇化具有显著碳减排效果,经济高质量城镇化也具有一定碳减排作用,但现阶段土地高质量城镇化增加了碳排放;不同维度的高质量城镇化与能源消费碳排放之间存在不同的作用机制。具体而言,劳动力结构转型在人口高质量城镇化与碳排放间不存在中介效应,土地财政在土地高质量城镇化与碳排放间存在完全中介效应,经济集聚在经济高质量城镇化与碳排放间存在遮掩效应。     

中国城市空气污染对人口流动的推拉效应研究

传统城市发展理论认为,空气污染会导致人口流出。然而,本文以城市雾霾数据为例,分类别构建固定效应模型后发现,空气污染会促进百强城市的人口净流入(形成拉力效应),非百强城市的人口净流出(形成推力效应)。拉力效应与传统的城市发展理论不符。本文认为,当城市间收入差距过大时,流入居民会形成高水平的收入预期,促使其愿意承受更严重的空气污染,该预期可量化为空气污染的拉力效应。据此进一步研究收入水平对推拉效应的调节作用发现,随着收入水平上升,其能放大百强城市的拉力效应和非百强城市的推力效应,即进一步促进百强城市的人口净流入和非百强城市的人口净流出。在此基础上,本文对百强城市和非百强城市分别提出政策建议,以期能为我国区域协调发展、城镇化科学转型提供理论支持。     

生态足迹方法在中国应用的案例初探

生态足迹方法通过估算维持人类生存的自然资源消费量和同化人类产生的废弃物所需要的生态性生产空间面积大小,并与给定人口区域的生态承载力进行比较,衡量区域的可持续发展状况。本文介绍了生态足迹模型的理论依据和计算方法,从模型方法应用范围,计算所需资料和模型自身三方面分析了生态足迹方法在我国应用中存在的问题和方法本身的不足。详细分析和比较了生态足迹方法在我国不同省市及地区的应用案例,结果表明,经济比较发达地区很大程度上需要通过地区贸易从不发达地区输入生态足迹,因而加重了不发达地区的生态负担。     

Multicriteria Group Decision-making Model for Environmental Conflict Analysis in the Cape Region,Mexico

This paper is concerned with developing a model for group decision making under multiple criteria. The multiple criteria group decision making (MCGDM)problem involves a set of feasible land use patterns that are evaluated on the basis of multiple, conflicting and noncommensurate criteria by a group of individuals. The model integrates the Analytic Hierarchy Process (AHP) and an integer mathematical programming method. The former provides a tool for structuring the decision problem and determining land suitability for different socio-economicactivities (the uses of land), the latter is used to identify the land use pattern that maximizes consensus among interest groups. The model is used to analyze environmental conflict over land resource allocation in the Cape Region of Mexico.     

耕地保护面临的形势及其对策研究

通过运用SWOT分析法，对我国城乡生态经济交错区农地保护的外部环境的机会与威胁、内部环境的优势与劣势进行了战略分析，其目的在于寻找新形势下农地保护的正确战略决策，以解决我国吃饭与建设的矛盾，实现土地资源的可持续利用。通过研究得出：农地保护面临着严峻的国内外形势，政府应该扬长避短，积极应对。     

Land Resources Allocation Strategies in an Urban Area Involving Uncertainty: A Case Study of Suzhou,in the Yangtze River Delta of China

A large number of mathematical models have been developed to support land resource allocation decisions and land management needs; however, few of them can address various uncertainties that exist in relation to many factors presented in such decisions (e.g., land resource availabilities, land demands, land-use patterns, and social demands, as well as ecological requirements). In this study, a multi-objective interval-stochastic land resource allocation model (MOISLAM) was developed for tackling uncertainty that presents as discrete intervals and/or probability distributions. The developed model improves upon the existing multi-objective programming and inexact optimization approaches. The MOISLAM not only considers economic factors, but also involves food security and eco-environmental constraints; it can, therefore, effectively reflect various interrelations among different aspects in a land resource management system. Moreover, the model can also help examine the reliability of satisfying (or the risk of violating) system constraints under uncertainty. In this study, the MOISLAM was applied to a real case of long-term urban land resource allocation planning in Suzhou, in the Yangtze River Delta of China. Interval solutions associated with different risk levels of constraint violation were obtained. The results are considered useful for generating a range of decision alternatives under various system conditions, and thus helping decision makers to identify a desirable land resource allocation strategy under uncertainty.     

A land suitability model for the evaluation of land-use change

A land suitability model was developed to provide the planner with a quantitative tool for assessing the environmental limitations on proposed land-use changes in the area surrounding Lake Monroe in southern Indiana. The model incorporates a weighting procedure that allows the environmental evaluation of a decision to convert the present land use to another category. The data base for the model was assembled by a multidisciplinary team. A case study is included, which illustrates the advantages and limitations of the land suitability model as it is applied to the evaluation of a site for the Alumni Family Camp.     

A multicriteria model for planning agricultural regions within a context of groundwater rational management

Current international research focuses on topics like sustainable development, regional planning, environmental decision making and implementation, biodiversity conservation plus a number of other relevant issues, especially at times of economic crisis as today. Economic growth and environmental protection can go hand in hand, provided that decision makers develop and use tools and insights targeting in the implementation of successful and robust long term policies. This paper was developed in the framework of a European research project and implements a Multicriteria Mathematical Programming model that optimises the sustainable management of agricultural regions taking in account the available resources (land, labour, capital) and environmental parameters (agrochemicals, water consumption). The model achieves the optimum farm plan in the area combining different criteria to a utility function under a set of constraints and the spatial integration of the vulnerability maps of the regions into the model enables the regional authorities to design policies for the optimal agricultural development and the groundwater protection from the agricultural land uses. Furthermore, the model is used to simulate different scenarios and policies by the local stakeholders, due to changes on different social, economic and environmental parameters. In this way the decision makers can achieve alternative farm plans and agricultural land uses as well as to estimate economic, social and environmental impacts of different policies. The model has been applied to an agricultural region in Northern Greece and proved to be a valuable tool in the implementation of environmental policies and actions, especially in agricultural regions in a delicate balance as the study area.     

Optimal Land Use Management for Soil Erosion Control by Using an Interval-Parameter Fuzzy Two-Stage Stochastic Programming Approach

Soil erosion is one of the most serious environmental and public health problems, and such land degradation can be effectively mitigated through performing land use transitions across a watershed. Optimal land use management can thus provide a way to reduce soil erosion while achieving the maximum net benefit. However, optimized land use allocation schemes are not always successful since uncertainties pertaining to soil erosion control are not well presented. This study applied an interval-parameter fuzzy two-stage stochastic programming approach to generate optimal land use planning strategies for soil erosion control based on an inexact optimization framework, in which various uncertainties were reflected. The modeling approach can incorporate predefined soil erosion control policies, and address inherent system uncertainties expressed as discrete intervals, fuzzy sets, and probability distributions. The developed model was demonstrated through a case study in the Xiangxi River watershed, China’s Three Gorges Reservoir region. Land use transformations were employed as decision variables, and based on these, the land use change dynamics were yielded for a 15-year planning horizon. Finally, the maximum net economic benefit with an interval value of [1.197, 6.311] × 10⁹ $ was obtained as well as corresponding land use allocations in the three planning periods. Also, the resulting soil erosion amount was found to be decreased and controlled at a tolerable level over the watershed. Thus, results confirm that the developed model is a useful tool for implementing land use management as not only does it allow local decision makers to optimize land use allocation, but can also help to answer how to accomplish land use changes.     

一类市场营销调控模型研究

利用最优控制充分条件 ,对一类市场营销最优控制模型进行了分析研究 ,最后改进并得出了与实际相符的市场营销调控模型 ,为企业最优广告策略和最优寿命提供了决策支持信息。     

Modelling land use change and environmental impact

Land use change models are tools for understanding and explaining the causes and consequences of land use dynamics. Recently, new models, combining knowledge and tools from biophysical and socio-economic sciences, have become available. This has resulted in spatially explicit models focussed on patterns of change as well as agent-based models focused on the underlying decision processes. These developments improve the use of land use change models in environmental impact studies. This special issue documents these developments: (i) analysing the system properties in a biophysical and socio-economic context at multiple scales; (ii) integrating spatially explicit land use change models in integrated assessment models; (iii) visualising and quantifying the potential effects of land use change in trade-off curves, to support land users and policy makers in their decisions; and (iv) modelling of the actual decision making process with agent-based modelling. A new promising future development is the incorporation of dynamic feedbacks between changing land use and changing environmental conditions and vice versa. Unfortunately such dynamic feedbacks between the socio-economic and biophysical model components are still not or only partially operational in current models and are therefore the most important challenge for land use and environmental modellers.     

Assessment of Economic and Water Quality Impacts of Land Use Change Using a Simple Bioeconomic Model

The objective of this study is to assess the economic and water quality impact of land use change in a small watershed in the Wiregrass region of Alabama. The study compares changes in water quality and revenue from agricultural and timber production due to changes in land use between years 1992 and 2001. The study was completed in two stages. In the first stage, a biophysical model was used to estimate the effect of land use change on nitrogen and phosphorus runoff and sediment deposition in the main channel; in the second stage, farm enterprise budgeting tools were used to estimate the economic returns for the changes in land use condition. Both biophysical and economic results are discussed, and a case for complex optimization to develop a decision support system is presented.     

Indivisibility and divisibility in land development over time and under uncertainty

The quasi-option value (QOV) literature originated by Arrow et al. (Arrow, K.J., Fisher, A.C., 1974. Environmental preservation, uncertainty, and irreversibility. Quarterly Journal of Economics 88, 312-319) and by Henry (Henry, C., 1974. Option values in the economics of irreplaceable assets. Review of Economic Studies 41, 89-104) is largely concerned with the analysis of two-period models of land development. Our paper extends this literature by analyzing two scenarios in which the decision to develop land is made in a multi-period and stochastic framework. In the first scenario, the development decision is indivisible. In contrast, in the second scenario, the development decision is divisible. Specifically, we study the properties of the indivisible development decision when there is a time constraint on when land is to be developed. We then analyze the ways in which the divisible land development decision depends on the extent of a landowner's landholding and on the number of development opportunities awaiting this landowner.