基于元胞自动机的城市生态安全格局模拟——以东莞市为例

以城市化快速发展的东莞市为研究对象,选取景观生态安全程度为评价标准,获取生态安全的元胞1 km×1 km范围内的城市化元胞数,将其嵌入元胞自动机(CA)转换规则中作为约束条件,控制城市发展,建立生态安全的城市CA,模拟生态安全的城市发展形态.结果表明: 东莞市综合景观生态安全指数从1988年的0.497降低到2005年的0.395,景观尺度上的生态安全下降.利用生态安全的CA模拟的2005年东莞市生态安全指数由实际的0.395增加到0.479,模拟的城市景观生态压力减小、生态安全状态和综合景观生态安全程度提高.CA可以作为探索生态安全城市研究的有效工具.     

基于CA-Markov模型和多目标优化的大连市土地利用格局

运用马尔科夫转移矩阵、多准则评估以及元胞自动机耦合的CA-Markov模型,基于1990、2000、2010年土地利用图、地形因子和地理要素等,模拟大连市未来土地利用景观格局变化趋势.基于大连市土地利用结构、经济社会、自然环境等特点,结合大连市城市总体规划和土地利用规划,建立经济、社会、环境3个目标导向的模糊多目标优化模型,优化配置了大连市未来土地利用格局.结果表明:1990-2010年,大连的快速发展呈现出建设用地持续扩张而耕地、林地面积缩小的特点,以现有城市化速度发展,到2020年大连市景观格局土地覆盖将发生很大变化,景观破碎化程度将加剧.优化调整土地利用数量结构,能满足未来大连可持续发展的要求.     

辽中地区矿业城市土地利用变化

辽中地区矿业城市是我国重要的能源生产和重工业基地,研究其土地利用变化有利于改善环境质量,提高土地利用效率。分析了1985—2000年鞍山、抚顺、本溪土地利用变化指数、土地利用变化程度综合指数、土地利用结构信息熵、土地利用景观指数及其驱动力。结果表明:辽中地区矿业城市土地利用变化整体上呈现耕地、建设用地增加,林地、草地减少的趋势;不同矿业城市变化率最大的土地类型均不相同,鞍山为建设用地,增加5.45%;抚顺为水域,增加3.19%;本溪为草地,减少7.29%。土地利用程度变化综合指数均为正值,且鞍山>本溪>抚顺;土地利用结构信息熵均呈增长趋势,2000年鞍山为0.603,抚顺为0.406,本溪为0.407;景观破碎化程度加大,破碎度为鞍山>本溪>抚顺,景观多样性指数较高,景观结构复杂,景观多样性和均匀性均为鞍山>抚顺>本溪;自然条件的差异是土地利用变化差异的基础,人类社会经济活动和政策法规是土地利用变化的主要驱动力。     

生态安全条件下土地利用格局优化——以皇甫川流域为例

在人类活动导致的生态环境问题中,土地利用格局变化对区域生态安全起着决定性作用。选择我国乃至在世界上都罕见的多沙、粗沙、强烈水土流失的黄河皇甫川流域作为研究区域,针对土壤侵蚀和生态用水这两大影响流域生态安全的关键问题,开展土地利用变化模拟、土壤侵蚀3S监测、适宜植被盖度估算、土壤侵蚀情景模拟、土地利用格局优化等方面的综合研究。结果表明:(1)土地利用格局变化是导致土壤侵蚀变化的重要因素。从1987年到2015年,建筑用地、林地和灌丛面积增加,水域、沙地和裸砒砂岩面积减少,导致流域年平均土壤侵蚀模数由16160.72 t km-2a-1降至9710.72 t km-2a-1。(2)土地利用类型与土壤侵蚀模数密切相关并存在一定规律。6种不同土地利用类型多年平均土壤侵蚀模数的大小顺序为:裸砒砂岩沙地耕地草地林地灌丛,表明灌、林措施是流域植被恢复和土壤侵蚀减少的首选。(3)土地利用结构和空间格局优化有助于提升区域生态安全水平。在优化格局下,2007年和2015年土壤侵蚀模数比优化前分别减少5469.57 t km-2a-1和5432.77 t km-2a-1,优化后2015年土壤侵蚀模数仅为4277.95 t km-2a-1,低于流域自然侵蚀临界值或允许土壤侵蚀模数5300 t km-2a-1,优化土地利用格局成为加强流域生态环境建设的重要途径。     

基于智能体模型的土地利用动态模拟研究进展

土地利用动态变化是全球变化和可持续发展研究的基础,对区域水循环、大气循环、环境质量、气候变化及陆地生态系统生产力等具有重要影响,也是造成生物多样性衰减的最主要原因.目前,建立于复杂性科学基础上的的智能体模型(ABM)成为土地利用动态模拟的重要方法.智能体模型能模拟个体或群体的行为及决策模式,从而能将政府、城市规划、房地产开发商、住户等社会群体及个人对土地利用产生的影响进行模拟,同时能对不同社会经济政策对土地动态影响进行模拟.智能体模型在元胞自动机基础上,加入了人为因素的智能体概念,从而能更好地模拟土地动态.在分析总结了智能体模型的相关概念和组织结构,并分析了其在土地利用动态、城市动态模拟及生态过程模拟等方面的应用与元胞自动机的关系,比较了常用的智能体模型的主要软件,最后概括了智能体模型优点、发展趋势及存在的主要问题.     

土地利用变化模拟研究进展

土地利用变化研究经历了近30年的快速发展,学者基于不同建模目标构建出多种土地利用变化模型,实现了从数量模拟到时空格局模拟,从单一模型向多种模型耦合的跨越。当前研究主要在元胞自动机(Cellular Automata,CA)模型和CLUE-S (Conversion of Land Use and its Effects at Small region extent)模型的基础上进行改进,马尔科夫模型、系统动力学(System Dynamics,SD)模型、Logistic回归和随机森林等均可计算CA模型和CLUE-S模型中所需的土地利用需求,多标准评价、地理加权回归、多主体模型以及人工神经网络等方法也多被用于CA模型的扩展,而CLUE-S的改进则存在模型本身系列的升级。这些模型广泛应用于各种区域和尺度土地利用变化预测实例研究并研发软件系统和数据集。驱动力分析主要从自然因素与人文因素两方面进行,人文因素是引发土地利用变化的主要因素。在目前的研究中,由于技术手段的限制,仍然存在时空尺度、数据误差、数据整合的不确定性等问题。未来土地利用变化模拟研究应进一步发挥大数据技术优势,推动土地利用变化模拟研究朝向精细化、多元化方向发展。结合生态环境领域实际问题,深挖土地利用变化与其生态环境效应之间的互馈机制,将研究视角从探究人类活动对土地利用变化的影响逐渐转向二者相互作用,最终促进人地关系协调发展。     

近50a土地利用变化对干旱区典型流域景观格局的影响——以新疆玛纳斯河流域为例

土地利用变化与景观格局间的相互作用机制是全球环境变化的研究焦点。大规模土地开发导致的土地利用变化及其对景观格局影响的定量评估对区域土地资源可持续利用具有重要意义。评价长时间尺度土地利用变化对干旱区典型流域景观格局的影响,以期为经济发展与生态环境保护政策的制定提供有益信息。选择的研究区新疆玛纳斯河流域是中国西北干旱区水土开发的典型代表区域。以1962年地形图,1976、1989、1999和2008年遥感影像为基础数据源,利用数学模型和景观格局指数重建土地利用和景观格局变化过程,并探讨了土地利用变化对流域景观格局的影响。结果表明:(1)近50a玛纳斯河流域土地利用变化剧烈,耕地和建设用地"涨势"显著,未利用地和林地"落势"较明显,草地和水域先"涨"后"落",土地利用变化整体处于不平衡态,单向转换频繁。(2)研究区景观破碎度和多样性增加,优势度减小,各景观类型间差异缩小,异质性程度和景观结构复杂性加大。(3)土地利用变化改变了流域景观格局,导致景观结构趋于多样化、均匀化和破碎化。最后,提出通过发展大规模集约化农业降低土地利用变化引起景观格局负面生态效应的观点。     

基于RUSLE-SMA的黄土丘陵沟壑区土壤侵蚀评价及景观格局分析——以庆城县蔡家庙流域为例

以甘肃省庆城县蔡家庙小流域为例,运用混合光谱线性分解(SMA)从Landsat遥感影像提取植被覆盖度,获取流域的植被覆盖因子,借助通用土壤侵蚀方程RUSLE计算了2003和2010年土壤侵蚀量,分析了土壤侵蚀与土地利用和地形因子之间的关系,并对流域土壤侵蚀景观格局变化进行了研究.结果表明:7年间,蔡家庙小流域土壤侵蚀量由3.61×106 t·a-1增加到4.48×106 t·a-1,增加了24％;平均侵蚀强度由8590.23 t·km-2增加到10652.01 t·km-2.不同土地利用类型的侵蚀状况差异较大,未利用地、草地、园地的侵蚀状况严重;坡度大于15°、高程低于1395 m以及坡向朝西的区域,土壤侵蚀较严重.研究区整体侵蚀景观高度破碎,斑块总数减少,破碎度变小,景观异质性减小,整体形状趋于规则;除微度侵蚀景观外,其余景观类型趋于简单化.     

集成灰色分析和元胞自动机用于景观动态模拟

针对景观生态系统"复杂性"的特点,采用灰色局势确定邻域转换规则,构建元胞自动机,用于模拟和分析景观生态动态变化.在信息不完全的情况下,提高了元胞自动机景观生态动态模型的可靠性和可行性.以中国云南省怒江流域中段作为实例,确定影响元胞转换规则的三因素主要有元胞邻域的聚集程度,土地适宜程度和人类活动影响程度,根据景观这一类复杂系统的动态变化特征其权重随地理空间位置和时间而变化,同时用Monte Carlo法考虑了模拟时转换的随机性.通过计算显示模拟未来发展的情景总的趋势是符合实际的,不但模拟了微观的景观单元的自组织机制,而且在一定程度上反映了宏观的社会经济因素影响,因而更具有针对性、典型性及准确性.     

寻乌水流域景观格局演变及其生态环境效应

土地利用变化引起的景观格局演变及其生态环境效应研究已成为诸多学者广泛关注的研究热点。为正确认识和评价土地利用变化对景观格局和生态环境的影响,以寻乌水流域为研究对象,选取1995、2005年Landsat5 TM影像和2015年Landsat8 OLI影像进行遥感解译,得到3期的土地利用数据,借助ArcGIS10.2和Frgstats4.2软件,分析土地利用动态变化与景观格局演变特征。同时运用遥感生态指数(RSEI)对寻乌水流域1995—2015年期间生态环境质量时空演变进行评价。结果表明:(1)近20年寻乌水流域园地(增加40.14%)和林地(减少33.91%)面积占比变化幅度最大,水域(减少0.1%)变化幅度最小。土地利用变化单向转换频繁,园地"涨势"和林地"落势"十分明显,整体处于不平衡状态。(2)景观水平上,流域的香农多样性指数(SHDI)、修正Simpon均匀度指数(MSIEI)分别由1995年的0.7083、0.2423上升至2015年的1.114、0.5247,景观聚集度指数(CONTAG)由1995年的72.93下降至2015年的58.13。流域的景观异质性增强,破碎化程...     

Modelling the effect of urbanization on the transmission of an infectious disease

This paper models the impact of urbanization on infectious disease transmission by integrating a CA land use development model, population projection matrix model and CA epidemic model in S-Plus. The innovative feature of this model lies in both its explicit treatment of spatial land use development, demographic changes, infectious disease transmission and their combination in a dynamic, stochastic model. Heuristically-defined transition rules in cellular automata (CA) were used to capture the processes of both land use development with urban sprawl and infectious disease transmission. A population surface model and dwelling distribution surface were used to bridge the gap between urbanization and infectious disease transmission. A case study is presented involving modelling influenza transmission in Southampton, a dynamically evolving city in the UK. The simulation results for Southampton over a 30-year period show that the pattern of the average number of infection cases per day can depend on land use and demographic changes. The modelling framework presents a useful tool that may be of use in planning applications.     

Simulating the Conversion of Rural Settlements to Town Land Based on Multi-Agent Systems and Cellular Automata

Rapid urbanization in China has triggered the conversion of land from rural to urban use, particularly the conversion of rural settlements to town land. This conversion is the result of the joint effects of the geographic environment and agents involving the government, investors, and farmers. To understand the dynamic interaction dominated by agents and to predict the future landscape of town expansion, a small town land-planning model is proposed based on the integration of multi-agent systems (MAS) and cellular automata (CA). The MAS-CA model links the decision-making behaviors of agents with the neighbor effect of CA. The interaction rules are projected by analyzing the preference conflicts among agents. To better illustrate the effects of the geographic environment, neighborhood, and agent behavior, a comparative analysis between the CA and MAS-CA models in three different towns is presented, revealing interesting patterns in terms of quantity, spatial characteristics, and the coordinating process. The simulation of rural settlements conversion to town land through modeling agent decision and human-environment interaction is very useful for understanding the mechanisms of rural-urban land-use change in developing countries. This process can assist town planners in formulating appropriate development plans.     

A spatially explicit representation of conservation agriculture for application in global change studies

Conservation agriculture (CA) is widely promoted as a sustainable agricultural management strategy with the potential to alleviate some of the adverse effects of modern, industrial agriculture such as large‐scale soil erosion, nutrient leaching and overexploitation of water resources. Moreover, agricultural land managed under CA is proposed to contribute to climate change mitigation and adaptation through reduced emission of greenhouse gases, increased solar radiation reflection, and the sustainable use of soil and water resources. Due to the lack of official reporting schemes, the amount of agricultural land managed under CA systems is uncertain and spatially explicit information about the distribution of CA required for various modeling studies is missing. Here, we present an approach to downscale present‐day national‐level estimates of CA to a 5 arcminute regular grid, based on multicriteria analysis. We provide a best estimate of CA distribution and an uncertainty range in the form of a low and high estimate of CA distribution, reflecting the inconsistency in CA definitions. We also design two scenarios of the potential future development of CA combining present‐day data and an assessment of the potential for implementation using biophysical and socioeconomic factors. By our estimates, 122–215 Mha or 9%–15% of global arable land is currently managed under CA systems. The lower end of the range represents CA as an integrated system of permanent no‐tillage, crop residue management and crop rotations, while the high estimate includes a wider range of areas primarily devoted to temporary no‐tillage or reduced tillage operations. Our scenario analysis suggests a future potential of CA in the range of 533–1130 Mha (38%–81% of global arable land). Our estimates can be used in various ecosystem modeling applications and are expected to help identifying more realistic climate mitigation and adaptation potentials of agricultural practices.     

Mountain vegetation change quantification using surface landscape metrics in Lancang watershed,China

Land cover and vegetation change are among the most important aspects of environmental change. Vegetation change can be quantified by landscape pattern indices (LPI). Landscape indices are routinely calculated using planar land use/land cover (LU/LC) maps, obtained by the projection of a non-flat landscape surface into a two-dimensional Cartesian space. Especially in mountainous areas, quantification on planar maps can lead to underestimation of vegetation and land cover changes. Hoechstetter et al. (2008) developed a method to compute LPIs in a surface structure by calculating landscape patch surface area and surface perimeter from digital elevation models (DEM). As yet there have been no applications of these surface landscape indices on land use/land cover and vegetation change quantification. The objectives of this study are to (1) choose a LPI method (surface metrics pattern analysis or common planimetric metrics pattern analysis) for vegetation change quantification; and (2) employ the selected surface LPI method to assess vegetation pattern change in two mountainous areas of the Lancang watershed, Yunnan Province, China. The results show that the surface approach to estimate changes of class area (CA), mean patch area (MPA), and mean Euclidean Near-Neighbor distance (MENN) may obtain more accurate results for quantifying vegetation change in steep mountain areas. Forest fragmentation increased significantly over time in the two different mountainous study areas. The patches of two land cover classes, (i) agricultural land and (ii) low density forest and tall shrubs, became more aggregated in the northern (temperate) study area. In the southern (tropical) study area, rubber plantations increased considerably in size and became more aggregated.     

Landslides and Their Contribution to Land‐cover Change in the Mountains of Mexico and Central America1

Landsliding is a natural process influencing montane ecosystems, particularly in areas with elevated rainfall and seismic activity. Yet, to date, little effort has been made to quantify the contribution of this process to land‐cover change. Focusing on the mountains of Mexico and Central America (M‐CA), we estimated the contribution of landsliding to land‐cover change at two scales. At the scale of M‐CA, we classified the terrain into major landforms and entered in a GIS historical data on earthquake‐ and rainfall‐triggered landslides. At the scale of the Sierra de Las Minas of Guatemala, we investigated Landsat TM data to map rainfall‐triggered landslides. During the past 110 yr, >136,200 ha of land in the mountains of M‐CA have been affected by landslides, which translates into disturbance rates exceeding 0.317 percent/century. In Sierra de Las Minas, rainfall associated with hurricane Mitch affected 1765 ha of forest, or equivalently, landslides triggered by storms of this magnitude transformed between 0.196 (return time of 500 yr) and 1.290 (return time of 75 yr) percent of forest/century. Although landsliding results in smaller rates of land‐cover change than deforestation, we hypothesize that it has a stronger impact on ecosystems, both in qualitative and quantitative terms, given its influence on vegetation and soil. Moreover, interactions between landsliding and deforestation may be altering the expression of this complex process such that the few protected areas in the mountains of M‐CA may represent the only possibility for the conservation of this process.     

Modelled biophysical impacts of conservation agriculture on local climates

Including the parameterization of land management practices into Earth System Models has been shown to influence the simulation of regional climates, particularly for temperature extremes. However, recent model development has focused on implementing irrigation where other land management practices such as conservation agriculture (CA) has been limited due to the lack of global spatially explicit datasets describing where this form of management is practiced. Here, we implement a representation of CA into the Community Earth System Model and show that the quality of simulated surface energy fluxes improves when including more information on how agricultural land is managed. We also compare the climate response at the subgrid scale where CA is applied. We find that CA generally contributes to local cooling (~1°C) of hot temperature extremes in mid‐latitude regions where it is practiced, while over tropical locations CA contributes to local warming (~1°C) due to changes in evapotranspiration dominating the effects of enhanced surface albedo. In particular, changes in the partitioning of evapotranspiration between soil evaporation and transpiration are critical for the sign of the temperature change: a cooling occurs only when the soil moisture retention and associated enhanced transpiration is sufficient to offset the warming from reduced soil evaporation. Finally, we examine the climate change mitigation potential of CA by comparing a simulation with present‐day CA extent to a simulation where CA is expanded to all suitable crop areas. Here, our results indicate that while the local temperature response to CA is considerable cooling (>2°C), the grid‐scale changes in climate are counteractive due to negative atmospheric feedbacks. Overall, our results underline that CA has a nonnegligible impact on the local climate and that it should therefore be considered in future climate projections.     

Combining system dynamic model and CLUE-S model to improve land use scenario analyses at regional scale: A case study of Sangong watershed in Xinjiang,China

Uses of models of land use change are primary tools for analyzing the causes and consequences of land use changes, assessing the impacts of land use change on ecosystems and supporting land use planning and policy. However, no single model is able to capture all of key processes essential to explore land use change at different scales and make a full assessment of driving factors and impacts. Based on the multi-scale characteristics of land use change, combination and integration of currently existed models of land use change could be a feasible solution. Taken Sangong watershed as a case study, this paper describes an integrated methodology in which the conversion of land use and its effect model (CLUE), a spatially explicit land use change model, has been combined with a system dynamic model (SD) to analyze land use dynamics at different scales. A SD model is used to calculate area changes in demand for land types as a whole while a CLUE model is used to transfer these demands to land use patterns. Without the spatial consideration, the SD model ensures an appropriate treatment of macro-economic, demographic and technology developments, and changes in economic policies influencing the demand and supply for land use in a specific region. With CLUE model the land use change has been simulated at a high spatial resolution with the spatial consideration of land use suitability, spatial policies and restrictions to satisfy the balance between land use demand and supply. The application of the combination of SD and CLUE model in Sangong watershed suggests that this methodology have the ability to reflect the complex behaviors of land use system at different scales to some extent and be a useful tool for analysis of complex land use driving factors such as land use policies and assessment of its impacts on land use change. The established SD model was fitted or calibrated with the 1987–1998 data and validated with the 1998–2004 data; combining SD model with CLUE-S model, future land use scenarios were analyzed during 2004–2030. This work could be used for better understanding of the possible impacts of land use change on terrestrial ecosystem and provide scientific support for land use planning and managements of the watershed.     

流域尺度土地利用与土壤类型空间分布的相关性研究

随着人类活动日益加强,土地利用变化及其驱动力研究已经成为国际地理学界研究的热点。但目前更多的工作侧重于研究人为因子,如人口增长、政策变化等因子对土地利用变化的影响,其实土地利用在宏观尺度上的变化一定程度上取决于自然环境背景,因此研究土地利用变化的自然环境背景特征对于进一步探讨土地利用变化的自然驱动力具有重要意义。土壤类型的空间分布在一定程度将影响土地利用的空间分布格局和变化过程。本文利用遥感、地理信息系统,通过选取景观格局指标,以于桥水库流域为例,研究了土地利用与土壤类型空间分布之间的相互关系。结果表明：(1)受人类活动干扰较弱的土地利用类型,如有林地、稀疏林地、灌木林地、其他林地和草地,主要分布在淋溶褐土、褐土性土以及棕壤地区;而与人类活动密切的土地利用类型,如山区旱耕地、丘陵区水田、丘陵区旱耕地和平原区旱耕地主要分布在淋溶褐土、褐土性土和潮土地区;(2)同类地区土地利用的多样性指数要比土壤的低。并且土地利用和土壤类型多样性均表现出明显的地形梯度效应,从中低山区、低山丘陵区、丘陵平原区到山间盆地区,土壤多样性指数从小到大有规律地变化。而土地利用类型多样性变化较为复杂,反映出人类活动对土地利用格局的影响较强,而对土壤类型的影响相对较小;(3)随着平均斑块面积的增加,流域多样性指数将呈下降趋势。土地利用多样性指数与流域总面积之间的相关性较差,但土壤多样性指数与流域总面积表现出的相关性较好;(4)土地利用类型与土壤类型之间,平均斑块面积上没有明显的相关关系,但在多样性指数之间存在着较好的相关性。土壤类型丰富多样的地区,土地利用的多样性指数也相对较高。     

上海轨道交通对城市土地利用变化的影响

利用1989、2005年上海市1∶50 000彩红外航空遥感影像解译的土地利用数据,基于GIS技术,定量研究了上海轨道交通对城市土地利用动态变化的影响,并用Markov模型对研究区2010—2025年间的土地利用变化进行了初步预测.结果表明：轨道交通加快了上海市土地利用的转化,促进了以耕地为主的自然景观向居住、公共设施用地等土地获益较高的人工景观转化;轨道交通增加了研究区的土地利用程度;1989—2005年,研究区其他用地（以在建用地为主,下同）、公共设施用地、绿地、耕地、水域的转化率较大,其中,其他用地的变化速度最快,水域的变化速度最慢;2010—2025年,耕地、水域的面积和比例将继续减少,居住、公共设施用地等人工景观的面积则呈继续增加的趋势.从提高土地利用程度和土地获益的角度,轨道交通沿线的这种土地利用结构仍需要进一步调整,以增加土地的集约化程度和实现土地资源的可持续利用.