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1.
北京城市湿地时空演变及驱动力定量分析(英文) 总被引：4，自引：1，他引：3
The decision tree and the threshold methods have been adopted to delineate boundaries and features of water bodies from LANDSAT images. After a spatial overlay analysis and using a remote sensing technique and the wetland inventory data in Beijing, the water bodies were visually classified into different types of urban wetlands, and data on the urban wetlands of Beijing in 1986, 1991, 1996, 2000, 2002, 2004 and 2007 were obtained. Thirteen driving factors that affect wetland change were selected, and gray correlation analysis was employed to calculate the correlation between each driving factor and the total area of urban wetlands. Then, six major driving factors were selected based on the correlation coefficient, and the contribution rates of these six driving factors to the area change of various urban wetlands were calculated based on canonical correlation analysis. After that, this research analyzed the relationship and mechanism between the main driving factors and various types of wetlands. Five conclusions can be drawn. (1) The total area of surface water bodies in Beijing increased from 1986 to 1996, and gradually decreased from 1996 to 2007. (2) The areas of the river wetlands, water storage areas and pool and culture areas gradually decreased, and its variation tendency is consistent with that of the total area of wetlands. The area of the mining water areas and wastewater treatment plants slightly increased. (3) The six factors of driving forces are the annual rainfall, the evaporation, the quantity of inflow water, the volume of groundwater available, the urbanization rate and the daily average discharge of wastewater are the main factors affecting changes in the wetland areas, and they correlate well with the total area of wetlands. (4) The hydrologic indicators of water resources such as the quantity of inflow water and the volume of groundwater are the most important and direct driving forces that affect the change of the wetland area. These factors have a combined contribution rate of 43.94%. (5) Climate factors such as rainfall and evaporation are external factors that affect the changes in wetland area, and they have a contribution rate of 36.54%. (6) Human activities such as the urbanization rate and the daily average quantity of waste-water are major artificial driving factors. They have an influence rate of 19.52%. 相似文献
2.
1984-2008年北京湿地景观格局驱动机制(英文) 总被引：3，自引：0，他引：3
The landscape pattern of Beijing wetlands has undergone a significant change as a result of natural and artificial elements.Supported by remote sensing and GIS technology,using multi-temporal TM images from 1984 to 2008 in Beijing,this paper analyzed the dynamic characteristics of wetlands landscape pattern through selected typical indices including patch area,patch average area,fractal dimension index,diversity,dominance,contagion indices and the spatial centroids of each wetlands type were calculated.Finally,the paper explored the evolution mode and driving factors of wetland landscape pattern.The results were obtained as follows:the total wetland area increased during the period 1984-1996,then decline from 1996 to 2004.The wetland area in 1994 accounted for only 47.37% of that in 2004.The proportion of artificial wetland area was larger than that of natural wetland.The proportion of reservoir wetland was 33.50% to 53.73% and had the maximum average area.pond and paddy field wetland type with the least average area accounted for 16.46% to 45.09% of the total wetland area.The driving forces of the natural river wetland were mainly natural elements;its fractal dimension index was greater than the others.The Shannon diversity index of wetland landscape increased from 1.11 in 1992 to 1.34 in 2004,indicating that the difference between proportions of each wetland type decreased and areas of each wetland type were evenly distributed.The contagion index went down from 65.59 to 58.41,indicating that the connectivity degraded.Miyun Reservoir had the largest area and its area change had a great impact on the location of the centroid.Wetland resources degenerated gradually from the joint effects of natural and artificial factors.During the period 2006-2008,the precipitation increased and the drought condition was relieved.The government implemented series of positive policies to save water resources,and the wetland area increased. 相似文献
3.
中国边境地区城镇化时空格局及其驱动力 总被引：2，自引：1，他引：2
Border area is not only an important gateway for inland opening-up,but also an important part of completing the building of a moderately prosperous society and optimizing national urban spatial pattern in China.Due to the location,natural resources endowment,and traffic accessibility,the urbanization speed is relatively slow in border areas.Therefore,it is a special area that needs to pay close attention to,especially under the background of the Belt and Road Initiative and China's regional coordinated development program.Based on the county-level data from 2000 to 2015,this paper tries to analyze the spatio-temporal pattern of urbanization in 134 border counties,and applies geographical detector method to study the driving forces of urbanization in border areas.Conclusions are as follows:(1)From 2000 to 2015,urbanization rate in border areas has been lower than the national average,and the gap has been widening.Some border counties in southern Xinjiang,Tibet,northeast of Inner Mongolia,and Yunnan,are even facing the problem of population loss.(2)In the same period,urbanization rate in the northwestern and southwestern border is low,while their urbanization rate grows relatively faster comparing with other border counties;urbanization rate in Tibet border is the lowest and grows relatively slowly;urbanization rate in the northeastern and northern border is slightly higher,but it grows slowly or even stagnates.(3)Transportation and industry are the important driving forces of urbanization in border areas,while the driving forces of market is relatively weak.And there are obvious mutual reinforcements among the driving forces,while the effort and explanatory power of resource force increases obviously after interaction.(4)Urbanization rate in the northwestern and southwestern border areas grows relatively fast,with industrial force and transportation force,market force and administrative force as the main driving forces respectively.Tibet border area has the lowest urbanization rate and growth rate,as the driving force of urbanization with strong contribution has not yet formed in Tibet.In the northeastern and northern border areas,the contribution of transportation force to urbanization is greater than other forces,and its interaction with market and industry has obvious effects. 相似文献
4.
The shapes of the urban lakes in Wuhan city have been strongly influenced by the rapid industrialization and urbanization experienced in recent decades.Based on topographic maps and remote sensing images,the temporal and spatial changes of East Lake,Wuhan city,over the past two decades were analyzed.The landscape shape index(LSI)and centroid method were applied to analyze the evolution of lake morphology and its causes.Several key results were obtained.(1)The surface area of East Lake decreased sharply by 2.13 km2 from 1995 to 2005,and slightly by 1.00 km2 from 2005 to 2015.The shoreline length of East Lake displayed a continuous trend of decline during the study period:The length reduced by 21.89 km from 1995 to 2005,and by 0.67 km from 2005 to 2015.The LSI values,7.04(1995),6.46(2005),and 6.28(2015),displayed an accelerated downward trend,indicating a reduction of complexity in East Lake and the intensification of manual interventions in the water body.(2)The changes to East Lake displayed a clear temporal and spatial heterogeneity.The centroid of East Lake moved northeast from 1995 to 2005 and southeast from 2005 to 2015.(3)The reduction in the area of East Lake was mainly affected by human activities.A lake area of about 4.8 km2 was converted to other land uses during 1995-2005,most of which was unused land,whereas from 2005 to 2015,0.43 km2 of the lake area was converted into built-up land,and 0.25 km2 was converted into other land uses.The reduction in area was caused by infrastructure construction by the government,the development of the real estate industry,illegal construction by villagers,and the development of scenic spots for tourism.The driving forces of this reduction included Wuhan's growing population,and the rapid development of the economy and urbanization between 1995 and 2015,which has resulted in a large demand for land.Finally,a formation mechanism model was constructed by analyzing the causes of East Lake's morphological evolution. 相似文献
5.
Effect of human settlements on urban thermal environment and factor analysis based on multi-source data: A case study of Changsha city 总被引：1，自引：1，他引：0
In view of the lack of comprehensive evaluation and analysis from the combination of natural and human multi-dimensional factors, the urban surface temperature patterns of Changsha in 2000, 2009 and 2016 are retrieved based on multi-source spatial data(Landsat 5 and Landsat 8 satellite image data, POI spatial big data, digital elevation model, etc.), and 12 natural and human factors closely related to urban thermal environment are quickly obtained. The standard deviation ellipse and spatial principal component analysis(PCA) methods are used to analyze the effect of urban human residential thermal environment and its influencing factors. The results showed that the heat island area increased by 547 km~2 and the maximum surface temperature difference reached 10.1℃ during the period 2000–2016. The spatial distribution of urban heat island was mainly concentrated in urban built-up areas, such as industrial and commercial agglomerations and densely populated urban centers. The spatial distribution pattern of heat island is gradually decreasing from the urban center to the suburbs. There were multiple high-temperature centers, such as Wuyi square business circle, Xingsha economic and technological development zone in Changsha County, Wangcheng industrial zone, Yuelu industrial agglomeration, and Tianxin industrial zone. From 2000 to 2016, the main axis of spatial development of heat island remained in the northeast-southwest direction. The center of gravity of heat island shifted 2.7 km to the southwest with the deflection angle of 54.9° in 2000–2009. The center of gravity of heat island shifted to the northeast by 4.8 km with the deflection angle of 60.9° in 2009–2016. On the whole, the change of spatial pattern of thermal environment in Changsha was related to the change of urban construction intensity. Through the PCA method, it was concluded that landscape pattern, urban construction intensity and topographic landforms were the main factors affecting the spatial pattern of urban thermal environment of Changsha. The promotion effect of human factors on the formation of heat island effect was obviously greater than that of natural factors.The temperature would rise by 0.293℃ under the synthetic effect of human and natural factors. Due to the complexity of factors influencing the urban thermal environment of human settlements, the utilization of multi-source data could help to reveal the spatial pattern and evolution law of urban thermal environment, deepen the understanding of the causes of urban heat island effect, and clarify the correlation between human and natural factors, so as to provide scientific supports for the improvement of the quality of urban human settlements. 相似文献
6.
Revealing ecosystem services relationships and their driving factors for five basins of Beijing 总被引：1，自引：1，他引：0
A clear understanding of the relationships among multiple ecosystem services(ESs) is the foundation for sustainable urban ecosystem management. Quantitatively identifying the factors that influence ES trade-offs and synergies can contribute to deepening ES research, from knowledge building to decision making. This study simulated soil conservation, water yield and carbon sequestration in Beijing, China, from 2015–2018. The spatial trade-offs and synergies of these three ESs within the five major river basins in Beijing were explored using geographically weighted regression. Furthermore, geographical detector was applied to quantitatively identify the driving mechanism of the environmental factors for the ES trade-offs and synergies. The results show the following:(1) the spatial relationships between soil conservation and water yield, as well as between water yield and carbon sequestration, were mainly trade-offs. There was a spatial synergy between soil conservation and carbon sequestration.(2) Regarding the spatial trade-off/synergy between soil conservation and water yield in Beijing, the dominant influencing factor was temperature/elevation, and the dominant interactions of the spatial trade-off and synergy between these two ESs in Beijing and the Chaobai River Basin are all manifested in the superposition of precipitation and potential evapotranspiration, temperature, and elevation.(3) Topographic factors were the dominant factors influencing the spatial relationship between soil conservation and carbon sequestration in Beijing and its five major river basins. As a result of the distribution of water systems and hydrological characteristics of the basins, differences were observed in the effects of different combinations of interaction factors on the spatial relationship between these two ESs in different basins.(4) Temperature had the strongest explanatory power in terms of the spatial trade-offs and synergies between water yield and carbon sequestration. The interactions between precipitation and temperature and between precipitation and elevation were the dominant interactions affecting the spatial relationship between water yield and carbon sequestration in Beijing. Overall, the explanatory power of influencing factors on the trade-offs and synergies and the degree of interaction between factors coexist in different basins with consistency and differences. Therefore, understanding the quantitative characteristics of basin-scale spatial trade-offs and synergies between ESs is important for ecosystem management and the promotion of synergy in different basins. 相似文献
7.
The area of desertified land has increased by 27.3% from 1987 to 2000 in Maduo County,northeastern Qinghai-Tibet Plateau.Driving forces of land degradation has been extensively studied in the region.Using Factor Analysis (FA),we evaluate contribution of human activity and natural environmental change to land degradation.Four common factors were extracted in this study.The result shows that climate related other than human-related factors,are the major inducing factors of land degradation in Maduo County.Climate change and consequent change of permafrost account for 70% to the land degradation.Increasing evaporation and declining precipitation in the beginning of the growing season hamper seedling establishment.Decreasing frozen days and rising active layer lower bound make surface soil loose and less soil moisture available for plant. 相似文献
8.
《地理学报(英文版)》2016,(3)
Different government departments and researchers have paid considerable attention at various levels to improving the eco-environment in ecologically fragile areas. Over the past decade, large numbers of people have emigrated from rural areas as a result of the rapid urbanization in Chinese society. The question then remains: to what extent does this migration affect the regional vegetation greenness in the areas that people have moved from Based on normalized difference vegetation index(NDVI) data with a resolution of 1 km, as well as meteorological data and socio-economic data from 2000 to 2010 in Inner Mongolia, the spatio-temporal variation of vegetation greenness in the study area was analyzed via trend analysis and significance test methods. The contributions of human activities and natural factors to the variation of vegetation conditions during this period were also quantitatively tested and verified, using a multi-regression analysis method. We found that:(1) the vegetation greenness of the study area increased by 10.1% during 2000–2010. More than 28% of the vegetation greenness increased significantly, and only about 2% decreased evidently during the study period.(2) The area with significant degradation showed a banded distribution at the northern edge of the agro-pastoral ecotone in central Inner Mongolia. This indicates that the eco-environment is still fragile in this area, which should be paid close attention. The area where vegetation greenness significantly improved showed a concentrated distribution in the southeast and west of Inner Mongolia.(3) The effect of agricultural labor on vegetation greenness exceeded those due to natural factors(i.e. precipitation and temperature). The emigration of agricultural labor improved the regional vegetation greenness significantly. 相似文献
9.
Quantitative analysis of the impact factors in energy-related CO_2 emissions serves as an important guide for reducing carbon emissions and building an environmentally-friendly society. This paper aims to use LMDI method and a modified STIRPAT model to research the conventional energy-related CO_2 emissions in Kazakhstan after the collapse of the Soviet Union. The results show that the trajectory of CO_2 emissions displayed U-shaped curve from 1992 to 2013. Based on the extended Kaya identity and additive LMDI method, we decomposed total CO_2 emissions into four influencing factors. Of those, the economic active effect is the most influential factor driving CO_2 emissions, which produced 110.86 Mt CO_2 emissions, with a contribution rate of 43.92%. The second driving factor is the population effect, which led to 11.87 Mt CO_2 emissions with a contribution rate of 4.7%. On the contrary, the energy intensity effect is the most inhibiting factor, which caused –110.90 Mt CO_2 emissions with a contribution rate of –43.94%, followed by the energy carbon structure effect resulting in –18.76 Mt CO_2 emissions with a contribution rate of –7.43%. In order to provide an in-depth examination of the change response between energy-related CO_2 emissions and each impact factor, we construct a modified STIRPAT model based on ridge regression estimation. The results indicate that for every 1% increase in population size, economic activity, energy intensity and energy carbon structure, there is a subsequent increase in CO_2 emissions of 3.13%, 0.41%, 0.30% and 0.63%, respectively. 相似文献
10.
Dual factors of climate and human on the hydrological process are reflected not only in changes in the spatiotemporal distribution of water resource amounts but also in the various characteristics of river flow regimes. Isolating and quantifying their contributions to these hydrological alterations helps us to comprehensively understand the response mechanism and patterns of hydrological process to the two kinds of factors. Here we develop a general framework using hydrological model and 33 indicators to describe hydrological process and quantify the impact from climate and human. And we select the Upper Minjiang River(UMR) as a case to explore its feasibility. The results indicate that our approach successfully recognizes the characteristics of river flow regimes in different scenarios and quantitatively separates the climate and human contributions to multi-dimensional hydrological alterations. Among these indicators, 26 of 33 indicators decrease over the past half-century(1961–2012) in the UMR, with change rates ranging from 1.3% to 33.2%, and the human impacts are the dominant factor affecting hydrological processes, with an average relative contribution rate of 58.6%. Climate change causes an increase in most indicators, with an average relative contribution rate of 41.4%. Specifically, changes in precipitation and reservoir operation may play a considerable role in inducing these alterations. The findings in this study help us better understand the response mechanism of hydrological process under changing environment and is conducive to climate change adaptation, water resource planning and ecological construction. 相似文献
11.
As one of the most critical impact factors of global change, historical land-use change is an indispensable input in climate and environment simulations. To better understand the cropland change in the Guanzhong area, gazetteers, statistics, and survey data were collected as data sources. Methods of registered tax-paying cropland data collection, selection of time points, and data interpolation and calibration were used to reconstruct changes in the cropland area. The cropland area data at the county level were allocated to 1 km×1 km grid cells. The total cropland area in the Guanzhong area was influenced by changes in population, wars, natural disasters, and land-use types, and it fluctuated from 1650 to 2016. From 1780 to 1830, the cropland expanded in the northern and western parts of Guanzhong area, and the cropland in the north of Qinling Mountains increased slightly. The spatial pattern of cropland reached its maximum range in 1980, and the cropland area declined in the whole study area, especially in the cities of Xi'an and Xianyang in 2016. The comparison between HYDE 3.2 and the data obtained in this study showed that the grid cells of HYDE 3.2 exhibit lower values of cropland area fractions in the Guanzhong Basin and higher values in high-altitude areas around the Guanzhong Basin as compared to those in this study. 相似文献
12.
Natural runoff changes in the Yellow River Basin 总被引：3，自引：1，他引：3
1IntroductionThe driving factors of runoff changes can be divided into precipitation factor and non-precipitation factor, and they can also be divided into natural factor and human activity factor. The influence of the natural factor includes precipitation reduction, precipitation features (for example, spatio-temporal distribution and intensity), landuse natural changes and so forth. All of these can cause runoff changes. Temperature, evaporation, topography, soil and geological environment i… 相似文献
13.
The Zoige Wetland is located in the northeastern Qinghai-Tibetan Plateau, which is highly sensitive to global environment change and human disturbance because of its high elevation and cold environment, thus, it’s a hotspot for land use and land cover change (LUCC) research. We used Landsat MSS images from 1975, Landsat ETM images from 2000, and Landsat TM images from 1990 and 2005 to assess the LUCC in the study area, using GIS techniques, as well as topographic, vegetation, and soil maps combined with field investigations. The monitoring result shows that the study area’s environment degraded rapidly between 1975 and 2005, including wetland shrinkage from 5,308 km2 to 4,980 km2, sandy land expansion from 112 km2 to 137 km2, forest land decreasing from 5,686 km2 to 5,443 km2, and grassland degradation from 12,309 km2 to 10,672 km2. According to the analysis of meteorological data and social-economic statistical data, we concluded that the LUCC in the Zoige Wetland was caused by both natural and anthropogenic factors, but human activities were primarily responsible for the observed LUCC, thereby, we suggest human behaviors must be adjusted to control environmental degradation. 相似文献
14.
厦门岛城市空间扩张特征及其影响因素 总被引：1，自引：0，他引：1
Most of the world’s cities are concentrated in coastal areas. As a special geographical component of the coastal system, island urban spatial expansion is the outcome of interactions between city development and the physical environment. This paper takes Xiamen Island, located in Southeastern China, as an example to analyze island urban spatial expansion and its determinants by combining an analysis of the literature on urban development policies, urban overall plans, population growth and industrial development, with geographical information analysis using historical maps and remote sensing photographs. Firstly, we reviewed the history of the Xiamen City development during the last 100 years, which can be divided into four periods: the embryonic modern city and early development from 1908 to 1949; administrative boundary expansion and infrastructure development from 1950 to 1979; special economic zone construction and rapid urbanization from 1980 to 2003; and Bay City construction since 2003. The dynamic changes to the coastline, island shape, built-up area, transportation, administrative division, and major land use type conversion which occurred during approximately the past 100 years were analyzed and the characteristics of the island urban spatial expansion were concluded: early expansion from a central point, followed by expansion along a section of coastline, and expansion from the coastline inland. Secondly, we discussed the potential determinants of island urban spatial expansion including administrative division adjustment, urban master planning revision, industrial development, topographical factors, coastal area reclamation, transportation expansion, and population growth. Finally, the effects of each potential determinant on island urban spatial expansion were concluded. Island urban spatial expansion is the result of a synthesis of natural and socio-economic factors which are not independent but interacting. Built-up area expansion is the major driver of island land cover and land use changes. By this paper, we hope to provide a scientific reference contributing to the rational understanding of island and coastal sustainable urbanization in China, and the world beyond. 相似文献
15.
The Yangtze River Watershed in China is a climate change hotspot featuring strong spatial and temporal variability;hence, it poses a certain threat to social development. Identifying the characteristics of and regions vulnerable to climate change is significantly important for formulating adaptive countermeasures. However, with regard to the Yangtze River Watershed, there is currently a lack of research on these aspects from the perspective of natural and anthropogenic factors. To address this issue, in this study, based on the temperature and precipitation records from 717 meteorological stations, the RClim Dex and random forest models were used to assess the spatiotemporal characteristics of climate change and identify mainly the natural and anthropogenic factors influencing climate change hotspots in the Yangtze River Watershed for the period 1958-2017. The results indicated a significant increasing trend in temperature, a trend of wet and dry polarization in the annual precipitation, and that the number of temperature indices with significant variations was 2.8 times greater than that of precipitation indices. Significant differences were also noted in the responses of the climate change characteristics of the sub-basins to anthropogenic and natural factors;the delta plain of the Yangtze River estuary exhibited the most significant climate changes, where 88.89% of the extreme climate indices varied considerably. Furthermore, the characteristics that were similar among the identified hotpots, including human activities(higher Gross Domestic Product and construction land proportions) and natural factors(high altitudes and large proportions of grassland and water bodies), were positively correlated with the rapid climate warming. 相似文献
16.
Saline-alkali soil is a kind of degraded soil, in which the content of dissolvable elements is supernormal. The soil structure, physical and chemical qualities have degenerated due to impact of both natural and human factors. Soil salinization in temperate semi-humid area includes grassland salinization, cropland salinization and partially, wetland salinization. In the 40 years, from the late 1950s to late 1990s, the saline-alkali soil in temperate semi-humid area expanded, and aggravated to c… 相似文献
17.
Environmental stress is used as an indicator of the overall pressure on regional environmental systems caused by the output of various pollutants as a result of human activities. Based on the pollutant emissions and socioeconomic databases of the counties in Beijing–Tianjin–Hebei region, this paper comprehensively calculates the environmental stress index(ESI) for the urban agglomeration using the entropy weight method(EWM) at the county scale and analyzes the spatiotemporal patterns and the differences among the four types of major functional zones(MFZ) for the period 2012–2016. In addition, the socioeconomic driving forces of environmental stress are quantitatively estimated using the geographically weighted regression(GWR) method based on the STIRPAT model framework. The results show that:(1) The level of environmental stress in the Beijing–Tianjin–Hebei region was significantly alleviated during that time period, with a decrease in ESI of 54.68% by 2016. This decrease was most significant in Beijing, Tangshan, Tianjin, Shijiazhuang, and other central urban areas, as well as the Binhai New Area. The level of environmental stress in counties decreased gradually from the central urban areas to the suburban areas, and the high-level stress counties were eliminated by 2016.(2) The spatial spillover effect of environmental stress increased further at the county scale from 2012 to 2016, and spatial locking and path dependence emerged in the cities of Tangshan and Tianjin.(3) Urbanized zones(development-optimized and development-prioritized zones) were the major areas bearing environmental pollution in the Beijing–Tianjin–Hebei region in that time period. The ESI accounted for 65.98% of the whole region, where there was a need to focus on the prevention and control of environmental pollution.(4) The driving factors of environmental stress at the county scale included population size and the level of economic development. In addition, the technical capacity of environmental waste disposal, the intensity of agricultural production input, the intensity of territorial development, and the level of urbanization also had a certain degree of influence.(5) There was spatial heterogeneity in the effects of the various driving factors on the level of environmental stress. Thus, it was necessary to adopt differentiated environmental governance and reduction countermeasures in respect of emission sources, according to the intensity and spatiotemporal differences in the driving forces in order to improve the accuracy and adaptability of environmental collaborative control in the Beijing–Tianjin–Hebei region. 相似文献
18.
《地理学报(英文版)》2010,(5)
Glaciers are one of the most important land covers in alpine regions and especially sensitive to global climate change.Remote sensing has proved to be the best method of investigating the extent of glacial variations in remote mountainous areas.Using Landsat thematic mapping(TM) and multi-spectral-scanner(MSS) images from Mt.Qomolangma(Everest) National Nature Preserve(QNNP),central high Himalayas for 1976,1988 and 2006,we derived glacial extent for these three periods.A combination of object-oriented image interpretation methods,expert knowledge rules and field surveys were employed.Results showed that(1) the glacial area in 2006 was 2710.17 ± 0.011 km2(about 7.41% of the whole study area),and located mainly to the south and between 4700 m to 6800 m above sea level;(2) from 1976 to 2006,glaciers reduced by 501.91 ± 0.035 km2 and glacial lakes expanded by 36.88 ± 0.035 km2;the rate of glacier retreat was higher in sub-basins on the southern slopes(16.79%) of the Himalayas than on the northern slopes(14.40%);most glaciers retreated,and mainly occurred at an elevation of 4700-6400 m,and the estimated upper limit of the retreat zone is between 6600 m and 6700 m;(3) increase in temperature and decrease in precipitation over the study period are the key factors driving retreat. 相似文献
19.
The environment evolution of Wuliangsuhai wetland since 1986 is analyzed based on the remote sensing principle. The total water area of Wuliangsuhai lake has been increased during the past 17 years. The open water area had an increasing trend before 1987, and the trend was decreasing up to 1996, then the trend has increased again since 2000; the variation of the water area with dense aquatic weed is basically contradictory to the variation of open water area. The natural reed area had been decreased before 1987, and then it has been increased. The areas of shallow water and swamp have been slightly increased, in fact, the variations are quite steady. The artificial reed area has been increased since the reed plantation was started in 1988. The relationships of the water environment, the climate, hydrology and different types of areas are discussed, and then the technological measures for sustainable development and utilization of Wuliangsuhai lake water environment are proposed. 相似文献
20.
Carbon dioxide(CO_2) is a major climate forcing factor, closely related to human activities. Quantifying the contribution of CO_2 emissions to the global radiative forcing(RF) is therefore important to evaluate climate effects caused by anthropogenic and natural factors. China, the United States(USA), Russia and Canada are the largest countries by land area, at different levels of socio-economic development. In this study, we used data from the CarbonTracker CO_2 assimilation model(CT2017 data set) to analyze anthropogenic CO_2 emissions and terrestrial ecosystem carbon sinks from 2000 to 2016. We derived net RF contributions and showed that anthropogenic CO_2 emissions had increased significantly from 2000 to 2016, at a rate of 0.125 PgC yr~(-1). Over the same period, carbon uptake by terrestrial ecosystems increased at a rate of 0.003 PgC yr~(-1). Anthropogenic CO_2 emissions in China and USA accounted for 87.19% of the total, while Russian terrestrial ecosystems were the largest carbon sink and absorbed 14.69 PgC. The resulting cooling effect was-0.013 W m~(-2) in 2016, representing an offset of-45.06% on climate warming induced by anthropogenic CO_2. This indicates that net climate warming would be significantly overestimated if terrestrial ecosystems were not included in RF budget analyses. In terms of cumulative effects, we analyzed RFs using reference atmospheres of 1750, at the start of the Industrial Revolution, and 2000, the initial year of this study. Anthropogenic CO_2 emissions in the study area contributed by + 0.42 W m~(-2) and +0.32 W m~(-2) to the global RF, relative to CO_2 levels of 1750 and 2000, respectively. We also evaluated correlations between global mean atmospheric temperature and net, anthropogenic and natural RFs. We found that the combined(net) RF caused by CO_2 emissions accounted for 30.3% of global mean temperature variations in 2000–2016. 相似文献