基于PLUS和InVEST模型的渭河流域土地利用与生境质量时空变化及预测

生境质量是关系人类福祉和实现可持续发展的重要基础,对区域生态保护和土地资源可持续利用具有重大意义。以渭河流域为研究对象,基于2000、2010年和2020年的土地利用数据,应用斑块生成土地利用变化模拟（Patch-generating land use simulation,PLUS）模型、生态系统服务和权衡的综合评估（Integrated valuation of ecosystem services and trade-offs,InVEST）模型预测并评价了土地利用与生境质量时空变化特征。结果表明：（1） 2000—2020年渭河流域建设用地和草地面积逐年增加,林地面积略微增长,耕地面积持续减少;2020—2050年土地利用变化趋势同2000—2020年基本一致但剧烈程度显著下降,建设用地扩张趋势减缓,耕地减少幅度下降,草地面积占比超过耕地跃居流域第一。（2） 2000—2020年流域内生境质量两极分化趋势明显,低生境质量和高生境质量区域面积有所增加,中等生境质量的面积减少,整体生境质量水平呈上升趋势;2020—2050年生境质量水平继续保持逐年上升趋势但增幅放缓,生境质量变化强度下降,低生境质量区域面积逐渐减少,中等生境质量面积保持稳定,高生境质量面积有所增长。研究结果可为渭河流域土地资源可持续利用和高质量发展提供相应科学依据和决策参考。     

A land-use-based modelling chain to assess the impacts of Natural Water Retention Measures on Europe’s Green Infrastructure

This article details the process of integrating models to answer a specific policy-driven question: ‘What could be the impact of proposed Natural Water Retention Measures (NWRMs) on Europe’s Green Infrastructure (GI)?’ It describes the new Land Use Modelling Platform (LUMP), now enabling a high spatial scale (100-m) and large coverage (pan-European), whereby several sector-specific models contribute to assessing the impact of regional-level policy on a given spatial topic of concern. The configuration (land claims and land allocations modules) and calibration (accessibility and biophysical suitability) of the LUMP are explained. Four NWRM scenarios (riparian areas, afforestation, grassland and baseline scenario) are configured to run the simulations. For the reference: year 2006, the spatial representation of GI is based on land-use features of a refined version of the CORINE Land Cover (CLC), and resumed as connected components made of nodes and links.

Mathematical morphological image processing and network graph theory model, available from the free software package GUIDOS (the Joint Research Center of the European Commission), enabled the measurement of the GI connectivity and identified most critical links. Results show that the competition for land claimed by different economic sectors, combined with policy-driven rule-sets for the implementation of different NWRMs, yields very different results for the 2030 land-use projections, and subsequently for the morphology of GI. Three indicators associated with the morphology of GI are computed in order to assess the model outputs for 2030. The indicators are computed to answer the following questions: (1) How is the quantity of GI affected by each of the NWRM, and what proportion of that GI is most valuable? (2) What is the location of the most critical nodes and connectors of GI, and what land-use conversions occur under these? (3) Are the average components getting larger or smaller?

Whereas the grassland measure results in the largest net increase of GI, the afforestation measure results in the overall largest number of hectares of key nodes and links within the network. Land conversions occur under the critical GI nodes and links, with a large increase in agricultural areas, especially for the riparian measure under critical nodes and the grassland measure under critical links. Also predominant is the swapping of land from pasture to forest under critical links with the afforestation measure. The riparian measure most increases the average size of GI components, and all three measures contribute to bridging two large components which were divided in the 2006 land-use map, thus increasing the size of the largest component by more than 50%.     

A total water management analysis of the Las Vegas Wash watershed,Nevada

Climate change, land-use change, and population growth are fundamental factors affecting future hydrologic conditions in streams, especially in arid regions with scarce water resources. Located in the arid southwest within the Las Vegas Wash watershed, Las Vegas is one of the fastest growing metropolitan areas of the country. In the past 30?years, because of climate and land-use changes, it has experienced a decrease in clean water supply but an increase in water demand. To alleviate some of these problems, large amounts of water have been pumped into the city from different sources, such as Lake Mead, and the urban wastewater is treated and returned back to the reservoir for water augmentation. However, in the face of continual global climate change and urbanization in the watershed, long-term planning for sustainable water management is critical. This research was designed to provide a comprehensive analysis incorporating hydrologic modeling, population projection, land-use change modeling, and water management policies to examine the total water balance and management options in this arid and rapidly urbanizing watershed under various scenarios of climate regime, population growth, land-use change, and total water management programs for the year 2050.     

广州市土地利用结构优化配置及其潜力

基于广州市土地利用结构、地区经济、生态与社会特点,结合广州城市总体规划(2010-2020),对广州市域土地利用结构进行生态经济效益-自然生态效益导向的多目标优化配置研究。结果表明：对广州市土地利用数量结构进行调整,一定时间内能够满足地区可持续发展;但是,土地仍然承担着巨大的压力,焦点是建设用地和农用地之间的数量转变,以耕地为主,也包括对未利用土地的利用;土地利用潜力度模型结果显示,通过优化土地利用结构,土地系统的协调度增大而潜力度减小：在生态经济效益目标下,潜力度分别为0.628～0.661,0.372～0.339;在自然生态效益目标下,分别为0.531～0.782,0.469～0.218,表明土地利用系统将趋于更高的协调状态,而其数量结构优化配置的潜力减小,优化各产业部门内部土地资源结构及其空间布局,将是广州市土地资源高效集约利用和进一步挖潜的主导方向。     

A CA-based land system change model: LANDSCAPE

Cellular automata (CA) models are widely used to simulate land-use changes because of their simplicity, flexibility, intuitiveness and ability to incorporate the spatial and temporal dimensions of processes. A small number of CA-based models have been developed to simulate changes in multiple land uses, most of which use the hierarchical allocation strategy and/or inertia factors to enable these CA models to do so accurately. However, only some of these models allow explicit determination of the allocation sequence for active land uses according to the hierarchical allocation strategy and the objective calculation of inertia factors. In this paper, we proposed a CA-based model, i.e. the LAND System Cellular Automata model for Potential Effects (LANDSCAPE), with a hierarchical allocation strategy and resistances, to simulate changes in multiple land uses. Furthermore, we introduced effective ways to objectively determine the allocation sequence for active land uses and calculate resistances for individual land uses. The results show that the LANDSCAPE model, with a calibrated allocation sequence and resistances, is reliable and accurate for simulating multiple land-use changes.     

基于高分辨率遥感影象的城市泥石流灾害损失评估

文章探讨了城市泥石流灾害损失评估的系统方法,该方法包括了泥石流堆积泛滥区危险区划、城市土地覆盖类型遥感解译、损失评估模型构建和价值核算4个主要内容。以美国高分辨率的"快鸟"卫星影象为数据源完成了研究区的土地覆盖类型遥感解译,根据泥石流危险程度和土地覆盖类型特征,构建了城市泥石流灾害的损失评估模型。最后,应用GIS提供的分析工具完成了研究区不同土地覆盖类型的泥石流灾害损失计算和评价。     

Simulating urban land-use changes at a large scale by integrating dynamic land parcel subdivision and vector-based cellular automata

Cellular automata (CA) have been widely used to simulate complex urban development processes. Previous studies indicated that vector-based cellular automata (VCA) could be applied to simulate urban land-use changes at a realistic land parcel level. Because of the complexity of VCA, these studies were conducted at small scales or did not adequately consider the highly fragmented processes of urban development. This study aims to build an effective framework called dynamic land parcel subdivision (DLPS)-VCA to accurately simulate urban land-use change processes at the land parcel level. We introduce this model in urban land-use change simulations to reasonably divide land parcels and introduce a random forest algorithm (RFA) model to explore the transition rules of urban land-use changes. Finally, we simulate the land-use changes in Shenzhen between 2009 and 2014 via the proposed DLPS-VCA model. Compared to the advanced Patch-CA and RFA-VCA models, the DLPS-VCA model achieves the highest simulation accuracy (Figure-of-Merit = 0.232), which is 32.57% and 18.97% higher respectively, and is most similar to the actual land-use scenario (similarity = 94.73%) at the pattern level. These results indicate that the DLPS-VCA model can both accurately split the land during urban land-use changes and significantly simulate urban expansion and urban land-use changes at a fine scale. Furthermore, the land-use change rules that are based on DPLS-VCA mining and the simulation results of several future urban development scenarios can act as guides for future urban planning policy formulation.     

Multi-criteria, multi-objective and uncertainty analysis for agro-energy spatial modelling

The worldwide increase in the use of biomass as a Renewable Energy Source raises the issue of introducing crops dedicated to energy production into rural landscapes. The purpose of this paper is to set-up a GIS based multi-criteria approach to assess a range of possibilities for perennial energy crops conversion. The presented method was implemented at the regional level in the Yorkshire and the Humber Region in Northern UK. The first phase of the study aims to set-up a land capability model for the specific purpose of assessing the potential of different typologies of perennial energy crops, on the basis of specific pedo-climatic and topographic factors. The model output illustrates a range of potentials for energy crop conversion that can be explored in the given landscape. In the second phase a uncertainty analysis of the land capability model was performed through a simulation approach in order to interpret the influence of assumptions and uncertainty on input data and model parameters. The last phase of the study allows allocating the energy crop conversion area according to specific environmental constraints, nature protection targets, food production priorities and land capability values. The land allocation output gives a rather restrictive energy crop penetration scenario, where more than half of the conversion area is allocated to cropping systems with low land degradation potential. This scenario represents a preliminary regional analysis of the energy crop potential in terms of theoretically available conversion areas. The final results also show that the areas with highest environmental risks correspond to the areas with both the lowest suitability for energy crop cultivation and the highest model uncertainty.     

An analysis of 200-year-long changes in a landscape affected by large-scale surface coal mining: History,present and future

We have investigated almost 200 years of landscape transformations in a traditional brown coal mining region in northwest Bohemia, Czech Republic. The investigation was focused on the central part of the North Bohemian Basin including 44 cadastral areas representing a total area of 228.48 km². Within this area, an analysis of land use in six different time periods (1845, 1954, 1975, 1989, 2010, 2050) was performed. The analysis therefore includes the transitory period of a boom and slow-down of surface coal mining and also provides a unique comparison with the planned future condition of the landscape after the year 2050, when the mines have been closed down and the landscape restored. Practically all available geographic data resources on land use have been used – the stable cadastre, topographic maps, current landscape mapping and aerial photographs. We differentiated twelve land-use categories. Both Friedman test and detrended correspondence analysis show significant differences in the representation of individual land-use categories and characteristics of the landscape before and during mining operations and after their discontinuance and revitalisation of spoil tips and in residual pits. For a long period of time, agricultural landscape was changed into an industrial one. The basin part of the studied territory almost completely lacks eco-stabilising features that could be used as a basis for planning of a new landscape. This is because the original landscape had been intensively used for agriculture previously, and almost one half of the territory was over-exploited and other areas were affected by operation facilities and coal processing industrial plants. With the growing number of reclamation projects, the diversity of the landscape has been increasing, as well as the proportion of ecologically valuable elements (mostly forests and water bodies), whose total area could exceed 70% of the landscape's surface in the future, approximating its characteristics to a natural landscape with a high degree of ecological stability.     

北京市土地利用空间格局演化模拟及预测

土地利用空间格局的演化模拟可定量地从空间尺度揭示区域土地利用变化的驱动因素,是厘清未来时期内土地变化的重要途径。基于CLUE-S模型,以北京市为研究案例,结合1985、2000和2010年三期土地利用数据,运用Logistic逐步回归方法识别了北京市各种土地利用类型演化的驱动因素,对北京市土地利用空间格局进行模拟。在此基础上,基于北京市社会经济发展、土地利用规划、资源禀赋及生态保护等不同情景,对北京市2020年土地利用空间分布格局进行模拟及预测。结果表明：①不同的时期内,驱动因子对不同土地利用类型的影响呈现差异性,其中交通因素及社会经济因素对土地利用类型的转化率影响较显著,坡度对各个土地利用类型的影响较大。②通过对2010年北京市土地利用变化的模拟结果来看,Kappa指数为87.03%,说明预测结果与实际土地利用情况有较好的一致性。③预测结果显示,北京市的城市发展均表现为继续向外扩展,且以东南、东北为主要扩展方向,但扩张的程度存在差异。     

河北省建设全面小康社会资源约束分析

随着人口增加、工业化和城市化进程的加快,资源需求量大幅上升,经济社会发展与资源供给的矛盾越来越突出。该文从全面建设小康社会目标角度分析河北省2020年水、耕地、能源等资源的需求量和可供量,得出河北省水资源的压力最大,其次是土地和能源,并提出加快资源节约型社会建设的措施。     

基于GIS的城市用地布局多情景模拟与方案评价——以江苏省太仓市为例

用地布局一直是城市总体规划中的关键难题,以往的规划方案多凭借规划师的经验判断、简单的图层叠加和有限的公众参与生成。然而新的城乡规划法要求从多角度综合考虑城乡用地布局问题,更加注重规划过程的科学性和准确性,也就特别需要有一种适应多情景分析下的城市用地布局模拟与方案评价方法。文章以江苏省太仓市为例,借助GIS技术的强大空间分析功能,探讨了这种方法的技术流程：① 参考已有的大尺度城市未来模型,结合我国特别是研究区的区域特点,构建一个实用的城市未来模型(Urban Future Model,UFM);② 通过用地评价、战略归纳、情景模拟等步骤,生成若干个可选的用地布局模拟方案;③ 应用多目标达成矩阵法从粮食、生态、灾害等多个角度对这些方案进行综合评价,并根据评价结果选择一个最佳方案作为本轮总规用地布局的规划参考方案。     

中国北方未来50年土地利用变化模拟

1 IntroductionLand use m odelling is a useful tool to analyze the land use cause, process and result, torecognize the im pact of land use system change on ecological environm ent,and to support theland use planning and policy (IIA SA ,1998;Costanza etal.,…     

广东冬季气候资源优势及寒害与对策

本文论述了广东冬季气候资源的优势及冬季寒害的两重性，分析了近两年寒害对农业生产的影响，在些基础上，提出了防御寒害的综合对策。     

Modelling scenarios of land use change in northern China in the next 50 years

Modelling scenarios of land use change and their impacts in typical regions are helpful to investigate the mechanism between land use and ecological systems and process the land use allocation under the ecological security. A system dynamics (SD) model with the aim to modelling scenarios of land use change and assessing ecological impact in northern China in the next 50 years is developed here. The accuracy assessment with the historic data from 1990 to 2001 indicated the SD model is robust. After the different "what-if" scenarios controlled by GDP, population, market, and technology advancement were built, the different scenarios of land use change in northern China from 2000 to 2050 were simulated with their ecological impact assessed. The result suggested that such factors as GDP, population, market and technology have a strong relationship with land use structural change in northern China. It also indicated that such measures as strict controlling of population increase, importing some food to keep the supply-demand balance in the region, and improving agricultural technology will be the guarantee of regional sustainable development with fast economic growth and the obvious land use structural improvement at the same time.     

Multi-label class assignment in land-use modelling

During the last two decades, a variety of models have been applied to understand and predict changes in land use. These models assign a single-attribute label to each spatial unit at any particular time of the simulation. This is not realistic because mixed use of land is quite common. A more detailed classification allowing the modelling of mixed land use would be desirable for better understanding and interpreting the evolution of the use of land. A possible solution is the multi-label (ML) concept where each spatial unit can belong to multiple classes simultaneously. For example, a cluster of summer houses at a lake in a forested area should be classified as water, forest and residential (built-up). The ML concept was introduced recently, and it belongs to the machine learning field. In this article, the ML concept is introduced and applied in land-use modelling. As a novelty, we present a land-use change model that allows ML class assignment using the k nearest neighbour (kNN) method that derives a functional relationship between land use and a set of explanatory variables. A case study with a rich data-set from Luxembourg using biophysical data from aerial photography is described. The model achieves promising results based on the well-known ML evaluation criteria. The application described in this article highlights the value of the multi-label k nearest neighbour method (MLkNN) for land-use modelling.     

LUCC驱动力模型研究综述

驱动力研究是土地利用变化研究中的核心问题。土地利用变化驱动力模型是分析土地利用变化原因和结果的有力工具，模型通过情景分析可为土地利用规划与决策提供依据。基于不同理论的驱动力研究方法很多，论文选取了几种国内外应用较多的LUCC驱动力模型进行综述，分析了每个模型的优缺点及适用范围，最后得出结论：1) 基于过程的动态模型更适于研究复杂的土地利用系统。2) 基于经验的统计模型能弥补基于过程的动态模型的不足。3) 基于不同学科背景的模型进一步集成将是LUCC驱动力模型未来的发展趋势。     

最优增长路径下的中国碳排放估计

从能源消费、水泥生产和森林碳汇3 个方面对中国未来的碳排放进行了较为全面的估计。其中,能源消费碳排放是在能源-经济框架下利用经济动力学模型对最优经济增长路径下的能源需求进行预测得到的,同时考虑了能源结构的演化及不同能源品种在碳排放系数上存在的差异;水泥生产碳排放则是在对水泥产量预测的基础上进行的,认为水泥产量与城市化进程存在一定的联系,而城市化进程遵循“S曲线”发展规律;森林碳汇是通过引入CO2FIX模型,分别对原有森林与新增可造林的固碳能力进行估算,最终合成了中国未来的净碳排放曲线。结果发现,能源消费碳排放在2031 年达到高峰,为2637 MtC,对应的人均GDP低于OECD国家的实证经验;人均排放高峰出现在2030 年,为1.73 tC/人,远低于美国欧盟和日本2006 年水平;水泥生产碳排放增长放缓,2050 年控制在254 MtC左右,占工业总排放的12%;森林碳汇至2050 年可累计吸收6806.2 MtC,年吸收量逐渐下降;净排放也于2033 年达到峰值,为2748 MtC。     

基于数理统计的快速城市化时期土地利用变化分析——以大连市为例

基于数理统计的快速城市化时期土地利用变化分析试以土地系统理论为基础,运用数理统计方法,建立1996—2005年各类用地数量变化数据库,分析大连市各类用地时空变化规律,预测未来用地规模。采用吉布斯一马丁（Gibbs—Mirtin）多样化指数和洛伦兹（Lorenz）曲线分析大连市各类用地的数量结构特点,利用二次指数平滑方法预测出2010～2020年大连市各类用地规模。结果表明,1996年以来全市建设用地面积呈上升趋势,农业用地和未利用地面积呈缓慢下降态势,但就经济增长的规模看,未来大连的经济发展不会始终保持之前的增长态势,建设用地的需求量也将有所缩减。     

Review on carbon emissions,energy consumption and low-carbon economy in China from a perspective of global climate change

Accompanying the rapid growth of China’s population and economy, energy consumption and carbon emission increased significantly from 1978 to 2012. China is now the largest energy consumer and CO₂ emitter of the world, leading to much interest in researches on the nexus between energy consumption, carbon emissions and low-carbon economy. This article presents the domestic Chinese studies on this hotpot issue, and we obtain the following findings. First, most research fields involve geography, ecology and resource economics, and research contents contained some analysis of current situation, factors decomposition, predictive analysis and the introduction of methods and models. Second, there exists an inverted “U-shaped” curve connection between carbon emission, energy consumption and economic development. Energy consumption in China will be in a low-speed growth after 2035 and it is expected to peak between 6.19–12.13 billion TCE in 2050. China’s carbon emissions are expected to peak in 2035, or during 2020 to 2045, and the optimal range of carbon emissions is between 2.4–3.3 PgC/year (1 PgC=1 billion tons C) in 2050. Third, future research should be focused on global carbon trading, regional carbon flows, reforming the current energy structure, reducing energy consumption and innovating the low-carbon economic theory, as well as establishing a comprehensive theoretical system of energy consumption, carbon emissions and low-carbon economy.