共查询到20条相似文献，搜索用时 187 毫秒
1.
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. 相似文献
2.
Research into urban expansion patterns and their driving forces is of great significance for urban agglomeration development planning and decision-making.In this paper,we reveal the multi-dimensional characteristics of urban expansion patterns,based on the intensity index of the urban expansion,the differentiation index of the urban expansion,the fractal dimension index,the land urbanization rate,and the center of gravity model,by taking the Beijing-Tianjin-Hebei(Jing-Jin-Ji)urban agglomeration as an example.We then build the center of gravity-geographically and temporally weighted regression(GTWR)model by coupling the center of gravity model with the GTWR model.Through the analysis of the temporal and spatial patterns and by using the center of gravity-GTWR model,we analyze the driving forces of the urban land expansion and summarize the dominant development modes and core driving forces of the Jing-Jin-Ji urban agglomeration.The results show that:1)Between 1990 and 2015,the expansion intensity of the Jing-Jin-Ji urban agglomeration showed a down-up-down trend,and the peak period was in 2005-2010.Before 2005,high-speed development took place in Beijing,Tianjin,Baoding,and Langfang;after 2005,rapid development was seen in Xingtai and Handan.2)Although the barycenter of cities in the Jing-Jin-Ji urban agglomeration has shown a divergent trend,the local interaction between cities has been enhanced,and the driving forces of urban land expansion have shown a characteristic of spatial spillover.3)The spatial development mode of the Jing-Jin-Ji urban agglomeration has changed from a dual-core development mode to a multi-core development mode,which is made up of three functional cores:the transportation core in the northern part,the economic development core in the central part,and the investment core in the southern part.The synergistic development between each functional core has led to the multi-core development mode.4)The center of gravity-GTWR model combines the analysis of spatial and temporal nonstationarity with urban spatial interaction,and analyzes the urban land expansion as a space-time dynamic system.The results of this study show that the model is a feasible approach in the analysis of the driving forces of urban land expansion. 相似文献
3.
青藏高原植被覆盖变化与降水关系 总被引：15，自引：6，他引：9
The temporal and spatial changes of NDVI on the Tibetan Plateau, as well as the relationship between NDVI and precipitation, were discussed in this paper, by using 8-km resolution multi-temporal NOAA AVHRR-NDVI data from 1982 to 1999. Monthly maximum NDVI and monthly rainfall were used to analyze the seasonal changes, and annual maximum NDVI, annual effective precipitation and growing season precipitation (from April to August) were used to discuss the interannual changes. The dynamic change of NDVI and the corre- lation coefficients between NDVI and rainfall were computed for each pixel. The results are as follows: (1) The NDVI reached the peak in growing season (from July to September) on the Tibetan Plateau. In the northern and western parts of the plateau, the growing season was very short (about two or three months); but in the southern, vegetation grew almost all the year round. The correlation of monthly maximum NDVI and monthly rainfall varied in different areas. It was weak in the western, northern and southern parts, but strong in the central and eastern parts. (2) The spatial distribution of NDVI interannual dynamic change was different too. The increase areas were mainly distributed in southern Tibet montane shrub-steppe zone, western part of western Sichuan-eastern Tibet montane coniferous forest zone, western part of northern slopes of Kunlun montane desert zone and southeastern part of southern slopes of Himalaya montane evergreen broad-leaved forest zone; the decrease areas were mainly distributed in the Qaidam montane desert zone, the western and northern parts of eastern Qinghai-Qilian montane steppe zone, southern Qinghai high cold meadow steppe zone and Ngari montane desert-steppe and desert zone. The spatial distribution of correlation coeffi- cient between annual effective rainfall and annual maximum NDVI was similar to the growing season rainfall and annual maximum NDVI, and there was good relationship between NDVI and rainfall in the meadow and grassland with medium vegetation cover, and the effect of rainfall on vegetation was small in the forest and desert area. 相似文献
4.
The delta evolution and erosion process of the abandoned Yellow River Delta(AYRD) have been extensively studied. However, the variation of sediment at a large littoral scale along the north coast of Jiangsu is less understood. In this study, the data of surface sediment samples obtained in the littoral area of the Yellow River Delta in 2006 and 2012 is used to study the sediment variability and sediment transport trends by using the geostatistics analysis tool and the grain size trend analysis model. In order to ensure the applicability of the model, the geostatistics method is used to determine the characteristic distance(Dc) with the average range value(Ao) of grain size parameter. Filtering method(removing data that not at a sampling station) is used to improve accuracy of data selection. The results show that sedimentary spatial correlation in Lianyun Port area and southern part of the abandoned Yellow River Delta(AS) is better than that in the northern part of the abandoned Yellow River Delta(AN). Sediment in the area is found to be anisotropy at the northeast–southeast direction. The grain size trend analysis reveals that the sediment trend is towards bayhead and southerly in the Haizhou Bay, southeasterly along the shoreline in the south Lianyun Port, northwesterly in AN and easterly–southeasterly in AS respectively. The investigation of possible relationships between Dc, Ao, sediment transport and delta evolution shows a close link between Dc and Ao of one sediment combination. It is also found that sediment transport trends could reasonably represent the delta evolution to a certain degree. 相似文献
5.
北京城市蔓延的测度与分析 总被引：5，自引：2，他引：3
Concerning about the rapid urban growth in recent China, this study takes Beijing as a case and puts forward that urban sprawl can be measured from spatial configuration, urban growth efficiency and external impacts, and then develops a geo-spatial indices system for measuring sprawl, a total of 13 indicators. In order to calculate these indices, different sources data are selected, including land use maps, former land use planning, land price and floor-area-ratio samples, digitized map of the highways and city centers, population and GDP statistical data, etc. Various GIS spatial analysis methods are used to spatialize these indices into 100m×100m cells. Besides, an integrated urban sprawl index is calculated by weight sum of these 13 indices. The application result indicates that geo-spatial indices system can capture most of the typical features and interior differentia of urban sprawl. Construction land in Beijing has kept fast growing with large amount, low efficiency and disordered spatial configuration, indicating a typical sprawling tendency. The following specific sprawl features are identified by each indicator: (1) typical spatial configuration of sprawling: obvious fragmentation and irregularity of landscape due to unsuccessful enforcement of land use planning, unadvisable pattern of typical discontinuous development, strip development and leapfrog development; (2) low efficiency of sprawl: low development density, low population density and economic output in newly developed area; and (3) negative impacts on agriculture, environment and city life. According to the integrated sprawl index, the sprawling amount in the northern part is larger than that in the southern, but the sprawling extent is in converse case; most sprawling area include the marginal area of the near suburbs and the area between highways, etc. Four sprawling patterns are identified: randomly expansion at urban fringe, strip development along or between highways, scattered development of industrial land, leapfrog development of urban residence and industrial area. 相似文献
6.
The simulation of LUCC based on Logistic-CA-Markov model in Qilian Mountain area,China 总被引：2，自引：0，他引：2
The Qilian mountain area was examined for using the Logistic-CA-Markov coupling model combined with GIS spatial analyst technology to research the transformation of LUCC, driving force system and simulate future tendency of variation. Results show that:(1) Woodland area decreased by 12.55%, while grassland, cultivated land, and settlement areas increased by 0.22%, 7.92%, and 0.03%, respectively, from 1986 to 2014. During the period of 1986 to 2000, forest degradation in the middle section of the mountain area decreased by 1,501.69 km~2. Vegetation cover area improved, with a net increase of grassland area of 38.12 km~2 from 2000 to 2014.(2) For constructing the system driving force, the best simulation scale was 210m×210m. Based on logistic regression analysis, the contribution(weight) of composite driving forces to land use and cover change was obtained, and the weight value was more objectively compared with AHP and MCE method.(3) In the natural scenarios, it is predicted that land use and cover distribution maps of Qilian mountain area in 2028 and 2042, and the Lee-Sallee index test was adopted. Over the next 27 years(2015–2042), farmland, woodland, grassland, settlement areas show an increasing trend, especially settlements with an obvious change of 0.56%. The area of bare land will decrease by 0.89%. Without environmental degradation, tremendous structural change of LUCC will not occur, and typical characteristic of the vertical zone of the mountain would remain. Farmland and settlement areas will increase, but only in the vicinity of Qilian and Sunan counties. 相似文献
7.
ZHANGBai ZHANGShuqing WANGAihua ZHANGJunyan 《地理学报(英文版)》2003,13(2):201-207
Using the methods of combining landscape ecology with GIS spatial analysis,this paper analyses the dynamics of the marsh landscape stucture of the Sanjing Plain in the past 20 years,furthermore,taking Fujin County,located in the north of the plain,as an example,analyzes the conversion between marsh and other land use types.It is shown that the marsh in the Sanjiang Plain decreased greatly in the past 20 years,but the trend has begun to reverse,The marsh area decreased by 51.33% from 1980 to 1996,whereas it decreased by 4.19% from 1996 to 2000.The fragmentation of the marsh increased;the number of the patches increased by 326 from 1986 to 1996,whereas it only increased by 18 patches from 1996 to 2000,It is obvious that the speed of patches number diminished and the marsh fragmentation decreased,which shows that the reclamation of the marsh converted from the fragmentation to the brim in a large area of the marsh.The reclaimed marsh has mainly converted to paddy field and dry land .Large area of the marsh.The reclaimed marsh has mainly converted to paddy fiedld and dry land.Large-scale reclamation in the Sanjiang Plain influences its natural environment directly:the climate of the region turns from cold and wet to warm and dry,which makes the marsh both in the low-temperature northern part and in the deeply stagnant eastern part suitable for further agricultural development. 相似文献
8.
基于GIS的中国人口重心的密度分级与曲线特征 总被引：1，自引：1，他引：0
In this paper, with the spatial analysis functions in ArcGIS and the county-level census data of 2000 in China, the population density map was divided and shown by classes, meanwhile, the map system of population distribution and a curve of population centers were formed; in accordance with the geographical proximity principle, the classes of population densities were reclassified and a population density map was obtained which had the spatial clustering characteristic. The multi-layer superposition based on the population density classification shows that the population densities become denser from the Northwest to the Southeast; the multi-layer clustering phenomenon of the Chinese population distribution is obvious, the populations have a water-based characteristic gathering towards the rivers and coastlines. The curve of population centers shows the population densities transit from the high density region to the low one on the whole, while in low-density areas there are relatively dense areas, and in high-density areas there are relatively sparse areas. The reclassification research on the population density map based on the curve of population centers shows that the Chinese population densities can be divided into 9 classes, hereby, the geographical distribution of Chinese population can be divided into 9 type regions: the concentration core zone, high concentration zone, moderate concentration zone, low concentration zone, general transitional zone, relatively sparse area, absolute sparse area, extreme sparse area, and basic no-man's land. More than 3/4 of the population of China is concentrated in less than 1/5 of the land area, and more than half of the land area is inhabited by less than 2% of the population, the result reveals a better space law of China’s population distribution. 相似文献
9.
青藏高原夏季上空水汽含量演变特征及其与降水的关系(英文) 总被引：4，自引：0，他引：4
By using the observed monthly mean temperature and humidity datasets of 14 radiosonde stations and monthly mean precipitation data of 83 surface stations from 1979 to 2008 over the Tibetan Plateau(TP),the relationship between the atmospheric water vapor(WV) and precipitation in summer and the precipitation conversion efficiency(PEC) over the TP are analyzed.The results are obtained as follows.(1) The summer WV decreases with increasing altitude,with the largest value area observed in the northeastern part of the TP,and the second largest value area in the southeastern part of the TP,while the northwestern part is the lowest value area.The summer precipitation decreases from southeast to northwest.(2) The summer WV presents two main patterns based on the EOF analysis:the whole region consistent-type and the north-south opposite-type.The north-south opposite-type of the summer WV is similar to the first EOF mode of the summer precipitation and both of their zero lines are located to the north of the Tanggula Mountains.(3) The summer precipitation is more(less) in the southern(northern) TP in the years with the distribution of deficient summer WV in the north while abundant in the south,and vice versa.(4) The PEC over the TP is between 3% and 38% and it has significant spatial difference in summer,which is obviously bigger in the southern TP than that in the northern TP. 相似文献
10.
《地理学报(英文版)》2017,(7)
In this paper, we analyzed the spatial patterns of cultivated land change between 1982 and 2011 using global vector-based land use/land cover data.(1) Our analysis showed that the total global cultivated land area increased by 528.768×104 km~2 with a rate of 7.920×104 km~2/a, although this increasing trend was not significant. The global cultivated land increased fastest in the 1980 s. Since the 1980 s, the cultivated land area in North America, South America and Oceania increased by 170.854×104 km~2, 107.890×104 km~2, and 186.492×104 km~2, respectively. In contrast, that in Asia, Europe and Africa decreased by 23.769×104 km~2, 4.035×104 km~2 and 86.76×104 km~2, respectively. Furthermore, the cultivated land area in North America, South America and Oceania exhibited significant increasing trends of 7.236× 104 km~2/a, 2.780×104 km~2/a and 3.758×104 km~2/a, respectively. On the other hand, that of Asia, Europe and Africa exhibited decreasing trend rates of –5.641×104 km~2/a, –0.831×104 km~2/a and –0.595×104 km~2/a, respectively. Moreover, the decreasing trend in Asia was significant.(2) Since the 1980 s, the increase in global cultivated lands was mainly due to converted grasslands and woodlands, which accounted for 53.536% and 26.148% of the total increase, respectively. The increase was found in southern and central Africa, eastern and northern Australia, southeastern South America, central US and Alaska, central Canada, western Russia, northern Finland and northern Mongolia. Among them, Botswana in southern Africa experienced an 80%–90% increase, making it the country with the highest increase worldwide.(3) Since the 1980 s, the total area of cultivated lands converted to other types of land was 1071.946×104 km~2. The reduction was mainly converted to grasslands and woodlands, which accounted for 57.482% and 36.000%, respectively. The reduction occurred mainly in southern Sudan in central Africa, southern and central US, southern Russia, and southern European countries including Bulgaria, Romania, Serbia and Hungary. The greatest reduction occurred in southern Africa with a 60% reduction.(4) The cultivated lands in all the continents analyzed exhibited a trend of expansion to high latitudes. Additionally, most countries displayed an expansion of newly increased cultivated lands and the reduction of the original cultivated lands. 相似文献
11.
1991 年以来长三角快速城市化地区生态经济系统协调度评价及其空间演化模式 总被引：12，自引：0，他引：12
以长江三角洲经济区1991、2001、2008 年的Landsat TM影像解译数据为基础,以长三角90 个县(市、市区) 为基本研究单元,构建空间数据转换模型、ESV模型、EEH模型,借助ArcGIS 9.3 平台对海量的栅格和矢量数据进行空间分析,依据ESV指数和EEH指数揭示长三角经济发展与生态环境系统的相关关系和演变特征,并进行功能分区和模式提炼.研究表明:① 1991 年以来长三角地区土地利用类型大幅转换,城镇面积增长最大,来源主要是水田、旱地、草地、园地和其他用地;② ESV模型研究发现,1991-2001 时段长三角生态系统呈现恶化趋势,2001-2008 时段恶化幅度有所减缓,同时证明水域、水田变为城镇和旱地的开发行为对生态系统的稳定性具有极大的伤害;③ 1991 年来GDP空间格局为中、南部高北部低,其中1991-2001 时段中部增长率明显高于北部,2001-2008 时段中部增长率明显高于南北;④依据EEH指数将长三角分为12 类区域,EEH空间特征为生态冲突区居中心区位,生态协调区居边缘区位,并且按EEH由低到高呈现出明显的核心-边缘空间结构;1991-2001 时段长三角生态-经济关系已经出现了集中型初步恶化趋势,2001-2008 时段则由集中型初步恶化趋势向分散型恶化与协调并存状态;⑤ 通过空间数据转换模型将长三角分为5 种生态经济演变类型分区:初始恶化区、初始协调区、持续恶化区、协调降低区、协调升级区;⑥ 总结出长三角EEH的空间演变模式:梯度模式与核心边缘模式共存,其中一级梯度模式为北中南三大横向梯度带,二级梯度模式为长三角南北两翼的东中西三大纵向梯度带;核心边缘模式概括为7 大组团:即苏锡常沪组团、南京组团、绍甬组团、苏北组团、泰州组团、杭州组团、南通组团.不同的模式对应着不同的生态经济系统演变方式,反映出长三角快速城市化地区内部存在着较大程度的生态经济关系空间分化趋势. 相似文献
12.
1996—2015年纽约湾区生态系统服务对景观格局变化的响应 总被引：1，自引：0，他引：1
生态系统服务价值对景观格局演变的响应研究已成为地理学、生态学等领域的研究热点。以纽约湾区为研究区,利用1996—2015年土地覆被数据和数字高程数据,采用生态系统服务价值当量估算法、景观格局指数、空间自相关分析等方法,分析1996—2015年湾区景观格局的时空演变规律,定量评估研究区生态系统服务价值,探讨纽约湾区生态系统服务价值对景观格局变化的响应。结果表明：①纽约湾区景观以林地和建设用地为主,其整体变化幅度较小,20年间湿地面积减少约10.94%,而建设用地增长幅度较高,约25.91%。②纽约湾区1996—2015年间ESV总量呈逐步减少,20年间共减少57.83亿元,2000—2005年间下降幅度较大约1.69%。③湾区ESV空间异质性较强,不同地区ESV增减所对应的土地利用转移各有差异。湾区南部热点区多出现湿地增加,而北部则以水域、草地增加为主。湾区西部冷点区多为湿地转林地的现象,而中部冷点区则以建设用地增加为主。④除建设用地外,湾区其余地类均呈现人为干预越少,景观结合度、聚集度越高,越有利于提升湾区整体的生态系统服务价值的规律。⑤纽约湾区ESV强度与土地利用程度（La）的空间关联性较弱,且湾区生态环境质量逐年下降。研究结果希望对世界级大湾区环境资源利用率的提升研究具有借鉴意义。 相似文献
13.
黄河三角洲“三生”用地转型的生态环境效应及其空间分异机制 总被引：2，自引：0，他引：2
“三生”用地转型的生态环境效应及其空间分异特征是指导区域国土空间开发与生态环境保护的重要依据。基于1998年、2008年和2018年3期土地利用遥感解译数据,构建黄河三角洲“三生”用地分类体系,通过土地利用转型图谱、生态环境质量指数、重心转移和地理探测器等方法定量分析研究区“三生”用地转型特征、生态环境效应及其空间分异性的主要影响因子。结果表明：① 1998—2018年黄河三角洲“三生”用地转型表现为生产用地占比大幅增加（+13.50%）,生态用地占比大幅减少（?17.19%）,生活用地占比小幅增长（+3.69%）。1998—2008年,“三生”用地转型以生态用地向生产用地转型为主。2008—2018年,无绝对优势转型类型,转型过程复杂化。② 1998—2018年,黄河三角洲生态环境质量整体向好,指数由0.390升至0.395,较高质量区与高质量区占主体地位。研究区中部及黄河入海口区域生态环境质量不断提升,东南及东北沿海地区生态环境质量有所降低。③ 植被覆盖度、微地貌类型、土壤类型是研究区生态环境质量空间分异的主导因子。区位因子与社会经济因子对生态环境质量空间分异的贡献率随生态环境质量的提升而降低,生态保护因子对生态环境质量空间分异的贡献率呈上升趋势。 相似文献
14.
基于县域单元的中国生态经济系统协调度及空间演化 总被引：4，自引：0，他引：4
以中国2853 个县(市、旗、区)为研究单元,利用1980、1990、2000 和2012 年的中国县级行政单元GDP数据和全国1 km格网土地利用数据,通过计算生态系统服务价值(ESV)和GDP的变化率,构建生态经济系统协调度(EEH)模型,分析了EEH的空间演化特征,在此基础上借助空间统计Local Moran's I 和Getis-Ord Gi* 指数评价EEH空间分布模式.结果表明:①自1980 年以来中国县级行政单元GDP持续快速增长,全国呈现东南沿海增长速度明显高于中部地区,而中部地区又明显高于西部地区的特征;②生态系统服务价值(ESV)在空间分布上表现为西部和北部地区较高,南部和中东部地区较低;③中国县域EEH 1980-2012 年间逐步得到改善,EEH空间关联度总体相对稳定,但空间格局分布不均衡.总体来看,确保生态经济系统的持续协调发展的任务依然十分艰巨. 相似文献
15.
黄河三角洲新生湿地土地利用变化图谱 总被引：26，自引：0，他引：26
在陈述彭先生提出的地学信息图谱理论和方法基础上,构建了土地利用图谱模型,在黄河三角洲新生湿地四期土地利用数据提取的基础上,合成了土地利用系列图谱,分别是1956～1984年,1984～1991年,1991～1996年三个时序。本文从黄河三角洲新生湿地土地利用强度变化、土地利用结构变化和土地利用格局变化三个方面进行了土地利用变化图谱分析,为地学信息图谱在土地利用变化研究中的应用提供了典型案例和实证。 相似文献
16.
土地利用生态服务价值与经济发展的协调及空间分异——以西洞庭湖区为例 总被引：3，自引：1，他引：2
土地利用生态服务价值体现了土地通过集约利用与空间优化所发挥生态效益的大小,可在一定程度上反映土地利用与与经济发展的协调关系。以西洞庭湖区为研究对象,在ArcGIS软件支持下,通过评价与分析生态服务价值变化,分析生态经济协调发展水平及其空间差异,探讨土地利用生态服务价值与区域经济发展的互动响应与耦合协调关系。研究表明：① 2000年以来西洞庭湖区土地利用生态服务价值呈下降趋势,2000年西洞庭湖区生态服务价值为1292.13×106元·a-1,2011年为953.03×106元·a-1,损失339.10×106元。② 从整个研究区来看,整个研究阶段处于低度冲突的县有6个,分别为常德市辖区、安乡县、汉寿县、澧县、临澧县、津市市,只有桃源县处于潜在危机状态。从数量上看,整个区域内大多为冲突状态,区域在经济发展中存在的潜在危机较大。③ 从空间分异来看,2008年与2011年土地利用生态经济协调度基本上为低度冲突状态,需采取生态服务供给恢复与重建措施,控制生态服务消费需求的过快增长。整个区域只有桃源县与汉寿县由不协调转换为协调状态,主要原因是森林覆盖率相对较高,林地类型面积大,水土保持与水源涵养生态服务功能较强,提高了生态服务价值。 相似文献
17.
基于广州市2004―2016年土地利用分类成果,通过CA-Markov模型模拟预测2020年土地利用状况,结合格网分析法构建广州市2004―2020年的生态系统服务价值（Ecosystem Services Value,ESV）密度格网,并展开Getis-Ord热点区分析和圈层分析评估,分析广州市快速城市化进程土地利用变化对ESV变化过程和影响的空间异质性。结果表明：1）广州市快速城市化进程中,建设用地扩张占用了大量生态用地,建设用地面积从2004年的1 320 km2扩张到2016年约2 000 km2,预计2020年将达到2 263.63 km2,生态用地斑块日趋破碎化;2）2004―2016年间,广州市ESV总值累计减少了92.41亿元,年均减少约8.4亿元,预计2016―2020年其继续减少但减速会放缓;3）ESV高值区域的格网数量净减少近18%,低值区域的格网数量净增加约46%,局部区域生态系统服务功能的改善难以抵消快速城市化造成的ESV损失;4）广州市ESV变化呈现局部空间自相关现象,高冷区常年集聚分布在花都区和番禺―南沙一带,高热区从集聚分布于东北部逐渐变成为零星分布;5）ESV圈层格局从中心城区向外围区（核心区、近郊区、边缘区和外围区）呈“低―低―中―高”向“低―低―低―高”的结构特征演变,地处城市边缘的近郊区域和边缘区域逐渐形成空间异质性最突出的城乡交错带。 相似文献
18.
关注生态系统服务价值（Ecosystem service value,ESV）与城市化耦合协调互动关系,对黄河流域高质量发展大有裨益。文章运用熵权法、耦合协调模型、空间自相关模型,障碍度模型分析了城市化与ESV的耦合协调关系及主导障碍因素。结果表明:（1） 1995—2018年,黄河流域ESV发生了很大的改善,整体增加了33.05×109元,且以调节服务为主导,草地、林地、耕地服务价值对总ESV贡献率较高。单位面积生态系统服务价值（PE）呈现南高北低、中游高上下游低的空间格局。（2） PE与城市化耦合协调度（Coupling coordination degree,CCD）逐渐改善,轻度耦合协调增加了27.12%,严重失调类型减少了45.46%,耦合亚型从城市化滞后型转变为ESV滞后型;从空间上看,CCD呈现南高北低、中游优于上游和下游的空间格局,协调度具有显著的空间正相关性,存在明显的高-高和低-低集聚特征,高-高集聚区主要分布在ESV高且城市化水平相对较高的中游和下游地区,低-低集聚区主要分布在ESV较低的上游地区。（3） 1995—2018年主导障碍因素未发生明显改变,ESV系统以调节服务为主,而城市化系统以经济子系统和社会子系统为主。基于此,应厘清ESV和城市化耦合协调关系,关注城市化进程对区域生态系统服务能力和生态安全格局的影响,实现流域整体优质协调发展。 相似文献
19.
通过构建评价指标体系和分析框架,利用综合指数法、耦合协调度模型和灰色关联度模型分析2005―2017年长江三角洲（长三角）碳排放与植被固碳耦合协调时空变化特征及驱动因素,并模拟政府决策优先级对耦合协调度趋势的影响。结果表明：长三角碳排放空间集聚特征显著,基本形成了以长江沿线和长三角东南沿海区域为核心的沿江沿海高排放带;长三角碳排放与植被固碳耦合协调度具有明显的空间分异特征,呈现出南京-上海沿线一般失调区域为核心的圈层结构特征;植被覆盖综合评价值高于碳排放综合评价值的地区耦合协调度普遍较高,人口的集聚和变化、城市建设和能源消耗对耦合协调度影响最大;同时,政府决策的优先级会显著影响耦合协调趋势。 相似文献
20.
人口城镇化的快速推进与生态城镇化的建设滞后是中国快速城镇化进程中面临的重要问题。以长三角地区城市人口与绿地面积为研究对象,构建城市人口-绿地面积异速增长模型分析2000—2018年两者关系的时空变化规律,并运用地理探测器模型揭示异速增长的驱动机制。结果表明：① 长三角地区城市人口呈加速增长态势,绿地建设增长缓慢,城市人口-绿地面积异速关系逐渐由人地基本协调型转变为人口扩张弱型,2000—2008年多数城市表现出绿地扩张的特征,2009—2018年则转变为人口扩张的特征。② 教育投入度、人口集中度、设施供给度、土地开发度和对外开放度是影响长三角地区城市人口-绿地面积异速增长的主要因子,双因子交互解释力均高于单因子,各因子间的影响具有协同增强的特征。③ 长三角地区城市人口-绿地面积异速增长是行政力、市场力和外资力共同驱动的结果,三种驱动力彼此联系、协同作用,主导驱动力逐渐由行政力转变为市场力。 相似文献