TMPA降水数据在澜沧江流域干旱监测中的评估(英文)

Drought is one of the most destructive disasters in the Lancang River Basin, which is an ungauged basin with strong heterogeneity on terrain and climate. Our validation suggested the version-6 monthly TRMM multi-satellite precipitation analysis (TMPA; 3B43 V.6) product during the period 1998 to 2009 is an alternative precipitation data source with good accuracy. By using the standard precipitation index (SPI), at the grid point (0.25°×0.25°) and sub-basin spatial scales, this work assessed the effectiveness of TMPA in drought monitoring during the period 1998 to 2009 at the 1-month scale and 3-months scale; validated the monitoring accuracy of TMPA for two severe droughts happened in 2006 and 2009, respectively. Some conclusions are drawn as follows. (1) At the grid point spatial scale, in comparison with the monitoring results between rain gauges (SPI1g) and TMPA grid (SPI1s), both agreed well at the 1-month scale for most of the grid points and those grid points with the lowest critical success index (CSI) are distributed in the middle stream of the Lancang River Basin. (2) The same as SPI1s, the consistency between SPI3s and SPI3g is good for most of the grid points at the 3-months scale, those grid points with the lowest were concentrated in the middle stream and downstream of the Lancang River Basin. (3) At the 1-month scale and 3-months scale, CSI ranged from 50% to 76% for most of the grid points, which demonstrated high accuracy of TMPA in drought monitoring. (4) At the 3-months scale, based on TMPA basin-wide precipitation estimates, though we tended to overestimate (underestimate) the peaks of dry or wet events, SPI3s detected successfully the occurrence of them over the five sub-basins at the most time and captured the occurrence and development of the two severe droughts happened in 2006 and 2009. This analysis shows that TMPA has the potential for drought monitoring in data-sparse regions.     

中国能源消费碳排放的空间计量分析(英文)

Based on energy consumption data of each region in China from 1997 to 2009 and using ArcGIS9.3 and GeoDA9.5 as technical support,this paper made a preliminary study on the changing trend of spatial pattern at regional level of carbon emissions from energy con-sumption,spatial autocorrelation analysis of carbon emissions,spatial regression analysis between carbon emissions and their influencing factors.The analyzed results are shown as follows.(1) Carbon emissions from energy consumption increased more than 148% from 1997 to 2009 but the spatial pattern of high and low emission regions did not change greatly.(2) The global spatial autocorrelation of carbon emissions from energy consumption in-creased from 1997 to 2009,the spatial autocorrelation analysis showed that there exists a "polarization" phenomenon,the centre of "High-High" agglomeration did not change greatly but expanded currently,the centre of "Low-Low" agglomeration also did not change greatly but narrowed currently.(3) The spatial regression analysis showed that carbon emissions from energy consumption has a close relationship with GDP and population,R-squared rate of the spatial regression between carbon emissions and GDP is higher than that between carbon emissions and population.The contribution of population to carbon emissions in-creased but the contribution of GDP decreased from 1997 to 2009.The carbon emissions spillover effect was aggravated from 1997 to 2009 due to both the increase of GDP and population,so GDP and population were the two main factors which had strengthened the spatial autocorrelation of carbon emissions.     

1990年以来中国小麦农业气象灾害时空变化特征(英文)

Agro-meteorological disasters(AMD) have become more frequent with climate warming. In this study, the temporal and spatial changes in the occurrence frequency of major meteorological disasters on wheat production were firstly explored by analyzing the observed records at national agro-meteorological stations(AMS) of China from 1991 to 2009. Furthermore, impact of climate change on AMD was discussed by comparing the warmer decade(2000–2009) with another decade(1991–2000). It was found that drought was the most frequent disaster during the last two decades, with a highest proportion of 79%. And the frequency of AMD increased significantly with climate change. Specifically, the main disasters occurred more frequently in the reproductive period than in the vegetative period. Besides, the spatial changes in the AMD frequency were characterized by region-specific. For example, the wheat cultivation areas located on the Loess Plateau and the middle-lower reaches of the Yellow River suffered mainly from drought. All these results were strongly linked to climate change in China. Therefore, sound adaptation options should be taken based on the latest changes of AMD under global warming to reduce agricultural damages.     

中国东北地区降雪的不均匀性特征分析(英文)

Based on 1961–2005 observed winter precipitation data in Northeast China, the temporal and spatial variations of snow concentration degree (SCD) and snow concentration period (SCP), together with the circulation characteristics when there is a higher SCD, are computed and analyzed. Results show that SCD in Northeast China presents a yearly rising tendency and SCP decreases obviously. In terms of decadal variation, there is a 12-year periodic variation in PCP, and since the mid-1970s there has been an 8-year short periodic variation. As to spatial variation, SCD in winter of Northeast China has increased gradually from the eastern part to the western, and the minimum value of SCD occurs in the east of Jilin Province, while the high value center is observed in the central part of the province. For the whole Northeast China, the variation tendencies are consistent in the eastern and central parts, where SCD presents a rising tendency and SCP shows a decreasing tendency. SCD in the southwestern and northern parts has a slight rising tendency, with SCD in the southwestern part having the slightest increasing tendency, and SCP in the northern part showing the slightest decreasing tendency. When a high SCD value is observed, the whole region is controlled by the East Asian deep trough at 500 hPa, and the trough becomes deeper in the western part, while a high pressure, which is easily formed and intensified in the eastern part, makes the East Asian deep trough move eastward slowly. Upper-level jet stream and low-level jet stream co-exist, and the former is stronger and takes more of a southwestward position than the latter. The high value zone of water vapor transport over the Pacific is intensified obviously, and the extent also increases. Northeast China is influenced by the water vapor transported to the northwest along the north of the high value center.     

中国畜禽养殖的空间分析及分区研究(英文)

The capacity of livestock breeding in China has increased rapidly since 1949, and the total output of meat, poultry and eggs maintains the world’s top first in recent 20 years. Livestock emissions and pollution is closely associated with its population and spatial distribution. This paper aims to investigate the spatial patterns of livestock and poultry breeding in China. Using statistical yearbook and agricultural survey in 2007, the county-level populations of livestock and poultry are estimated as equivalent standardized pig index (ESP), per cultivated land pig index (PCLP) and per capita pig index (PCP). With the help of spatial data analysis (ESDA) tools in Geoda and ArcGIS software, especially the Moran’s I and LISA statistics, the nationwide global and local clustering trends of the three indicators are examined respectively. The Moran’s I and LISA analysis shows that ESP and PCP are significantly clustering both globally and locally. However, PCLP is clustering locally but not significant globally. Furthermore, the thematic map series (TMS) and related gravity centers curve (GCC) are introduced to explore the spatial patterns of livestock and poultry in China. The indicators are classified into 16 levels, and the GCCs for the three indicators from level 1 to 16 are discussed in detail. For districting purpose, each interval between gravity centers of near levels for all the three indicators is calculated, and the districting types of each indicator are obtained by merging adjacent levels. The districting analysis for the three indicators shows that there exists a potential uniform districting scheme for China’s livestock and poultry breeding. As a result, the China’s livestock and poultry breeding would be classified into eight types: extremely sparse region, sparse region, relatively sparse region, normally sparse region, normal region, relatively concentrated region, concentrated region and highly concentrated region. It is also found that there exists a clear demarcation line between the concentrated and the sparse regions. The line starts from the county boundary between Xin Barag Left Banner and Xin Barag Right Banner, Inner Mongolia Autonomous Region to the west coast of Dongfang County, Hainan Province.     

中国西南地区农业干旱灾害风险空间特征

21世纪,中国西南地区干旱灾害农业综合损失率远超过全国平均水平,给人类生活带来了巨大的风险。本文依据灾害系统理论,利用遥感、气象和地理信息数据与技术建立致灾因子危险性、孕灾环境脆弱性、承灾体易损性和防灾减灾能力可靠性等4个因子的风险指数和模型,基于4个因子建立农业干旱灾害综合风险评估模型,在GIS平台下计算了干旱灾害综合风险指数。结果表明:西南地区干旱灾害风险格局模式具有明显的地带性和复杂性,全区并不一致,高风险区主要位于四川盆地和云贵川三省交界处,北部高于南部,东部高于西部,从西南到东北依次增加。随着干旱灾害综合风险指数的变化,干旱灾害风险的模式具有不同的格局。西南地区干旱灾害风险主要受复杂地形和多样气候带的影响,还受植被盖度、农业经济水平、土壤状况等地理环境影响,同时,喀斯特地貌和相对薄弱的抗旱能力也使得西南地区农业干旱灾害风险较高。     

基于情景的中国1951-2010年极端高温灾害的危险性分析(英文)

China is physically and socio-economically susceptible to global warming-derived high temperature extremes because of its vast area and high urban population density. This article presents a scenario-based analysis method for high temperature extremes aimed at illustrating the latter’s hazardous potential and exposure across China. Based on probability analysis, high temperature extreme scenarios with return periods of 5, 10, 20, and 50 years were designed, with a high temperature hazard index calculated by integrating two differentially-weighted extreme temperature indices (maximum temperature and high temperature days). To perform the exposure analysis, a land use map was employed to determine the spatial distribution of susceptible human activities under the different scenarios. The results indicate that there are two heat-prone regions and a sub-hotspot occupying a relatively small land area. However, the societal and economic consequences of such an environmental impact upon the North China Plain and middle/lower Yangtze River Basin would be substantial due to the concentration of human activities in these areas.     

中国城市群分布及范围的定量评价(英文)

Urban clusters are the expected products of high levels of industry and urbanization in a country, as well as being the basic units of participation in global competition. With respect to China, urban clusters are regarded as the dominant formation for boosting the Chinese urbanization process. However, to date, there is no coincident, efficient, and credible methodological system and set of techniques to identify Chinese urban clusters. This research investigates the potential of a computerized identification method supported by geographic information techniques to provide a better understanding of the distribution of Chinese urban clusters. The identification method is executed based on a geographic information database, a digital elevation model, and socio-economic data with the aid of ArcInfo Macro Language programming. In the method, preliminary boundaries are identified accord-ing to transportation accessibility, and final identifications are achieved from limiting city numbers, population, and GDP in a region with the aid of the rasterized socio-economic dataset. The results show that the method identifies nine Chinese urban clusters, i.e., Pearl River Delta, Lower Yangtze River Valley, Beijing-Tianjin-Hebei Region, Northeast China Plain, Middle Yangtze River Valley, Central China Plains, Western Taiwan Strait, Guanzhong and Chengdu-Chongqing urban clusters. This research represents the first study involving the computerized identification of Chinese urban clusters. Moreover, compared to other related studies, the study’s approach, which combines transportation accessibility and socio-economic characteristics, is shown to be a distinct, effective and reliable way of identifying urban clusters.     

中国流动人口地域类型——划分方法及空间分布(英文)

With the rapid increase of the number and influence of floating population in China,it is urgently needed to understand the regional types of China’s floating population and their spatial characteristics. After reviewing the current methods for identifying regional types of floating population,this paper puts forward a new composite-index identification method and its modification version which is consisted of two indexes of the net migration rate and gross migration rate. Then,the traditional single-index and the new composite-index identification methods are empirically tested to explore their spatial patterns and characteristics by using China’s 2000 census data at county level. The results show:(1) The composite-index identification method is much better than traditional single-index method because it can measure the migration direction and scale of floating simultaneously,and in particular it can identify the unique regional types of floating population with large scale of immigration and emigration. (2) The modified composite-index identification method,by using the share of a region’s certain type of floating population to the total in China as weights,can effectively correct the over-or under-estimated errors due to the rather large or small total population of a region. (3) The spatial patterns of different regional types of China’s floating population are closely related to the regional differentiation of their natural environment,population density and socio-economic development level. The three active regional types of floating population are mainly located in the eastern part of China with lower elevation,more than 800 mm precipitation,rather higher population densities and economic development levels.     

中国东北红河国家级自然保护区湿地植被空间格局与环境梯度关系(英文)

Quantifying correlation between the spatial patterns of natural wetland plants and environmental gradient gives better understanding of wetland habitats, which is the fundamental for the strategy making on the protection and restoration of natural wetlands. In this study, the spatial patterns of wetland plants and the environmental gradient of wetland habitats were assessed in the Honghe National Nature Reserve (HNNR) in Northeast China, a wetland of international importance on the Ramsar list. Biophysical parameters’ values of wetland plants were obtained by field sampling methods, and wetland mapping at the community scale was completed using remote sensing techniques. Digital delineation of the surface water system, hydrological zoning and wetness index were produced by spatial analysis methods in Geographic Information System. An ecological ordination method and two clustering methods were used to quantify the relationship between the spatial distribution patterns of wetland plants and the corresponding environmental gradients. Such quantitative analyses also present the specific diversity of different types of wetland plants based on the environmental attributes of their habitats. With the support from modern geo-information techniques, the experimental results indicate how four ecotypes of wetland plants spatially transit from forest swamp, shrub wetland and meadow into marsh wetland with increasing wetness index and water table. And they also show how wetland spatial distribution patterns are controlled by an environmental gradient of wetness. Another key finding of this research work is that our results present the exact fundamental differences between marsh and non-marsh plants of 11 wetland plant communities within the core study area. Hence, this case study gives a good sample for better understanding of the complex correlation between the spatial patterns of wetland plants and their environmental attributes using advanced digital analysis methods. It is also useful to show how to integrate geoinformatic techniques with statistical analysis methods based on the field data base.     

广西壮语地名分布与演化的GIS分析

以壮族人口聚居的广西壮族自治区为研究区,通过解读《中华人民共和国地名大辞典》等资料,构建了一个乡镇、县、市的壮语地名地理信息系统(GIS)数据库,并借助空间可视化技术直观显示了壮语地名集中程度从广西西南部左右江流域和西部山区向东部逐渐降低。回归模型揭示了壮语地名的分布相对集中于地势高、坡度陡的边远地区。对命名时代的分析表明,壮语地名的几何中心随时间东移,汉语地名的几何中心西推,两者逐渐靠拢,表明二者在空间分布上的趋同,映证了广西逐渐走向壮汉杂居的历史过程。本文演示GIS和相关科学分析(包括空间分析和数理统计)方法用于历史文化研究的潜力,旨在促进自然科学与人文社会科学的有机结合,推动交叉学科的发展。     

空间数据分析与空间模型

虽然GIS已在各个领域得到广泛应用,但它相对较弱的空间分析功能正在限制其应用的广度和深度。文中系统论述了空间数据的基本特征,GIS中空间数据分析的基本需求,空间统计分析,空间数据探索分析以及空间模型,探讨了GIS与空间模型结合的必要性,结合途径以及结合中的问题与对策。     

中国贫困村测度与空间分布特征分析

农村贫困问题是中国全面建成小康社会的主要障碍之一。面向当前国家瞄准贫困村和贫困人口的精准脱贫战略需求,基于“十二五”期间全国贫困村“整村推进”项目村数据,构建村级多维贫困综合测度模型,并利用加权核密度模型、空间自相关方法等,从不同尺度、不同视角系统测度并分析了研究区贫困村的相对贫困特征。结果表明：① 贫困程度上,“十二五”期间贫困村呈中间大,两头小的“橄榄型”结构,省级、县级尺度下贫困深度与当地经济、区位、政策、自然环境等因素相关;② 空间分布上,全国贫困村分布呈现出东部和西北部稀疏、中部和西南部密集的“夹层”形空间异质性格局,同时存在多个不同量级、呈“星点”式分布的贫困核心;③ 中国贫困村的多维贫困存在较强的全局空间依赖性,局部呈现为高—高区与低—低区集中式分布、高—低区与低—高区离散夹杂式分布,且整体表现为西高东低的“阶梯状”格局。     

基于GIS的新疆气温数据栅格化方法研究

以新疆99个气象台站1971-2010年年平均气温为数据源,采用多元回归结合空间插值的方法对新疆区域气温数据进行栅格化研究。建立了年平均气温与台站经纬度和海拔高度的多元回归模型,对于残差数据的插值采用了反距离权重法(IDW) 、普通克立格法 (Kriging)和样条函数法(Spline)3种目前应用广泛的空间插值方法,针对于这3种方法进行了基于MAE和RMSIE的交叉验证和对比分析,结果表明在新疆的年平均气温的GIS插值方案中,IDW方法精度总体要高于其他两种插值方法。     

Drought identification and characterization in Jordan

A comparison between identified droughts was carried out through local and regional analysis. Comprehensive analyses of data for stationarity and randomness have been carried out with three tests, Student's t -test, Kendall's τ test and Turning point test. The calendar year, water year, and trimester time-scales were considered. For each series four different thresholds were used, mean, median, mean minus standard deviation and 35% quantile. The numbers of the drought periods, for the calendar series, are almost the same locally. Different periods and percentages are noticed with water year series, and with no consistency in results. Trimester series are with more drought periods and longer. The last decade has been characterized by more frequent and longer droughts in Jordan.     

空间信息分析技术

在GIS技术日趋成熟和空间数据极大丰富的今天,通过分析空间数据探索空间过程机理正变得日益迫切。空间信息分析技术至少包括以下六个主要方面:(1)空间数据获取和预处理;(2)属性数据空间化和空间尺度转换;(3)空间信息探索分析;(4)地统计;(5)格数据分析;(6)复杂信息反演和预报。本文提出了解决具体应用问题一般的空间数据分析计算、结果解释和反馈程序。认为空间过程的一般共性和作为共同的研究对象,各种不同的方法技术最终可能导致空间数学(spatialmathematics)的产生,同时发展鲁棒的空间分析软件包对于普及空间数学是必要的。     

基于多维Copula的中国干旱特征及危险性分析

干旱是中国主要的自然灾害之一.在全国开展干旱的特征分析,评估干旱的发生概率,有利于宏观了解中国整体干旱风险格局,对干旱监测和预警工作具有重要意义.基于1980—2019年国家气象科学数据中心地面气候资料日值数据集计算标准化降水蒸散指数(SPEI),通过游程理论识别历史干旱事件并提取干旱历时、干旱强度和烈度峰值3个特征变...     

近50 年西南地区极端干旱气候变化特征

利用中国气象局整编的1960-2009 年西南地区108 站逐日气温、降水等资料,计算年、月地表湿润指数,并进行标准化,统计极端干旱发生频率,对年际、年代际、季风期和非季风期的极端干旱变化特征进行分析,得出结论：(1) 整体上,四川盆地西南部、横断山区南端、广西南部沿海和贵州北部是近50 年来年极端干旱发生频率明显增加的地区;年代际变化上,20 世纪60-80 年代极端干旱呈逐渐减少趋势,高发区交替出现在东南-西北-东,90 年代下降明显,整个地区都转湿,进入21 世纪后,极端干旱距平呈现正距平,且增幅较大,区域间差异却显著减小。(2) 季风期与非季风期的极端干旱变化有很大差异,季风期极端干旱频率在不断增加,多发生在四川盆地周边海拔较高的山区、广西大部和“帚形山脉”地带,海拔对季风期极端干旱发生频率有一定影响;非季风期缓慢下降,整体偏湿。(3) 通过滑动t 检验和小波分析发现,季风期西南极端干旱在2003 年发生突变,非季风期在1989 年突变,年极端干旱发生频率是季风期和非季风期的突变叠加的结果;年极端干旱存在准5年和准12 年的周期变化。     

中国低碳城市评价与空间格局分析

城市是人类生产和消费活动最为集中的区域,带来了大量的能源消耗和碳排放,低碳城市受到国内外学者广泛探讨。本文从低碳开发、低碳经济、低碳环境、城市规模与能源消耗5个方面22个指标构建了低碳城市评价体系,引入遥感影像中的DMSP-OLS夜间灯光数据集与PM2.5浓度反演影像;利用因子分析、聚类分析及空间相关性分析,将2006年及2010年284个地级及以上城市按照低碳水平分为低碳、相对低碳、相对高碳、高碳四类城市;根据驱动力分为环境主导型、居民主导型、城镇化主导型及产业主导型四种城市类型;空间上识别出京津冀、长三角、山东省及珠三角地区具有低碳城市发展集聚效应;低碳城市发展水平受城市行政等级、产业转型等因素影响。     

中国西部兰白西城市群经济增长结构分解及空间特征

采用偏离-份额四分量模型,分解2010-2015年兰白西城市群41个县（区）经济增长结构;采用空间数据分析方法,分析41个县（区）经济增长总量及各分量空间特征。结果表明：（1）兰白西城市群呈现以兰州市和西宁市为双核心的"中心-外围"经济结构,兰州市的经济中心地位更为显著。（2）根据经济增长总量及各分量,将兰白西城市群41个县（区）分为经济快速增长型、经济滞后增长型、竞争力优势推动型和资源配置优势推动型等4种类型。（3）经济增长总量、份额偏离分量、产业结构分量在空间上存在集聚性特征,竞争力分量在空间上存在随机分布性特征,资源配置分量在空间上存在负相关性特征。（4）份额偏离分量、产业结构分量与经济增长总量的空间重合度较高,竞争力分量、资源配置分量与经济增长总量的空间重合度有待优化。