A new forest cover map of continental southeast Asia derived from SPOT‐VEGETATION satellite imagery

Question: Can recent satellite imagery of coarse spatial resolution support forest cover assessment and mapping at the regional level? Location: Continental southeast Asia. Methods: Forest cover mapping was based on digital classification of SPOT4‐VEGETATION satellite images of 1 km spatial resolution from the dry seasons 1998/1999 and 1999/2000. Following a geographical stratification, the spectral clusters were visually assigned to land cover classes. The forest classes were validated by an independent set of maps, derived from interpretation of satellite imagery of high spatial resolution (Landsat TM, 30 m). Forest area estimates from the regional forest cover map were compared to the forest figures of the FAO database. Results: The regional forest cover map displays 12 forest and land cover classes. The mapping of the region's deciduous and fragmented forest cover remained challenging. A high correlation was found between forest area estimates obtained from this map and from the Landsat TM derived maps. The regional and sub‐regional forest area estimates were close to those reported by FAO. Conclusion: SPOT4‐VEGETATION satellite imagery can be used for mapping consistently and uniformly the extent and distribution of the broad forest cover types at the regional scale. The new map can be considered as an update and improvement on existing regional forest cover maps.     

Spatial scaling of arbuscular mycorrhizal fungal diversity is affected by farming practice

Evidence suggests that microbial communities show patterns of spatial scaling which can be driven by geographical distance and environmental heterogeneity. Here we demonstrate that human management can have a major impact on microbial distribution patterns at both the local and landscape scale. Mycorrhizal fungi are vital components of terrestrial ecosystems, forming a mutualistic symbiosis with plant roots which has a major impact on above ground ecology and productivity. We used contrasting agricultural systems to investigate the spatial scaling of the most widespread mycorrhizal fungus group, the arbuscular mycorrhizal fungi (AMF). Using multiple sampling sites with a maximum separation of 250 km we describe for the first time the roles which land management, environmental heterogeneity and geographical distance play in determining spatial patterns of microbial distribution. Analysis of AMF taxa–area relationships at each sampling site revealed that AMF diversity and spatial turnover was greater under organic relative to conventional farm management. At the regional scale (250 km) distance–decay analyses showed that there was significant change in AMF community composition with distance, and that this was greater under organic relative to conventional management. Environmental heterogeneity was found to be the major factor determining turnover of AMF taxa at the landscape scale. Overall we demonstrate that human management can play a key role in determining the turnover of microbial communities at both the local and regional scales.     

Agricultural land use changes – a scenario-based sustainability impact assessment for Brandenburg,Germany

Decisions for agricultural management are taken at farm scale. However, such decisions may well impact upon regional sustainability. Two of the likely agricultural management responses to future challenges are extended use of irrigation and increased production of energy crops. The drivers for these are high commodity prices and subsidy policies for renewable energy. However, the impacts of these responses upon regional sustainability are unknown. Thus, we conducted integrated impact assessments for agricultural intensification scenarios in the federal state of Brandenburg, Germany, for 2025. One Irrigation scenario and one Energy scenario were contrasted with the Business As Usual (BAU) scenario. We applied nine indicators to analyze the economic, social and environmental effects at the regional, in this case district scale, which is the smallest administrative unit in Brandenburg. Assessment results were discussed in a stakeholder workshop involving 16 experts from the state government.The simulated area shares of silage maize for fodder and energy were 29%, 37% and 49% for the BAU, Irrigation, and Energy scenarios, respectively. The Energy scenario increased bio-electricity production to 41% of the demand of Brandenburg, and it resulted in CO₂ savings of up to 3.5 million tons. However, it resulted in loss of biodiversity, loss of landscape scenery, increased soil erosion risk, and increased area demand for water protection requirements. The Irrigation scenario led to yield increases of 7% (rapeseed), 18% (wheat, sugar beet), and 40% (maize) compared to the BAU scenario. It also reduced the year-to-year yield variability. Water demand for irrigation was found to be in conflict with other water uses for two of the 14 districts. Spatial differentiation of scenario impacts showed that districts with medium to low yield potentials were more affected by negative impacts than districts with high yield potentials.In this first comprehensive sustainability impact assessment of agricultural intensification scenarios at regional level, we showed that a considerable potential for agricultural intensification exists. The intensification is accompanied by adverse environmental and socio-economic impacts. The novelty lies in the multiscale integration of comprehensive, agricultural management simulations with regional level impact assessment, which was achieved with the adequate use of indicators. It provided relevant evidence for policy decision making. Stakeholders appreciated the integrative approach of the assessment, which substantiated ongoing discussions among the government bodies. The assessment approach and the Brandenburg case study may stay exemplary for other regions in the world where similar economic and policy driving forces are likely to lead to agricultural intensification.     

Flexible Strategies for Coping with Rainfall Variability: Seasonal Adjustments in Cropped Area in the Ganges Basin

One of the main manifestations of climate change will be increased rainfall variability. How to deal with this in agriculture will be a major societal challenge. In this paper we explore flexibility in land use, through deliberate seasonal adjustments in cropped area, as a specific strategy for coping with rainfall variability. Such adjustments are not incorporated in hydro-meteorological crop models commonly used for food security analyses. Our paper contributes to the literature by making a comprehensive model assessment of inter-annual variability in crop production, including both variations in crop yield and cropped area. The Ganges basin is used as a case study. First, we assessed the contribution of cropped area variability to overall variability in rice and wheat production by applying hierarchical partitioning on time-series of agricultural statistics. We then introduced cropped area as an endogenous decision variable in a hydro-economic optimization model (WaterWise), coupled to a hydrology-vegetation model (LPJmL), and analyzed to what extent its performance in the estimation of inter-annual variability in crop production improved. From the statistics, we found that in the period 1999–2009 seasonal adjustment in cropped area can explain almost 50% of variability in wheat production and 40% of variability in rice production in the Indian part of the Ganges basin. Our improved model was well capable of mimicking existing variability at different spatial aggregation levels, especially for wheat. The value of flexibility, i.e. the foregone costs of choosing not to crop in years when water is scarce, was quantified at 4% of gross margin of wheat in the Indian part of the Ganges basin and as high as 34% of gross margin of wheat in the drought-prone state of Rajasthan. We argue that flexibility in land use is an important coping strategy to rainfall variability in water stressed regions.     

基于SWCI-NDVI特征空间的县域耕地地力遥感反演

利用遥感反演县域耕地地力状况,快速、准确、高效地实现耕地定级,是区域耕地资源利用与管理的客观需求.本研究以东平县为研究区,利用Landsat-TM卫星影像和耕地地力评价资料,构建以地表含水量指数(SWCI)、归一化植被指数(NDVI)为特征参量的水分植被地力指数(MVFI),进而优选得到最佳反演模型,并在县域空间上进行...     

Land cover changes with the development of anaerobic digestion for biogas production in France

Anaerobic digestion is developing in various countries worldwide to produce renewable energy. In addition, the resulting digestates provide readily available nutrients when applied to cropping systems as fertilizers. The introduction of a biogas plant on a farm can induce land cover changes, in relation to the production of feedstock for the biogas plant and/or to the modification of the farming system. The aim of this study was therefore to characterize and quantify the land cover changes in farms associated with biogas plants in France. We combined two national spatialized databases: the Land Parcel Identification System (yearly French land cover at the parcel scale with farm identifier per parcel) and the SINOE database (biogas plant location and year of start-up). We showed that, on average, the changes were limited, with an increase in maize areas (+3.4% of the total farm areas) compensated by a decrease in wheat and rapeseed areas (−1.8% and −1.9%, respectively), but with a certain variability. The French regulation and market limiting the use of dedicated energy crops seems to have limited land cover changes in France compared to other countries. However, we elaborated a typology of land cover changes and characterized five clusters of farms across the country. The main one (67% of the farms) corresponded to unchanged land cover after the introduction of a biogas plant. The four other clusters showed contrasting changes, for example, an increase or a decrease in grassland areas, a strong increase in maize areas, or a replacement of winter wheat by winter barley. The diversity and the driving factors behind these changes deserve to be better studied and understood through further farmer surveys.     

黄淮海地区耕地复种指数的时空格局演变

耕地复种指数是土地利用强度的重要表征,时空动态特征有助于理解人类活动与生态环境的耦合作用。以黄淮海地区2001—2015年MODIS(Moderate-resolution Imaging Spectroradiometer,中分辨率成像光谱仪)NDVI(Normalized Difference Vegetation Index,归一化植被指数)遥感影像为数据源,使用Savitzky-Golay滤波对时间序列曲线平滑重构后,结合研究区物候信息设置含有阈值的二次差分算法提取复种次数,最后在R环境下绘制复种指数空间分布图。结果表明:(1)河南省复种指数最高(169.3%),山东省次之,天津市最小;(2)各省市年际变化趋势大体一致,经历了升高-降低-升高的过程;从空间分布特征来看,耕地复种指数具有明显的地域性差异,二熟制主要集中于南部,东部和北部受地形和纬度影响,主要以一熟制为主。研究结果对于黄淮海农耕区的土地利用强度辨识、人类活动方式确定具有参考价值,同时也证明了该方法具有更大尺度推广的潜力。     

Crop yield response to climate change varies with cropping intensity

Projections of the response of crop yield to climate change at different spatial scales are known to vary. However, understanding of the causes of systematic differences across scale is limited. Here, we hypothesize that heterogeneous cropping intensity is one source of scale dependency. Analysis of observed global data and regional crop modelling demonstrate that areas of high vs. low cropping intensity can have systematically different yields, in both observations and simulations. Analysis of global crop data suggests that heterogeneity in cropping intensity is a likely source of scale dependency for a number of crops across the globe. Further crop modelling and a meta‐analysis of projected tropical maize yields are used to assess the implications for climate change assessments. The results show that scale dependency is a potential source of systematic bias. We conclude that spatially comprehensive assessments of climate impacts based on yield alone, without accounting for cropping intensity, are prone to systematic overestimation of climate impacts. The findings therefore suggest a need for greater attention to crop suitability and land use change when assessing the impacts of climate change.     

<Emphasis Type="Italic">Hieracium pilosella</Emphasis> invasion in the Tierra del Fuego steppe,Southern Patagonia

Biological invasions have important ecological impacts at both local and global levels, affecting biodiversity, ecosystem functioning, and economic sustainability. The study of invasions requires specific methodological approaches to gain rapid insight into the spatial and temporal dynamics of the system. We studied a recent invasion by the exotic herb Hieracium pilosella L. (Mouse-ear hawkweed, Asteraceae) in the Argentinean portion of the northern part of Tierra del Fuego Island in Southern Patagonia. To assess the extent of this invasion and the related ecological and land use factors, we performed an extensive field sampling at a regional scale and used a spatial pattern approach using geostatistical techniques to build a map of the invasion. Our results showed that the invading species is widely distributed across the entire Fuegian steppe, in general with low cover (<2%) and a particular spatial structure having hot spots (10–70%) related to specific land uses. We found regional-latitudinal and also local-community level variability in the frequency, cover and spatial distribution of the invasive species, each of them associated with particular ecological factors, and no association with regular domestic animal grazing. Region-wide invasion may be accounted for by wind dispersal of the seeds and the latitudinal variability of the precipitation; while local-variability was associated with the susceptibility of different plant communities to invasion. Hot spots were found to be related to massive soil disturbances (e.g., road building, shrub removal, physical impacts of long-term and intense domestic animal use, etc.), probably due to the presence of bare soil favoring colonization by the invading species. Scrublands, lawns and grasslands were more invaded than wetlands, heathlands or salt grasslands. Since the invasion is apparently at initial stages due to the low cover values found, we believe that information about the extent and environmental or management factors involved in this exotic plant’s expansion should be used to design appropriate control and mitigation tools. In this sense, our results point to management actions focused on reducing the presence of hot spots of invasion by means of quick revegetation of bare soil after a massive disturbance event takes place.     

多功能视角下的山区乡村空间功能分异特征及类型划分

以西部山区重庆乡村空间为研究对象,构建乡村空间多功能评价指标体系,将乡村空间多功能划分为农业生产功能、经济发展功能、生态保育功能、生态稳定性功能,社会保障居住家园功能五种子功能,采用熵权法定量核算2013年全市乡村空间功能值,运用GIS技术和Dagum基尼系数刻画重庆市不同地区乡村空间功能值地区差异特征,并划分了重庆市乡村空间多功能类型,研究结果表明:(1)山地型乡村地形复杂,景观类型多样,功能也极具多样性,研究区乡村空间除了生态稳定性功能外,其他各功能值具有显著的空间分异特征,有明显的空间集聚性。(2)Dagum基尼系数,是一种有效的技术方法,能够更为深入地刻画研究区乡村空间功能值地区间差异及区内差异特征。基尼系数测算及其分解结果显示,地区间差距是总体差距的主要来源,其贡献率都超过50%。(3)根据乡间空间多功能分布的差异性及山地乡村的特点和山区生态环境的脆弱性,将研究区乡村空间划分为农业生产-经济发展型,农业生产-人居生活型,人居生活-社会保障型,人居生活-经济发展型,水源涵养生态保育型,生态保育-经济发展型,生态保育-农业生产型,土壤保持生态保护型8种功能类型,能较好地体现地域特色,为科学健康的开发利用山地乡村空间土地资源提供有益借鉴,有利于区域协调可持续发展。     

Multiple Methods in the Study of Driving Forces of Land Use and Land Cover Change: A Case Study of SE Kajiado District,Kenya

This landscape-scale study combines analysis of multitemporal satellite imagery spanning 30 years and information from field studies extending over 25 years to assess the extent and causes of land use and land cover change in the Loitokitok area, southeast Kajiado District, Kenya. Rain fed and irrigated agriculture, livestock herding, and wildlife and tourism have all experienced rapid change in their structure, extent, and interactions over the past 30 years in response to a variety of economic, cultural, political, institutional, and demographic processes. Land use patterns and processes are explored through a complementary application of interpretation of satellite imagery and case study analysis that explicitly addresses the local–national spatial scale over a time frame appropriate to the identification of fundamental causal processes. The results illustrate that this combination provides an effective basis for describing and explaining patterns of land use and land cover change and their root causes.     

基于遥感的煤炭型矿业城市土地利用与生态承载力时空变化分析

运用遥感和社会经济系统发展指数修正生态足迹模型,开展淮南市土地利用与生态承载力时空演化分析。结果表明:1987—2012年,淮南市人均生态承载力总体呈现缓慢降低后略微升高的趋势,2009年是人均生态承载力提升的拐点,表明经济科技因子的提升作用;淮南市生态承载力时空差异显著,总体呈现东南和北部高、西部低的格局,而且区域破碎化加剧的趋势。矿区占用大量耕地以及积水塌陷区的形成,是生态承载力的下降和空间格局分异的主要原因;土地利用转移以耕地、建筑用地为主,水域对土地利用格局的影响日益增强,开展塌陷区整治,将塌陷区形成的水域转换成耕地或建设用地,将是提高淮南市生态承载力的最有效途径之一。     

长江流域产水功能对土地利用变化的响应及其驱动因素

长江流域产水功能是流域水生态平衡的重要组成部分,在生态安全防护上具有重要战略地位。产水量是指示区域水环境功能的重要生态指标,探讨长江流域土地利用变化对产水量的影响对于深化和揭示土地利用对水环境功能的效应有重要意义。研究基于多元统计方法与InVEST模型产水模块探讨了产水量对土地利用变化的响应模式,以及影响区域产水的驱动因素。结果表明：1.1990年至2015年,长江流域平均产水量呈西北低、东南高、中游>下游>上游的空间分布规律,子流域间的产水空间差异程度呈加剧趋势;2.从总产水量来看,洞庭湖、鄱阳湖和金沙江为主要贡献流域,贡献了总产水量的50%,且农用地与林地为主要土地贡献类型;3.由于长江流域土地利用结构和配置的转变,产水量的响应呈土地类型上的多样性,表现为农用地、草地、未利用地对产水变化具有正向协同效应,而林地和水域具有负向协同效应,建设用地对产水的响应不明显;4.影响产水功能的主要驱动力为建设用地、水域、人口密度、国民生产总值、降雨,农用地、植被覆盖、温度为潜在驱动力,未来长江流域产水功能的调控需要重视不同子流域间产水量的空间异质性与土地利用配置的协调性。     

Estimating Impacts of Climate Change Policy on Land Use: An Agent-Based Modelling Approach

Agriculture is important to New Zealand’s economy. Like other primary producers, New Zealand strives to increase agricultural output while maintaining environmental integrity. Utilising modelling to explore the economic, environmental and land use impacts of policy is critical to understand the likely effects on the sector. Key deficiencies within existing land use and land cover change models are the lack of heterogeneity in farmers and their behaviour, the role that social networks play in information transfer, and the abstraction of the global and regional economic aspects within local-scale approaches. To resolve these issues we developed the Agent-based Rural Land Use New Zealand model. The model utilises a partial equilibrium economic model and an agent-based decision-making framework to explore how the cumulative effects of individual farmer’s decisions affect farm conversion and the resulting land use at a catchment scale. The model is intended to assist in the development of policy to shape agricultural land use intensification in New Zealand. We illustrate the model, by modelling the impact of a greenhouse gas price on farm-level land use, net revenue, and environmental indicators such as nutrient losses and soil erosion for key enterprises in the Hurunui and Waiau catchments of North Canterbury in New Zealand. Key results from the model show that farm net revenue is estimated to increase over time regardless of the greenhouse gas price. Net greenhouse gas emissions are estimated to decline over time, even under a no GHG price baseline, due to an expansion of forestry on low productivity land. Higher GHG prices provide a greater net reduction of emissions. While social and geographic network effects have minimal impact on net revenue and environmental outputs for the catchment, they do have an effect on the spatial arrangement of land use and in particular the clustering of enterprises.     

Is Yield Increase Sufficient to Achieve Food Security in China?

Increasing demand for food, driven by unprecedented population growth and increasing consumption, will keep challenging food security in China. Although cereal yields have substantially improved during the last three decades, whether it will keep thriving to meet the increasing demand is not known yet. Thus, an integrated analysis on the trends of crop yield and cultivated area is essential to better understand current state of food security in China, especially on county scale. So far, yield stagnation has extensively dominated the main cereal-growing areas across China. Rice yield is facing the most severe stagnation that 53.9% counties tracked in the study have stagnated significantly, followed by maize (42.4%) and wheat (41.9%). As another important element for production sustainability, but often neglected is the planted area patterns. It has been further demonstrated that the loss in productive arable land for rice and wheat have dramatically increased the pressure on achieving food security. Not only a great deal of the planted areas have stagnated since 1980, but also collapsed. 48.4% and 54.4% of rice- and wheat-growing counties have lost their cropland areas to varying degrees. Besides, 27.6% and 35.8% of them have retrograded below the level of the 1980s. The combined influence (both loss in yield and area) has determined the crop sustainable production in China to be pessimistic for rice and wheat, and consequently no surprise to find that more than half of counties rank a lower level of production sustainability. Therefore, given the potential yield increase in wheat and maize, as well as substantial area loss of rice and wheat, the possible targeted adaptation measures for both yield and cropping area is required at county scale. Moreover, policies on food trade, alongside advocation of low calorie diets, reducing food loss and waste can help to enhance food security.     

大城市边缘区景观破碎化空间异质性——以北京市顺义区为例

探索大城市边缘区景观破碎化格局及其空间异质性特征,有助于把握景观动态的变化机制及其生态问题.以北京市顺义区这一典型大城市边缘区为例,基于土地利用分类数据,采用有效粒度尺寸方法,对1992年、1999年和2009年景观破碎化空间变异进行了地统计学分析,主要包括尺度依赖性、空间异质性、空间格局及其生态过程的分析.研究结果表明:1)景观破碎化空间变异具有明显的尺度依赖性特征,由空间自相关部分引起的空间异质性较高;1992年和1999年景观破碎化空间总变异相对缓和,2009年空间总变异强烈;通过不同尺度上的异质性对比,选取1000m幅度作为研究区景观破碎化的空间异质性分析较为适宜.2)景观破碎化空间异质性表现出明显的上升趋势,土地利用斑块破碎化不断加剧,其中1999-2009年间的表现尤为强烈.3)景观破碎化高值区呈现出由东部向西部转移的态势,并且其空间布局具有集聚性与分散性的显著特征,空间上相似属性聚集与相异属性聚集的空间格局十分突出.4)景观破碎化空间自相关作用主要来自高强度社会经济活动的影响,并表现出明显的区位特征.该研究结果可为土地、城镇规划以及景观生态建设提供参考.     

稻田不同耕作制下有机质和氮磷钾的变化研究

６ａ定位研究的结果表明,在东洞庭湖地区土壤,气候及施肥等条件下,４种主要耕作制中,稻－稻－冬闲耕作制不仅产量较低,而且经济效益也较差,并有可能导致土壤肥力的下降和退化,稻－稻－肥（紫云英）耕作制由具有一定的增产效果,并且有较高的经济效益,土壤肥力亦呈现出上升和进化的趋势,稻－稻－麦（大麦）和稻－稻－油（油菜）耕作制则不仅使土地的得用率提高,增加了单位的产量,且土壤肥力也同样得到了上升和进化,但其经     

An integrative modeling framework to evaluate the productivity and sustainability of biofuel crop production systems

The potential expansion of biofuel production raises food, energy, and environmental challenges that require careful assessment of the impact of biofuel production on greenhouse gas (GHG) emissions, soil erosion, nutrient loading, and water quality. In this study, we describe a spatially explicit integrative modeling framework (SEIMF) to understand and quantify the environmental impacts of different biomass cropping systems. This SEIMF consists of three major components: (1) a geographic information system (GIS)‐based data analysis system to define spatial modeling units with resolution of 56 m to address spatial variability, (2) the biophysical and biogeochemical model Environmental Policy Integrated Climate (EPIC) applied in a spatially‐explicit way to predict biomass yield, GHG emissions, and other environmental impacts of different biofuel crops production systems, and (3) an evolutionary multiobjective optimization algorithm for exploring the trade‐offs between biofuel energy production and unintended ecosystem‐service responses. Simple examples illustrate the major functions of the SEIMF when applied to a nine‐county Regional Intensive Modeling Area (RIMA) in SW Michigan to (1) simulate biofuel crop production, (2) compare impacts of management practices and local ecosystem settings, and (3) optimize the spatial configuration of different biofuel production systems by balancing energy production and other ecosystem‐service variables. Potential applications of the SEIMF to support life cycle analysis and provide information on biodiversity evaluation and marginal‐land identification are also discussed. The SEIMF developed in this study is expected to provide a useful tool for scientists and decision makers to understand sustainability issues associated with the production of biofuels at local, regional, and national scales.     

Environmental Controls of Primary Production in Agricultural Systems of the Argentine Pampas

We studied the aboveground net primary productivity (ANPP) of wheat crops in the Argentine Pampas. Our specific objectives were to determine (a) the response of ANPP to changes in water availability (b) the regional patterns of ANPP and (c) the interannual variability and environmental controls of ANPP. We used ground and satellite data to address these questions. Wheat ANPP was calculated as the ratio between grain yield and harvest index. We developed a simple model that took into account environmental and genetic improvement effects upon harvest index. We used the normalized difference vegetational index (NDVI) as a surrogate for ANPP at the county level. Straight-line regression models were fitted to single-year and average values of ANPP and precipitation to derive temporal and spatial models for wheat. For grasslands, we used spatial and temporal models already published. At any given site, there was no difference between modeled wheat and grassland average ANPP. The response of ANPP to changes in interannual water availability decreased along the precipitation gradient when vegetation structure (for example, species composition, density, and total cover) was held constant (wheat crops). Wheat ANPP and total production variability, estimated from remotely sensed data, decreased as mean annual precipitation (MAP) increased. The percentage of soils without drainage problems was the variable that explained most of the wheat ANPP spatial variability as shown by stepwise linear regression. Precipitation variability accounted for 49% of wheat ANPP variability. Remotely sensed estimates of ANPP variability showed lower and wheat ANPP higher temporal variability than annual precipitation.     

三峡库区生态敏感区土地生态安全预警测度与时空演变——以重庆市万州区为例

以三峡库区生态敏感区典型区万州区为研究对象,基于压力-状态-响应(P-S-R)框架构建土地生态安全预警指标体系,运用熵值法进行土地生态安全预警分析,并通过空间统计学方法对研究区土地生态安全警度的空间分布特征、变异规律及空间关联格局进行研究分析,旨在为区域土地资源利用的规划、管理及其生态保护提供决策参考。结果表明:(1)研究区2000-2014年土地生态安全警度呈连续上升趋势,土地生态安全警度较高区域由万州区中心城区不断向四周扩散,但2000-2009年期间研究区土地生态安全警度提升幅度比2009-2014年期间更为明显,2000-2009年期间是区域土地生态安全警度变化的关键时段。(2)研究区2000-2014年C_0/(C_0+C)呈不断上升趋势,表明非结构性因素对区域土地生态安全警度的影响程度在不断加大,这与研究区14年来经济高速发展、人类对土地资源利用强度加剧以及区域自然灾害频发的实际情况相符。(3)研究区2000年、2009年、2014年全局Moran's I值分别为0.7823、0.7772、0.775,表明土地生态安全预警指数在空间上存在较强的正相关关系,区域土地生态安全警度在空间上具有较强聚集性。(4)研究区"高-高"、"低-低"值区均呈现出2000-2009年范围逐渐增加,而2009-2014年范围逐渐缩小的趋势;且"高-高"值区主要集中分布在中心城区及其邻近区域,"低-低"值区则主要集中分布在研究区西北部和东南部等土地利用程度相对较弱、植被覆盖相对较好地区;中心城区周边的"低-高"值区将是城市发展中优先被占用的区域,在未来的土地利用中,尤其需加强对区域"低-高"值区的重点保护。