中国近期主要农业自然灾害的时空变化分析(英文)

China is a disaster prone country, and a comprehensive understanding of change of disasters is very important for China’s agricultural development. In this study, statistical techniques and geographic information system tools are employed to quantify the main agriculture disasters changes and effects on grain production in China during the period of 1990–2011. The results show that China’s grain production was severely affected by disasters including drought, flood, hail, frost and typhoon. The annual area covered by these disasters reached up to 48.7×106 ha during the study period, which accounted for 44.8% of the total sown area, and about 55.1% of the per unit area grain yield change was caused by disasters. In addition, all of the disasters showed high variability, different changing trends, and spatial distribution. Drought, flood, and hail showed significantly decreasing trends, while frost and typhoon showed increasing trends. Drought and flood showed gradual changes and were distributed across the country, and disasters became more diversified from north to south. Drought was the dominated disaster type in northern China, while flood was the most important disaster type in the southern part. Hail was mainly observed in central and northern China, and frost was mainly distributed in southern China. Typhoon was greatly limited to the southeast coast. Furthermore, the resilience of grain production of each province was quite different, especially in several major grain producing areas, such as Shandong, Liaoning, Jilin and Jiangsu, where grain production was seriously affected by disasters. One reason for the difference of resilience of grain production was that grain production was marginalized in developed provinces when the economy underwent rapid development. For China’s agricultural development and grain security, we suggest that governments should place more emphasis on grain production, and invest more money in disaster prevention and mitigation, especially in the major grain producing provinces.     

Attribution analysis for water yield service based on the geographical detector method: A case study of the Hengduan Mountain region

Ecosystem services, which include water yield services, have been incorporated into decision processes of regional land use planning and sustainable development. Spatial pattern characteristics and identification of factors that influence water yield are the basis for decision making. However, there are limited studies on the driving mechanisms that affect the spatial heterogeneity of ecosystem services. In this study, we used the Hengduan Mountain region in southwest China, with obvious spatial heterogeneity, as the research site. The water yield module in the In VEST software was used to simulate the spatial distribution of water yield. Also, quantitative attribution analysis was conducted for various geomorphological and climatic zones in the Hengduan Mountain region by using the geographical detector method. Influencing factors, such as climate, topography, soil, vegetation type, and land use type and pattern, were taken into consideration for this analysis. Four key findings were obtained. First, water yield spatial heterogeneity is influenced most by climate-related factors, where precipitation and evapotranspiration are the dominant factors. Second, the relative importance of each impact factor to the water yield heterogeneity differs significantly by geomorphological and climatic zones. In flat areas, the influence of evapotranspiration is higher than that of precipitation. As relief increases, the importance of precipitation increases and eventually, it becomes the most influential factor. Evapotranspiration is the most influential factor in a plateau climate zone, while in the mid-subtropical zone, precipitation is the main controlling factor. Third, land use type is also an important driving force in flat areas. Thus, more attention should be paid to urbanization and land use planning, which involves land use changes, to mitigate the impact on water yield spatial pattern. The fourth finding was that a risk detector showed that Primarosol and Anthropogenic soil areas, shrub areas, and areas with slope 5° and 25°–35° should be recognized as water yield important zones, while the corresponding elevation values are different among different geomorphological and climatic zones. Therefore, the spatial heterogeneity and influencing factors in different zones should be fully con-sidered while planning the maintenance and protection of water yield services in the Hengduan Mountain region.     

Forest phenological patterns of Northeas China inferred from MODIS data

The role of remote sensing in phenological studies is increasingly regarded as a key to understand large area seasonal phenomena. This paper describes the application of Moderate Resolution Imaging Spectroradiometer (MODIS) time series data for forest phenological patterns. The forest phenological phase of Northeast China (NE China) and its spatial characteristics were inferred using 1-km 10-day MODIS normalized difference vegetation index (NDVI) datasets of 2002. The threshold-based method was used to estimate three key forest phenological variables, which are the start of growing season (SOS), the end of growing season (EOS) and growing season length (GSL).Then the spatial patterns of forest phenological variables of NE China were mapped and analyzed. The derived phenological variables were validated by the field observed data from published papers in the same study area. Results indicate that forest phenological phase from MODIS data is comparable with the observed data. As the derived forest phenological pattern is related to forest type distribution, it is helpful to discriminate between forest types.     

近50年中国光合有效辐射的时空变化(英文)

Based on long-term measurement data of weather/ecological stations over China,this paper calculated and produced annually-and seasonally-averaged Photosynthetically Active Radiation(PAR) spatial data from 1961 to 2007,using climatological calculations and spatialization techniques.The spatio-temporal variation characteristics of annually-and seasonally-averaged PAR spatial data over China in recent 50 years were analyzed with Mann-Kendall trend analysis method and GIS spatial analysis techniques.The results show that:(1) As a whole,the spatial distribution of PAR is complex and inhomogeneous across China,with lower PAR in the eastern and southern parts of China and higher PAR in the western part.Mean annual PAR over China ranges from 17.7 mol m-2 d-1 to 39.5 mol m-2 d-1.(2) Annually-and seasonally-averaged PAR of each pixel over China are averaged as a whole and the mean values decline visibly with fluctuant processes,and the changing rate of annually-averaged PAR is-0.138 mol m-2 d-1/10a.The changing amplitudes among four seasons are different,with maximum dropping in summer,and the descending speed of PAR is faster before the 1990s,after which the speed slows down.(3) The analysis by each pixel shows that PAR declines significantly(α=0.05) in most parts of China.Summer and winter play more important roles in the interannual variability of PAR.North China is always a decreasing zone in four seasons,while the northwest of Qinghai-Tibet Plateau turns to be an increasing zone in four seasons.(4) The spatial distributions of the interannual variability of PAR vary among different periods.The interannual variabilities of PAR in a certain region are different not only among four seasons,but also among different periods.     

中国科技资源配置效率测度及其时空格局演变特征(英文)

According to the connotation and structure of science and technology resources and some relevant data of more than 286 cities at prefecture level and above during 2001–2010, using modified method—Data Envelopment Analysis(DEA), science and technology(ST) resource allocation efficiency of different cities in different periods has been figured out, which, uncovers the distributional difference and change law of ST resource allocation efficiency from the time-space dimension. Based on that, this paper has analyzed and discussed the spatial distribution pattern and evolution trend of ST resource allocation efficiency in different cities by virtue of the Exploratory Spatial Data Analysis(ESDA). It turned out that:(1) the average of ST resource allocation efficiency in cities at prefecture level and above has always stayed at low levels, moreover, with repeated fluctuations between high and low, which shows a decreasing trend year by year. Besides, the gap between the East and the West is widening.(2) The asymmetrical distribution of ST resource allocation efficiency presents a spatial pattern of successively decreasing from Eastern China, Central China to Western China. The cities whose ST resource allocation efficiency are at higher level and high level take on a cluster distribution, which fits well with the 23 forming urban agglomerations in China.(3) The coupling degree between ST resource allocation efficiency and economic environment assumes a certain positive correlation, but not completely the same. The differentiation of ST resource allocation efficiency is common in regional development, whose existence and evolution are directly or indirectly influenced by and regarded as the reflection of many elements, such as geographical location, the natural endowment and environment of ST resources and so on.(4) In the perspective of the evolution of spatial structure, ST resource allocation efficiency of the cities at prefecture level and above shows a notable spatial autocorrelation, which in every period presents a positive correlation. The spatial distribution of ST resource allocation efficiency in neighboring cities seems to be similar in group, which tends to escalate stepwise. Meanwhile, the whole differentiation of geographical space has a diminishing tendency.(5) Viewed from LISA agglomeration map ofST resource allocation efficiency in different periods, four agglomeration types have changed differently in spatial location and the range of spatial agglomeration. And the continuity of ST resource allocation efficiency in geographical space is gradually increasing.     

Spatial distribution and the scale effect of influencing factors of specialized and sophisticated enterprises that produce new and unique products in the Yangtze River Delta region: Based on the buffer and MGWR analyses北大核心CSCD

High-quality cultivation of specialized and sophisticated enterprises that produce new and unique products is an important starting point for consolidating the security foundation of China's industrial chain and supply chain. Using buffer zone analysis and the multi-scale geographically weighted regression (MGWR) model, this study explored the spatial distribution of specialized and sophisticated enterprises that produce new and unique products in the Yangtze River Delta region and influencing factors in 2021. The study found that: 1) Spatially, Shanghai is the main area where specialized and sophisticated enterprises that produce new and unique products are concentrated, followed by provincial capitals and cities on the coast and along rivers; The overall composition of the industry is unbalanced, and the real economic industries such as machinery and equipment manufacturing and high-tech manufacturing account for a relatively high proportion, but there are differences in different regions. 2) In terms of spatial agglomeration, differences between circles and the scale effect are obvious. Within each province, the spatial distribution of specialized and sophisticated enterprises that produce new and unique products in different cities is uneven. Region-wide, the overall spatial distribution pattern of "one pole and multiple cores" is evident. Shanghai is the main agglomeration area for these enterprises, and the provincial capital cities and cities that are the regional economic centers are the secondary agglomeration areas of these enterprises. 3) The four dimensions of influencing factors—physical geography, government, market, and society—have a scale effect on the spatial distribution of specialized and sophisticated enterprises that produce new and unique products. The degree of land development acts at a small scale, which is a local variable, and shows a large difference in the impact on the spatial distribution of these enterprises across the region. Factors such as elevation, government-business relationship, degree of marketization, number and scale of enterprises, degree of openness, logistics development level, and innovation environment are global variables, and except that the degree of marketization and the number of enterprises have a significant negative impact on the spatial distribution of these enterprises, the impact of all other factors is significantly positive. The research results can provide support for the optimization of the layout of new special expertise enterprise space in the Yangtze River Delta region, in order to provide reference for the formulation of new special expertise policies and industrial planning. © 2023, Editorial office of PROGRESS IN GEOGRAPHY. All rights reserved.     

塔里木河流域绿洲城镇发展与水土资源效益分析(英文)

This paper examines the spatial pattern of land and water resources as well as urbanization and their interactions in the Tarim River Basin, Xinjiang, China. In order to do so, we extract the data associated with efficiency of land and water resources and urbanization for the years of 1995, 2000, 2005 and 2008. Specifically the paper investigates the extent to which agglomeration of population and economic activities varies geographically and interplays with spatial pattern of resources efficiency through computation of Global Moran’s I index, Getis-Ord Gi* index and a coordinated development model. The method used provides clear evidence that urbanization, land and water resources efficiency have shown uneven spatial pattern due to oasis distribution, climate, and initial phase of urban development. Some conclusions can be drawn as follows.(1) Agglomeration and dispersion of urbanization are not consistent with those of land and water resources efficiency.(2) Evolution of the hot and cold spots of urbanization, and land and water resources efficiency, in different trajectories, indicate that there are no significant interactions between them.(3) The evidence that numbers of hot and cold spots of the three factors present varying structures reveals the dominance of unequal urban development in the study area.(4) Significant differences are also found between sub-river basins in terms of the three factors, which is a reflection of the complex physical geography of the area.(5) The degree of coordinated development of cities in the Tarim River Basin is generally low in part as a reflection of difference in spatial patterns of the three factors. It is also shown that the pattern of the degree of coordinated development is relatively stable compared with evolution of hot and cold spots of the three factors.     

2008-2014年祁连山区夏季降水的日变化特征及其影响因素（英文）

To investigate the diurnal variation of summer precipitation in the Qilian Mountains in the northeast Tibetan Plateau,the hourly precipitation amount for this region during the summers of 2008–2014 are analyzed using an hourly merged precipitation product at 0.1°×0.1° resolution.The main results are as follows.(1) The spatial distribution and temporal variation of mean hourly precipitation amount and frequency are generally similar and hourly precipitations in the eastern and middle portions are larger and more frequent than that in the western portion.The high value area of precipitation intensity is obviously different from that of precipitation amount and frequency.(2) The spatial distribution of daytime precipitation is generally similar to that of nighttime precipitation,and the daytime precipitation is heavier than the nighttime precipitation.(3) The change rate of precipitation has a maximum at 20:00 Beijing time,and a minimum at 12:00.The hourly precipitation amount significantly correlated with frequency,especially for the middle and eastern portions.     

A case study on Landscape Component Niche based on Landscape Pattern Indices: Yanchi,Ningxia Province,China

Yanchi County is located in the agro-pastoral ecotone and belongs to the ecologically fragile area of Northwest China.It is important to study the evolution of landscape pattern to curb its environmental degradation.In order to intuitively show how the landscape pattern of the study area changes over time,Landsat Thematic Mappers(TM)and Landsat Operational Land Imager(OLI)data of 1991,2000,2010 and 2017 were used.This paper attempts to apply niche theories and methods into landscape ecology,and constructs a niche model of landscape components by using"n-dimentional hypervolume niche theory"and landscape pattern indices.By evaluating the spatial and temporal evolution of niche from the perspective of two-dimensional space to reflect the changes of landscape pattern in the study area over the past 26 years,new theories and methods were introduced for the characterization of landscape pattern.The results indicate that:1)The larger the attribute and dominance value of landscape components,the higher the ecological niche and the stronger the control effect on the overall landscape.2)The ecological niche of each landscape component was significantly different,just as its control effect on the overall landscape.3)The dynamic change of the ecological niche of each landscape component was different,with grassland,unused land and arable land always in a high dominant position,although the ecological niche of construction land and water area was always low.In general,the introduction of niche theory into the landscape ecology provided a new method to study the changes in regional landscape pattern.     

黑河流域NDVI与环境因子的空间关联性（英文）

The Heihe River Basin is located in the arid and semi-arid regions of Northwest China. Here, the terrestrial ecosystem is vulnerable, making it necessary to identify the factors that could affect the ecosystem. In this study, MODIS-NDVI data with a 250-m resolution were used as a proxy for the terrestrial ecosystem. By combining these with environmental factors, we were able to explore the spatial features of NDVI and identify the factors influencing the NDVI distribution in the Heihe River Basin during the period of 2000–2016. A geographical detector(Geodetector) was employed to examine the spatial heterogeneity of the NDVI and to explore the factors that could potentially influence the NDVI distribution. The results indicate that:(1) the NDVI in the Heihe River Basin appeared high in the southeast while being low in the north, showing spatial heterogeneity with a q-statistic of 0.38. The spatial trend of the vegetation in the three sub-basins generally increased in the growing seasons from 2000 to 2016;(2) The results obtained by the Geodetector(as denoted by the q-statistic as well as the degree of spatial association between the NDVI and environmental factors) showed spatial heterogeneity in the associations between the NDVI and the environmental factors for the overall basin as well as the sub-basins. Precipitation was the dominant factor for the overall basin. In the upper basin, elevation was found to be the dominant factor. The dominant factor in the middle basin was precipitation, closely followed by the soil type. In the lower basin, the dominant factor was soil type with a lower q-statistic of 0.13, and the dominant interaction between the elevation and soil type was nonlinearly enhanced(q-statistic = 0.22).     

历史时期中国重大自然灾害时空分异特征

通过历史文献和史料记载的整理,对中国历史时期的重大自然灾害进行了系统的梳理,分析了公元前180 年-1911 年和民国时期重大自然灾害发生的频次和损失的时空格局特征,得出结论:(1) 对灾害发生的频次进行分析,不同灾种发生频次不同,空间格局呈现明显的地域分异,灾害的空间分布与灾种之间的关系明显;(2) 对灾害带来的损失进行分析,发现不同类型灾害发生的频次与灾害带来损失的空间格局并不相同。究其原因在于:(1) 各种自然灾害的孕灾环境不同,是其空间格局差异性的决定性因素;(2) 自然灾害带来的损失大小与经济和人口的集中程度密切相关。自然灾害损失较大的往往都是农业、文化、商贸较为发达的区域,这也是我国区域经济格局空间差异的必然。     

2005-2010年中国自然灾害救助应急响应的区域分异特征

应急响应是政府管理部门进行高效、科学应对各类突发事件的重要保障,受到世界各国的重视。针对重大自然灾害启动的自然灾害救助应急响应分四级,一般重大灾害一般启动四、三级响应,而特大灾害则需启动二、一级响应。本文统计分析了2005-2010年中国自然灾害救助应急响应的启动情况,结果表明:①应急响应南北分异特征明显,主要是由针对我国南方地区频繁发生的洪涝和台风灾害启动的四、三级等低级别响应决定,反映了近年一般重大灾害的发生以南方地区为主。②应急响应也呈现东西分异特征,其中,尤以针对中西部地区发生的特大地震、罕见的山洪泥石流以及影响严重的旱灾和低温雨雪冰冻等灾害启动的二、一级等高级别响应最为明显,反映了近年中西部地区灾害损失偏重发生。③中国针对各灾种的应急响应的区域分布特点,大致反映了各灾种的地理分布规律。     

“一带一路”沿线地区自然灾害危险性与灾损空间格局研究

灾害危险性和灾害损失是区域灾害风险评估的重要内容。以往研究大多基于国别尺度,无法表征国家内部和经济带沿线的灾害损失特征。本文基于“一带一路”沿线地区的洪涝、干旱、风暴、地震4类主要自然灾害的历史数据,提出灾害数据空间尺度下推方法,构建了基于省级尺度的灾害数据库,从灾害发生频次与灾害损失的角度,探讨了“一带一路”沿线地区主要灾害危险性和人口、经济损失的空间分布特征以及综合灾损高值区的主导灾害。研究表明2003—2018年间,“一带一路”沿线地区灾害发生广泛,各类灾害危险性和损失具有明显的集聚特征：81.4%区域均有灾害发生,洪涝灾害发生范围最广,风暴主要发生在沿海地区,干旱灾害集中在中国北部和泰国等地,地震多分布于地震带沿线;全域人口损失以洪涝（53%）、干旱（26%）为主,经济损失以洪涝（49%）、地震（23%）为主,各地区人口和经济损失因区域内人口和经济基础不同存在空间差异;大部分区域损失由单一灾害主导,仅小部分地区损失受多种灾害共同影响。研究结果提示我们应针对各灾害高危区、灾损高值区及各地区主导灾害制定相适应的防灾减灾措施,为未来“一带一路”的自然灾害风险防范与综合减灾、重大基础设施建设等提供支撑。     

1949-2015年中国典型自然灾害及粮食灾损特征

中国是一个自然灾害频发的国家,研究其自然灾害演变特征及粮食灾损规律,对实现中国社会经济可持续发展、解决中国粮食安全问题具有重要意义。本文先基于Python语言编程获取1949-2015年中国31省市自然灾害造成的受灾、成灾、绝收面积,构建灾害强度指数分析不同灾种的时序特征分异,利用趋势分析、ESDA方法分析不同灾种在省域空间的分布特征及冷热区;再获取1949-2015年粮食种植数据,通过粮食灾损估算模型、定义粮食灾损率、地理空间探测器,计算并检验中国粮食损失时空特征及分异性。结果表明：① 相比受灾面积曲线,本文构建的灾害程度指数能够更好揭示自然灾害时序演变特征;② 1949-2015年期间中国两大主力灾害（洪灾、旱灾）交替出现,未来5~10年以洪灾为主;③ 灾种排序旱灾>洪灾>风雹>低温>台风,其中旱灾、洪灾受灾占比过半;④ 省域不同灾种间空间趋势变化特征明显,区域受灾面积东部>西部,北部>南部,且北部灾种单一、南部多灾并发;⑤ 自然灾害受灾总和、旱灾、雹灾、低温空间上全局自相关性不显著,呈随机模式分布,洪涝、台风在空间分布上具有显著的全局自相关性,呈集聚模式;⑥ 1949-2015年灾害、灾损量、灾损率整体时序趋势呈现先升后降,2000年为临界点,空间分布具有异质性,单因子解释力度差异显著,多因子交互均呈非线性增强关系,胡焕庸线两侧冷热点分布呈两极化且其重心向北迁移。建议政府加强除旱减雹（西北）、除旱排内涝（东北）、排涝防冻（中部）、排涝预台（东南沿海）等工程技术措施;同时西北（环境恶劣）、东北（中国粮仓）应作为防灾减灾重点保护区,制定专项保护方案,以保证中国粮食丰产增收。     

中国飞蝗(Locusta migratoria)灾害地理分布模拟及其生物气候因子分析

飞蝗Locusta migratoria (Linnaeus)系斑翅蝗科Oedipodidae飞蝗属Locusta Linnaeus洲际性农业重大害虫，在我国主要包括东亚飞蝗L.migratoria manilensis (Meyen)、亚洲飞蝗[WTBX]L.migratoria[WTBZ] (Linnaeus)和西藏飞蝗L.migratoria tibetensis Chen。掌控飞蝗灾害的地理空间分布并预测起潜在的适宜分布区，对于我国飞蝗灾害的综合防控具有重要意义。结合三种中国飞蝗灾害记录地理信息和生物环境环境因子参数，应用最大熵模型(MaxEnt) 和地理信息技术(GIS) ，在3 km×3 km尺度上对三种飞蝗灾害在中国的地理分布空间格局梯度、灾害风险概率和风险等级进行了模拟预测与分析，并对影响分布的关键生物气候环境因子进行了分析。结果显示，蝗灾害风险区的地理分布模拟结果与历史记录完全符合，ROC检验表明MaxEnt 模型预测可靠性极高。三种飞蝗东亚飞蝗、亚洲飞蝗和西藏飞蝗在中国的灾害风险区总面积依次分别为315.87×10⁴ km²、395.80×10⁴ km²和125.00×10⁴ km²，分别占国土面积的33.43%、41.96% 和13.25%。东亚飞蝗和亚洲飞蝗的灾害风险区存在75.8×10⁴ km²的空间重叠，主要分布于我国农牧交错区及以南区域。三种飞蝗灾害风险区的地理梯度与分布格局与中国三大自然地理区高度吻合，其地理分布格局表现出显著的经度和纬度空间梯度异质性。刀切法检测（Jackknife test）表明，三种飞蝗灾害的主导生物—气候影响因子的不同导致了其地理分布格局的显著差异，表明蝗灾爆发概率同时受到各自不同飞蝗物种对气候环境的适应性与地理空间隔离作用的共同制约。研究结果可为我国飞蝗灾害的跨界联合全程防控、区域联网监测联控和综合治理提供参考依据。     

横断山区泥石流空间格局和激发雨量分异性研究

地形、降雨等环境因子决定了泥石流的时空分布特征,理解泥石流与这些因子的关系有助于区域泥石流灾害风险评估与防灾减灾工作。以横断山区为研究区域,选取降水、气候、地貌、地质、土地覆盖、土壤厚度、高差势能以及湿度指数等因子,利用地理探测器和灰度关联分析等方法,探讨了环境因子与泥石流沟空间分布的关系以及降水特征与泥石流灾害的时间关联性。结果表明,湿度指数是决定泥石流沟空间格局的最主要因子,其次是高差势能和土壤厚度,多年平均分布的降水特征对泥石流沟分布的影响较小。泥石流灾害事件与降水特征的时间关联具有较大的区域异质性。泥石流发生地的激发雨量、湿度指数、高差及土壤厚度的统计分布在不同地貌、地质和气候单元中有明显差异。这表明泥石流预警不仅需要考虑雨量等激发因子,还必须考虑其他影响因素的空间差异性。     

贫困村空间分布及影响因素分析——以乌蒙山连片特困区为例

针对目前贫困分布研究以大尺度为主而缺乏对小尺度的关注和致贫因素分析忽略个体效应或背景效应的不足,基于空间贫困视角,以乌蒙山片区为研究区域、贫困村为研究对象,运用空间点模式分析方法探究贫困村空间分布特征,并设计多层线性回归模型从贫困村和县域两个层面综合定量剖析贫困影响因素。研究发现：① 贫困村的空间聚集特征较为明显,总体分布呈现大分散小集中、散点-极核-轴带-团块并存的空间格局。② 贫困村的贫困程度受多层因素的显著影响。其中,村级影响因素为：人口密度、通路率、劳动力比例、遭受自然灾害频次、安全饮用水比例;县级影响因素为：人均地方生产总值、高中阶段毛入学率、植被覆盖率。③ 农村贫困来源于贫困村与县域的双重作用。因此在精准扶贫工作中,政府及相关部门可针对不同尺度对象有针对性地施策,合理配置扶贫资金。     

我国热带气旋潜在影响力指数分析

利用热带气旋路径资料和灾情资料,综合考虑热带气旋的频数、强度、范围以及持续时间,建立热带气旋潜在影响力指数,分析了1949-2009 年我国热带气旋的潜在影响力的空间格局和年际变化特征,并以0608 号超强台风“桑美”为例分析了该指数与灾害损失、过程极大风速、过程雨量的关系。研究结果表明：1949-2009 年间,我国的热带气旋的潜在影响力呈现出弱减少的趋势,这种趋势并不显著,但各阶段性的趋势比较明显;近20 年来,我国海南、广东、广西等华南沿海受热带气旋潜在影响力在下降,而浙江、福建、台湾等东南沿海省份受热带气旋潜在影响力在上升;潜在影响力指数最高的区域主要分布在台湾、海南、广东沿海、福建沿海以及浙江南部沿海等地;TCPI 与灾害损失、过程极大风速、过程降水量等有较好的相关性,并都通过了0.01 的显著性检验。     

中国民族乐器制造企业的空间格局

运用探索性空间数据分析、最邻近指数以及核密度等分析方法,并基于点与面2个方面对中国民族乐器制造企业的空间格局特征进行分析,结果表明：基于点的方面,中国民族乐器企业及其分类别的民族乐器企业的空间分布均呈显著集聚状态,且集聚度较高,其中吹奏乐器企业集聚度最低,而长三角、珠三角、环渤海地区以及滇、豫等区域是其重要的集聚区;基于面的方面,中国民族乐器企业及其分类别民族乐器制造企业分布均呈弱集聚状态;其热点区数量均很少,且分布与基于点的集聚区分析结果基本一致,而全国绝大部分的城市为冷点区域。中国民族乐器制造企业空间格局的影响因素可归纳为资源禀赋、历史基础以及集聚经济效应3个方面。     

基于生态系统服务的中国陆地生态风险评价

传统的生态风险评价主要依据是点源性威胁、区域景观格局变化等生态实体特征指标,忽略了与实体功能属性密切相关的人类福祉因素。将生态系统服务纳入生态风险评价体系是一个新的研究思路。本文运用GIS和遥感技术重构了中国陆地生态系统服务的空间图谱,采用生态风险分析模型给出了基于生态系统服务的中国陆地生态风险格局的定量描述和空间分布,划定了不同置信水平下的生态风险管控优先区。结果表明：① 2000-2010年中国陆地生态系统年均总生态系统服务指数取值在0~2.17之间,年际间呈现小幅波动趋势,年平均总指数在0.30~0.57之间变化,其中24.7%的区域显著增加,主要分布在台湾、云贵高原及新疆西北内陆区,37.1%的区域显著减少,主要分布在东北、青藏高原及中东部地区;② 不同置信水平下的中国陆地生态系统服务存在的风险损失不尽相同。如当置信水平为90%时,总生态系统服务指数的可能损失比例为24.19%,生态风险指数为0.253。比较置信水平和生态风险指数间的关系,发现当置信水平较高时,生态系统服务蒙受风险的概率相应降低,但此时出现风险时所承受的损失也对应增加;③ 以90%置信水平为例,中国生态地理区划的风险特征表现为：平均生态系统服务风险指数居前列的六位依次为内蒙古高原生态区、华北平原生态区、黄土高原生态区、东北平原生态区、横断山生态区、青藏高原生态区,极重度风险所占区域面积比例依次为55.89%、26.63%、24.35%、20.62%、18.70%、25.12%。