Serial remote sensing images offer a valuable means of tracking the evolutionary changes and growth of a specific geographical area over time.Although the original images may provide limited insights,they harbor consi...Serial remote sensing images offer a valuable means of tracking the evolutionary changes and growth of a specific geographical area over time.Although the original images may provide limited insights,they harbor considerable potential for identifying clusters and patterns.The aggregation of these serial remote sensing images(SRSI)becomes increasingly viable as distinct patterns emerge in diverse scenarios,such as suburbanization,the expansion of native flora,and agricultural activities.In a novel approach,we propose an innovative method for extracting sequential patterns by combining Ant Colony Optimization(ACD)and Empirical Mode Decomposition(EMD).This integration of the newly developed EMD and ACO techniques proves remarkably effective in identifying the most significant characteristic features within serial remote sensing images,guided by specific criteria.Our findings highlight a substantial improvement in the efficiency of sequential pattern mining through the application of this unique hybrid method,seamlessly integrating EMD and ACO for feature selection.This study exposes the potential of our innovative methodology,particularly in the realms of urbanization,native vegetation expansion,and agricultural activities.展开更多
Population aging has become an inevitable trend and exerted profound influences on socio-economic development in China.In this study,we utilized data from national population census and statistical yearbooks in 2010 a...Population aging has become an inevitable trend and exerted profound influences on socio-economic development in China.In this study,we utilized data from national population census and statistical yearbooks in 2010 and 2020 to explore spatio-temporal patterns of aging population and its coupling correlations with socio-economic factors from both global and local perspectives.The results from Local Indicators of Spatial Association(LISA)uncover notable spatial disparities in aging population rates,with higher rates concentrated in the eastern regions and lower rates in the western areas of the Chinese mainland.The results from the global correlation analysis with the changes in aging population rates show significant positive correlations with government interventions and industrial structures,but negatively correlated with economic development,social consumption,and medical facilities.From a local perspective,a Geographically Weighted(GW)correlation analysis is employed to uncover local correlations between aging trends and socio-economic factors.The insights gained from this technique not only underscore the complexity and diversity of economic implications stemming from population aging,but also provide invaluable guidance for crafting region-specific economic policies tailored to various stages of population aging.展开更多
In recent decades, Urban Heat Island Effects have become more pronounced and more widely examined. Despite great technological advances, our current societies still experience great spatial disparity in urban forest a...In recent decades, Urban Heat Island Effects have become more pronounced and more widely examined. Despite great technological advances, our current societies still experience great spatial disparity in urban forest access. Urban Heat Island Effects are measurable phenomenon that are being experienced by the world’s most urbanized areas, including increased summer high temperatures and lower evapotranspiration from having impervious surfaces instead of vegetation and trees. Tree canopy cover is our natural mitigation tool that absorbs sunlight for photosynthesis, protects humans from incoming radiation, and releases cooling moisture into the air. Unfortunately, urban areas typically have low levels of vegetation. Vulnerable urban communities are lower-income areas of inner cities with less access to heat protection like air conditioners. This study uses mean evapotranspiration levels to assess the variability of urban heat island effects across the state of Tennessee. Results show that increased developed land surface cover in Tennessee creates measurable changes in atmospheric evapotranspiration. As a result, the mean evapotranspiration levels in areas with less tree vegetation are significantly lower than the surrounding forested areas. Central areas of urban cities in Tennessee had lower mean evapotranspiration recordings than surrounding areas with less development. This work demonstrates the need for increased tree canopy coverage.展开更多
Medicinal plant diversity(MPD)is an indispensable part of global plant diversity,serving as the foundation for human survival by offering remedies and preventive measures against diseases.However,factors such as overe...Medicinal plant diversity(MPD)is an indispensable part of global plant diversity,serving as the foundation for human survival by offering remedies and preventive measures against diseases.However,factors such as overexploitation,competition from invasive alien species,and climate change,threaten the habitats of medicinal plants,necessitating a comprehensive understanding of their spatial distribution and suitable habitats.We leveraged a decade of field survey data on medicinal plant distribution in the Yinshan Mountains,combined with spatial analysis,species distribution modeling,and the Carnegie Ames Stanford Approach(CASA)to explore the MPD spatial distribution and suitable habitats.Spatial analysis revealed that the central and eastern parts of Yinshan Mountains were the primary MPD hotspots,with no cold spots evident at various spatial scales.As the spatial scale decreased,previous non-significant regions transformed into hotspots,with instances where large-scale hotspots became insignificant.These findings offer valuable guidance for safeguarding and nurturing MPD across diverse spatial scales.In future climate change scenarios within the shared socioeconomic pathways(SSP),the habitat suitability for MPD in the Yinshan Mountains predominantly remains concentrated in the central and eastern regions.Notably,areas with high net primary productivity(NPP)values and abundant vegetation coverage align closely with MPD habitat suitability areas,potentially contributing to the region's rich MPD.展开更多
[Objective] This study investigated the spatial characteristics of counties （cities） with comparative advantages in watermelon and melon production to provide reference bases in formulating strategies for the develo...[Objective] This study investigated the spatial characteristics of counties （cities） with comparative advantages in watermelon and melon production to provide reference bases in formulating strategies for the development of watermelon and melon industries in Hainan Province. [Method] By using the sowing area, total yield, and yield per unit area of watermelon and melon in Hainan Province as research u- nits, the yield comparative advantage （YCA）, efficiency comparative advantage （E- CA）, scale comparative advantage （SCA）, concentration ratio comparative advantage （CRCA）, comprehensive comparative advantage （CCA）, ratio of yield per unit area （RYPA）, sowing area ratio （SAR）, and distribution characteristics of watermelon and melon were systematically analyzed. By referring to the agricultural statistic data of 18 counties （cities） in Hainan Province, indexes for each research unit （i.e., the YCA index, ECA index, SCA index, CRCA index, CCA index, RYPA index, and SAR index） were established and calculated to determine the comparative advantage of watermelon and melon production in Hainan Province. A spatial expression of the research result on a map was conducted by using GIS software. [Result] Seven counties （cities） exhibited comparative advantages in watermelon production, namely, Lingshui, Wanning, Wenchang, Dongfang, Sanya, Ledong, and Changjiang. The Eastern and Southern Hainan Provinces had CCAs, and the Western and Northern Hainan Provinces could be reserved for future development. For melon production, four counties （cities） exhibited comparative advantages, namely, Ledong, Lingshui, Sanya, and Dongfang. The Southern Hainan Province had CCA, whereas the West- ern Hainan Province could be reserved for later development. [Conclusion] The result has showed that establishing watermelon and melon as dominant agricultural prod- ucts is necessary for the future development of the industry and for the formulation of a layout of regions with advantages, where key support and construction should be provided preferentially with the aim to raise the yield, quality, and market com- petitiveness of products.展开更多
Using GIS spatial statistical analysis method, with ArcGIS software as an analysis tool, taking the diseased maize in Hedong District of Linyi City as the study object, the distribution characteristic of the diseased ...Using GIS spatial statistical analysis method, with ArcGIS software as an analysis tool, taking the diseased maize in Hedong District of Linyi City as the study object, the distribution characteristic of the diseased crops this time in spatial location was analyzed. The results showed that the diseased crops mainly dis- tributed along with river tributaries and downstream of main rivers. The correlation between adjacent diseased plots was little, so the infection of pests and diseases were excluded, and the major reason of incidence might be river pollution.展开更多
Using geographic information system (GIS) techniques and the newest seasonal and annual average precipitation data of 679 meteorological stations from 1971 to 2000, the multiple regressions equations of the precipitat...Using geographic information system (GIS) techniques and the newest seasonal and annual average precipitation data of 679 meteorological stations from 1971 to 2000, the multiple regressions equations of the precipitation and topographical variables are established to extract the effect of topography on the annual and seasonal precipitation in the upper-middle reaches of the Yangtze River. Then, this paper uses a successive interpolation approach (SIA), which combines GIS techniques with the multiple regressions, to improve the accuracy of the spatial interpolation of annual and seasonal rainfall. The results are very satisfactory in the case of seasonal rainfall, with the relative error of 6.86%, the absolute error of 13.07 mm, the average coefficient of variation of 0.070, and the correlation coefficient of 0.9675; in the case of annual precipitation, with the relative error of 7.34%, the absolute error of 72.1 mm, the average coefficient of variation of 0.092, and the correlation coefficient of 0.9605. The analyses of annual mean precipitation show that the SIA calculation of 3-5 steps considerably improves the interpolation accuracy, decreasing the absolute error from 211.0 mm to 62.4 mm, the relative error from 20.74% to 5.97%, the coefficient of variation from 0.2312 to 0.0761, and increasing the correlation coefficient from 0.5467 to 0.9619. The SIA iterative results after 50 steps identically converge to the observed precipitation.展开更多
Using degree distribution to assess network vulnerability represents a promising direction of network analysis.However,the traditional degree distribution model is inadequate for analyzing the vulnerability of spatial...Using degree distribution to assess network vulnerability represents a promising direction of network analysis.However,the traditional degree distribution model is inadequate for analyzing the vulnerability of spatial networks because it does not take into consideration the geographical aspects of spatial networks.This paper proposes a spatially weighted degree model in which both the functional class and the length of network links are considered to be important factors for determining the node degrees of spatial networks.A weight coefficient is used in this new model to account for the contribution of each factor to the node degree.The proposed model is compared with the traditional degree model and an accessibility-based vulnerability model in the vulnerabil-ity analysis of a highway network.Experiment results indicate that,although node degrees of spatial networks derived from the tra-ditional degree model follow a random distribution,node degrees determined by the spatially weighted model exhibit a scale-free distribution,which is a common characteristic of robust networks.Compared to the accessibility-based model,the proposed model has similar performance in identifying critical nodes but with higher computational efficiency and better ability to reveal the overall vulnerability of a spatial network.展开更多
This paper summarizes a few spatial statistical analysis methods for to measuring spatial autocorrelation and spatial association, discusses the criteria for the identification of spatial association by the use of glo...This paper summarizes a few spatial statistical analysis methods for to measuring spatial autocorrelation and spatial association, discusses the criteria for the identification of spatial association by the use of global Moran Coefficient, Local Moran and Local Geary. Furthermore, a user-friendly statistical module, combining spatial statistical analysis methods with GIS visual techniques, is developed in Arcview using Avenue. An example is also given to show the usefulness of this module in identifying and quantifying the underlying spatial association patterns between economic units.展开更多
In this study, the relationship between land use and cover change (LUCC) and variation of groundwater level and quality in the Sangong Oasis Region was investigated using a spatial geostatistical approach. Specificall...In this study, the relationship between land use and cover change (LUCC) and variation of groundwater level and quality in the Sangong Oasis Region was investigated using a spatial geostatistical approach. Specifically, interactions among groundwater, surface water, and LUCC were analyzed through the utilization of geographical information system (GIS), remote sensing (RS) Imagery processing, and geostatistics. Study outputs indicated that recharging into the groundwater did not change significantly during the period from 1978 to 1998. However, both LUCC and groundwater level changed substantially in the Sangong Oasis Region, and their variations were closely correlated to each other spatially and temporally over the past two decades. It confirmed that urbanization process and increased industrial activities were the direct reasons of groundwater table descending and the deterioration of water quality. The results of this research provided a scientific basis for understanding sustainability-related problems and solution options in the oasis areas of western China.展开更多
We used spatial, global trend and post-blocking analysis to examine the effectiveness of a progeny trial in a tree breeding program for Chinese fir （Cunninghamia lanceolata （Lamb.） Hook） on a hilly site with an en...We used spatial, global trend and post-blocking analysis to examine the effectiveness of a progeny trial in a tree breeding program for Chinese fir （Cunninghamia lanceolata （Lamb.） Hook） on a hilly site with an environmental gradient from hill top to bottom. Diameter at breast height （DBH） and tree height data had significant spatial auto-correlations among rows and columns. Adding a firstorder separable autoregressive term more effectively modelled the spatial variation than did the incomplete block （IB） model used for the experimental design. The spatial model also accounted for effects of experimental design factors and greatly reduced residual variances. The spatial analysis rel- ative to the IB analysis improved estimation of genetic parameters with the residual variance reduced 13 and 19% for DBH and tree height, respectively; heritability increased 35 and 51% for DBH and tree height, respectively; and genetic gain improved 3-5%. Fitting global trend and postblocking did not improve the analyses under IB model. The use of a spatial model or combined with a design model is recommended for forest genetic trials, particularly with global trend and local spatial variation of hilly sites.展开更多
Resources potential assessment is one of the fields in geosciences,which is able to take great advantage of GIS technology as a substitution of traditional working methods.The gold resources potential in the eastern K...Resources potential assessment is one of the fields in geosciences,which is able to take great advantage of GIS technology as a substitution of traditional working methods.The gold resources potential in the eastern Kunlun Mountains,Qinghai Province,China was assessed by combining weights-of-evidence model with GIS spatial analysis technique.All the data sets used in this paper were derived from an established multi-source geological spatial database,which contains geological,geophysical,geochemical and remote sensing data.Three multi-class variables,i.e.,structural intersection,Indosinian k-feldspar granite and regional fault,were used in proximity analysis to examine their spatial association with known gold deposits.A prospectivity map was produced by weights-of-evidence model based on seven binary evidential maps,all of which had passed a conditional independence test.The study area was divided into three target zones of high potential,moderate potential and low potential areas,among which high potential areas and moderate potential areas accounted for 20% of the total area and contained 32 of the 43 gold deposits.The results show that the gold resources potential assessment in the eastern Kunlun Mountains has a higher precision.展开更多
Popular regional inequality indexes such as variation coefficient and Gini coefficient can only reveal overall inequality, and have limited ability in revealing spatial dependence or spatial agglomeration. Recently so...Popular regional inequality indexes such as variation coefficient and Gini coefficient can only reveal overall inequality, and have limited ability in revealing spatial dependence or spatial agglomeration. Recently some methods of exploratory spatial data analysis such as spatial autocorrelation have provided effective tools to analyze spatial agglomeration and cluster, which can reveal the pattern of regional inequality. This article attempts to use spatial autocorrelation at county level to get refined spatial pattern of regional disparity in Chinese northeast economic region over 2000-2006 (2001 absent). The result indicates that the basic trend of regional economy is an increasing concentration of growth among counties in northeast economic region, and there are two geographical clusters of poorer counties including the counties in western Liaoning Province and adjacent counties in Inner Mongolia, poorer counties of Heihe, Qiqihar and Suihua in Heilongjiang Province. This article also reveals that we can use the methods of exploratory spatial data analysis as the supplementary analysis methods in regional economic analysis.展开更多
The aviation industry has become one of the top ten greenhouse gas emission industries in the world. China’s aviation carbon emissions continue to increase, but the analysis of its influencing factors at the provinci...The aviation industry has become one of the top ten greenhouse gas emission industries in the world. China’s aviation carbon emissions continue to increase, but the analysis of its influencing factors at the provincial level is still incomplete. This paper firstly uses Stochastic Impacts by Regression on Population, Affluence and Technology model(STIRPAT) model to analyze the time series evolution of China’s aviation carbon emissions from 2000 to 2019. Secondly, it uses the Logarithmic Mean Divisia Index(LDMI) model to analyze the influencing characteristics and degree of four factors on China’s aviation carbon emissions, which are air transportation revenue, aviation route structure, air transportation intensity and aviation energy intensity. Thirdly, it determines the various factors’ influencing direction and evolution trend of 31 provinces’ aviation carbon emissions in China(not including Hong Kong, Macao, Taiwan of China due to incomplete data). Finally, it derives the decoupling effort model and analyzes the decoupling relationship and decoupling effort degree between air carbon emissions and air transportation revenue in different provinces. The study found that from 2000 to2019, China’s total aviation carbon emissions continued to grow, while the growth rate of aviation carbon emissions showed a fluctuating downward trend. Air transportation revenue and aviation route structure promote the growth of total aviation carbon emissions, and air transportation intensity and aviation energy intensity have a restraining effect on the growth of total aviation carbon emissions. The scope of negative driving effect of air transportation revenue and air transportation intensity on total aviation carbon emissions in various provinces has increased. While the scope of positive driving influence of aviation route structure on total aviation carbon emissions of various provinces has increased, aviation energy intensity mainly has negative driving influence on total aviation carbon emissions of each province. Overall, the emission reduction trend in the areas to the west and north of the Qinling-Huaihe River Line is obvious. The decoupling mode between air carbon emissions and air transportation revenue in 31 provinces is mainly expansion negative decoupling.The air transportation intensity effect shows strong decoupling efforts in most provinces, the decoupling effort of aviation route structure effect and aviation energy intensity effect is not prominent.展开更多
Formulation of different ecological zone plans according to the corresponding protection targets and the necessity of proper conservation policy is one of the measures to achieve the goal of ecological conservation in...Formulation of different ecological zone plans according to the corresponding protection targets and the necessity of proper conservation policy is one of the measures to achieve the goal of ecological conservation in China.In order to clarify the interrelation among key ecological zone plans,this paper carried out the research on spatial relation of priority areas of biodiversity conservation and three key ecological areas(key ecological function areas,key regions of ecological service function,national nature reserves)and the research on ecological conditions,based on multi-scale ecological spatial theme information,which incorporates elements like ecological quality and type,and by the aid of spatial information analysis and GIS modeling.The results showed a contrastively fine spatial consistency with 68.8%of priority areas of biodiversity conservation overlapping with three key ecological areas.Although the environment in priority areas of biodiversity conservation were in good conditions,protection pressure is also increasing,powerful supervision and protection should not be ignored.The environmental conditions in the overlapping areas,as a whole,were superior to those in the non-overlapping areas.Since two areas have different characteristics,targeted protection measures should be formulated based on this difference,which will be very important for biodiversity conservation in priority areas of biodiversity conservation.展开更多
The spatial calculating analysis model is based on GIS overlay. It will compartmentalize the land in research district into three spatial types: unchanged parts, converted parts and increased parts. By this method we ...The spatial calculating analysis model is based on GIS overlay. It will compartmentalize the land in research district into three spatial types: unchanged parts, converted parts and increased parts. By this method we can evaluate the numerical model and dynamic degree model for calculating land-use change rates. Furthermore, the paper raises the possibility of revising the calculating analysis model of spatial information in order to predicate more precisely the dynamic changing level of all types of land uses. In the most concrete terms, the model is used mainly to understand changed area and changed rates (increasing or decreasing) of different land types from microcosmic angle and establish spatial distribution and spatio-temporal principles of the changing urban lands. And we will try to find out why the situation can take place by combining social and economic situations. The result indicates the calculating analysis model of spatial information can derive more accurate procedure of spatial transference and increase of all kinds of land from microcosmic angle. By this model and technology we can conduct the research of land-use spatio-temporal structure evolution more systematically and more deeply, and can obtain a satisfactory result. The result will benefit the rational planning and management of urban land use of developed coastal areas in China in the future.展开更多
Accurate and reliable predictions of pest species distributions in forest ecosystems are urgently needed by forest managers to develop management plans and monitor new areas of potential establishment.Presence-only sp...Accurate and reliable predictions of pest species distributions in forest ecosystems are urgently needed by forest managers to develop management plans and monitor new areas of potential establishment.Presence-only species distribution models are commonly used in these evaluations.The maximum entropy algorithm(MaxEnt)has gained popularity for modelling species distribution.Here,MaxEnt was used to model the spatial distribution of the Mexican pine bark beetle(Dendroctonus mexicanus)in a daily fashion by using forecast data from the Weather Research and Forecasting model.This study aimed to exploit freely available geographic and environmental data and software and thus provide a pathway to overcome the lack of costly data and technical guidance that are a challenge to implementing national monitoring and management strategies in developing countries.Our results showed overall agreement values between 60 and 87%.The results of this research can be used for D.mexicanus monitoring and management and may aid as a model to monitor similar species.展开更多
Landscape structure is often regarded as an important factor that governs the distribution and abundance of species. Therefore it is critical to understand the landscapes and their dynamics. Patterns of landscape elem...Landscape structure is often regarded as an important factor that governs the distribution and abundance of species. Therefore it is critical to understand the landscapes and their dynamics. Patterns of landscape elements strongly influence the ecological characteristics. This study was designed to document and map the current status of the tropi-cal dry deciduous forest of the Tadoba-Andhari Tiger Reserve （TATR）, Central India, （using IRS P6 LISS IV data） and to describe its landscape structure at three levels of organization viz. landscape, class, and patch. The study area was classified into 10 land cover classes that include 6 vegetation classes. The landscape structure was analyzed using FRAG-STATS using 12 set of indices. The TATR landscapes have a total of 2,307 patches with a mean patch size of 25.67 ha and patch density of 1.7 patches per km2. Amongst all land cover classes, mixed bamboo forest is dominant-it occupied maximum area （77.99%）-while riparian forest is least represented （0.32%）. Mixed forest has maximum number of patches among all vegetation classes. Results have shown that despite being dominant in the area, mixed bamboo forest has low patch density （0.25/100 ha）. Dominance of mixed bamboo forest is attributed to large patch sizes and not to the number of patches. This study has focussed on the approach of integrating satellite forest classification and forest inven-tory data for studying forest landscape patterns.展开更多
Challenges faced by African countries in achieving the goals of sustainable development are similar and trans-boundary. Previous analysis of Africa’s progress on the Sustainable Development Goals (SDGs) has largely b...Challenges faced by African countries in achieving the goals of sustainable development are similar and trans-boundary. Previous analysis of Africa’s progress on the Sustainable Development Goals (SDGs) has largely beennon-spatial, reducing the ability to find spatial relationships between countries and SDGs to help cooperationand proffer country-specific interventions. This study adopted techniques of exploratory and inferential spatialstatistics to assess the successes of African countries from 2016 to 2020 in achieving the goals of sustainable de-velopment. Also, the study sought to understand how the spatial synergies and trade-offs between SDGs vary percountry and time. The results revealed that spatial hotspots of countries with high SDGs scores were mostly con-fined to northern African countries with significant coldspots within central and eastern Africa and few patchesin western and southern Africa for 2016. In 2020, the number of countries forming hotspots reduced, with Cen-tral African countries as significant cold spots. Five main spatial relationships: positive linear, negative linear,concave, convex and undefined complex, were found among countries and the SDGs. However, these spatialrelationships were fluid as they changed over time and with different levels of influence from 2016 to 2020.The study concludes that generic solutions and policies by development agencies, governments, developmentfinance instiutions and other impact investors will not be enough in achieving the SDGs because of the spatialheterogeneity of the continent. Tailored and country-specific policies based on results of spatial statistics matter.展开更多
文摘Serial remote sensing images offer a valuable means of tracking the evolutionary changes and growth of a specific geographical area over time.Although the original images may provide limited insights,they harbor considerable potential for identifying clusters and patterns.The aggregation of these serial remote sensing images(SRSI)becomes increasingly viable as distinct patterns emerge in diverse scenarios,such as suburbanization,the expansion of native flora,and agricultural activities.In a novel approach,we propose an innovative method for extracting sequential patterns by combining Ant Colony Optimization(ACD)and Empirical Mode Decomposition(EMD).This integration of the newly developed EMD and ACO techniques proves remarkably effective in identifying the most significant characteristic features within serial remote sensing images,guided by specific criteria.Our findings highlight a substantial improvement in the efficiency of sequential pattern mining through the application of this unique hybrid method,seamlessly integrating EMD and ACO for feature selection.This study exposes the potential of our innovative methodology,particularly in the realms of urbanization,native vegetation expansion,and agricultural activities.
基金National Natural Science Foundation of China(No.42071368)Fundamental Research Funds for the Central Universities(Nos.2042022dx0001,2042024kf0005).
文摘Population aging has become an inevitable trend and exerted profound influences on socio-economic development in China.In this study,we utilized data from national population census and statistical yearbooks in 2010 and 2020 to explore spatio-temporal patterns of aging population and its coupling correlations with socio-economic factors from both global and local perspectives.The results from Local Indicators of Spatial Association(LISA)uncover notable spatial disparities in aging population rates,with higher rates concentrated in the eastern regions and lower rates in the western areas of the Chinese mainland.The results from the global correlation analysis with the changes in aging population rates show significant positive correlations with government interventions and industrial structures,but negatively correlated with economic development,social consumption,and medical facilities.From a local perspective,a Geographically Weighted(GW)correlation analysis is employed to uncover local correlations between aging trends and socio-economic factors.The insights gained from this technique not only underscore the complexity and diversity of economic implications stemming from population aging,but also provide invaluable guidance for crafting region-specific economic policies tailored to various stages of population aging.
文摘In recent decades, Urban Heat Island Effects have become more pronounced and more widely examined. Despite great technological advances, our current societies still experience great spatial disparity in urban forest access. Urban Heat Island Effects are measurable phenomenon that are being experienced by the world’s most urbanized areas, including increased summer high temperatures and lower evapotranspiration from having impervious surfaces instead of vegetation and trees. Tree canopy cover is our natural mitigation tool that absorbs sunlight for photosynthesis, protects humans from incoming radiation, and releases cooling moisture into the air. Unfortunately, urban areas typically have low levels of vegetation. Vulnerable urban communities are lower-income areas of inner cities with less access to heat protection like air conditioners. This study uses mean evapotranspiration levels to assess the variability of urban heat island effects across the state of Tennessee. Results show that increased developed land surface cover in Tennessee creates measurable changes in atmospheric evapotranspiration. As a result, the mean evapotranspiration levels in areas with less tree vegetation are significantly lower than the surrounding forested areas. Central areas of urban cities in Tennessee had lower mean evapotranspiration recordings than surrounding areas with less development. This work demonstrates the need for increased tree canopy coverage.
基金The National Key Research and Development Program of China,No.2021YFE0190100Inner Mongolia Autonomous Region Mongolian Medicine Standardization Project,No.2023-[MB023]The Earmarked Fund for CARS,No.CARS-21。
文摘Medicinal plant diversity(MPD)is an indispensable part of global plant diversity,serving as the foundation for human survival by offering remedies and preventive measures against diseases.However,factors such as overexploitation,competition from invasive alien species,and climate change,threaten the habitats of medicinal plants,necessitating a comprehensive understanding of their spatial distribution and suitable habitats.We leveraged a decade of field survey data on medicinal plant distribution in the Yinshan Mountains,combined with spatial analysis,species distribution modeling,and the Carnegie Ames Stanford Approach(CASA)to explore the MPD spatial distribution and suitable habitats.Spatial analysis revealed that the central and eastern parts of Yinshan Mountains were the primary MPD hotspots,with no cold spots evident at various spatial scales.As the spatial scale decreased,previous non-significant regions transformed into hotspots,with instances where large-scale hotspots became insignificant.These findings offer valuable guidance for safeguarding and nurturing MPD across diverse spatial scales.In future climate change scenarios within the shared socioeconomic pathways(SSP),the habitat suitability for MPD in the Yinshan Mountains predominantly remains concentrated in the central and eastern regions.Notably,areas with high net primary productivity(NPP)values and abundant vegetation coverage align closely with MPD habitat suitability areas,potentially contributing to the region's rich MPD.
基金Supported by China Agricultural Research System(CARS-26)~~
文摘[Objective] This study investigated the spatial characteristics of counties （cities） with comparative advantages in watermelon and melon production to provide reference bases in formulating strategies for the development of watermelon and melon industries in Hainan Province. [Method] By using the sowing area, total yield, and yield per unit area of watermelon and melon in Hainan Province as research u- nits, the yield comparative advantage （YCA）, efficiency comparative advantage （E- CA）, scale comparative advantage （SCA）, concentration ratio comparative advantage （CRCA）, comprehensive comparative advantage （CCA）, ratio of yield per unit area （RYPA）, sowing area ratio （SAR）, and distribution characteristics of watermelon and melon were systematically analyzed. By referring to the agricultural statistic data of 18 counties （cities） in Hainan Province, indexes for each research unit （i.e., the YCA index, ECA index, SCA index, CRCA index, CCA index, RYPA index, and SAR index） were established and calculated to determine the comparative advantage of watermelon and melon production in Hainan Province. A spatial expression of the research result on a map was conducted by using GIS software. [Result] Seven counties （cities） exhibited comparative advantages in watermelon production, namely, Lingshui, Wanning, Wenchang, Dongfang, Sanya, Ledong, and Changjiang. The Eastern and Southern Hainan Provinces had CCAs, and the Western and Northern Hainan Provinces could be reserved for future development. For melon production, four counties （cities） exhibited comparative advantages, namely, Ledong, Lingshui, Sanya, and Dongfang. The Southern Hainan Province had CCA, whereas the West- ern Hainan Province could be reserved for later development. [Conclusion] The result has showed that establishing watermelon and melon as dominant agricultural prod- ucts is necessary for the future development of the industry and for the formulation of a layout of regions with advantages, where key support and construction should be provided preferentially with the aim to raise the yield, quality, and market com- petitiveness of products.
文摘Using GIS spatial statistical analysis method, with ArcGIS software as an analysis tool, taking the diseased maize in Hedong District of Linyi City as the study object, the distribution characteristic of the diseased crops this time in spatial location was analyzed. The results showed that the diseased crops mainly dis- tributed along with river tributaries and downstream of main rivers. The correlation between adjacent diseased plots was little, so the infection of pests and diseases were excluded, and the major reason of incidence might be river pollution.
基金The National 973 Project of China, No.2001CB309404 O versea O utstanding Youth Cooperation Project, N o. 40128001/D 05N ationalN aturalScience Foundation ofChina,N o.49375248 Zhejiang Province Science Research (C33)Project,N o.2004C33082
文摘Using geographic information system (GIS) techniques and the newest seasonal and annual average precipitation data of 679 meteorological stations from 1971 to 2000, the multiple regressions equations of the precipitation and topographical variables are established to extract the effect of topography on the annual and seasonal precipitation in the upper-middle reaches of the Yangtze River. Then, this paper uses a successive interpolation approach (SIA), which combines GIS techniques with the multiple regressions, to improve the accuracy of the spatial interpolation of annual and seasonal rainfall. The results are very satisfactory in the case of seasonal rainfall, with the relative error of 6.86%, the absolute error of 13.07 mm, the average coefficient of variation of 0.070, and the correlation coefficient of 0.9675; in the case of annual precipitation, with the relative error of 7.34%, the absolute error of 72.1 mm, the average coefficient of variation of 0.092, and the correlation coefficient of 0.9605. The analyses of annual mean precipitation show that the SIA calculation of 3-5 steps considerably improves the interpolation accuracy, decreasing the absolute error from 211.0 mm to 62.4 mm, the relative error from 20.74% to 5.97%, the coefficient of variation from 0.2312 to 0.0761, and increasing the correlation coefficient from 0.5467 to 0.9619. The SIA iterative results after 50 steps identically converge to the observed precipitation.
基金Supported by the Institute of Crustal Dynamics Funds (No. ZDJ2009‐01, No. ZDJ2007‐13)
文摘Using degree distribution to assess network vulnerability represents a promising direction of network analysis.However,the traditional degree distribution model is inadequate for analyzing the vulnerability of spatial networks because it does not take into consideration the geographical aspects of spatial networks.This paper proposes a spatially weighted degree model in which both the functional class and the length of network links are considered to be important factors for determining the node degrees of spatial networks.A weight coefficient is used in this new model to account for the contribution of each factor to the node degree.The proposed model is compared with the traditional degree model and an accessibility-based vulnerability model in the vulnerabil-ity analysis of a highway network.Experiment results indicate that,although node degrees of spatial networks derived from the tra-ditional degree model follow a random distribution,node degrees determined by the spatially weighted model exhibit a scale-free distribution,which is a common characteristic of robust networks.Compared to the accessibility-based model,the proposed model has similar performance in identifying critical nodes but with higher computational efficiency and better ability to reveal the overall vulnerability of a spatial network.
文摘This paper summarizes a few spatial statistical analysis methods for to measuring spatial autocorrelation and spatial association, discusses the criteria for the identification of spatial association by the use of global Moran Coefficient, Local Moran and Local Geary. Furthermore, a user-friendly statistical module, combining spatial statistical analysis methods with GIS visual techniques, is developed in Arcview using Avenue. An example is also given to show the usefulness of this module in identifying and quantifying the underlying spatial association patterns between economic units.
基金supported by the National Key Basic Research Development Program of China (2009CB825105)National Natural Science Foundation of China (No. 40730633)
文摘In this study, the relationship between land use and cover change (LUCC) and variation of groundwater level and quality in the Sangong Oasis Region was investigated using a spatial geostatistical approach. Specifically, interactions among groundwater, surface water, and LUCC were analyzed through the utilization of geographical information system (GIS), remote sensing (RS) Imagery processing, and geostatistics. Study outputs indicated that recharging into the groundwater did not change significantly during the period from 1978 to 1998. However, both LUCC and groundwater level changed substantially in the Sangong Oasis Region, and their variations were closely correlated to each other spatially and temporally over the past two decades. It confirmed that urbanization process and increased industrial activities were the direct reasons of groundwater table descending and the deterioration of water quality. The results of this research provided a scientific basis for understanding sustainability-related problems and solution options in the oasis areas of western China.
基金funded by the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(Grant No.15KJA220002)Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)Fujian Province Science and Technology Research funding on the fourth Tree Breeding Cycle Program of Chinese fir(Grant No.Min Lin 2016-1)
文摘We used spatial, global trend and post-blocking analysis to examine the effectiveness of a progeny trial in a tree breeding program for Chinese fir （Cunninghamia lanceolata （Lamb.） Hook） on a hilly site with an environmental gradient from hill top to bottom. Diameter at breast height （DBH） and tree height data had significant spatial auto-correlations among rows and columns. Adding a firstorder separable autoregressive term more effectively modelled the spatial variation than did the incomplete block （IB） model used for the experimental design. The spatial model also accounted for effects of experimental design factors and greatly reduced residual variances. The spatial analysis rel- ative to the IB analysis improved estimation of genetic parameters with the residual variance reduced 13 and 19% for DBH and tree height, respectively; heritability increased 35 and 51% for DBH and tree height, respectively; and genetic gain improved 3-5%. Fitting global trend and postblocking did not improve the analyses under IB model. The use of a spatial model or combined with a design model is recommended for forest genetic trials, particularly with global trend and local spatial variation of hilly sites.
基金Under the auspices of National High-tech R & D Program of China(No.2007AA12Z227)National Natural Science Foundation of China(No.40701146)
文摘Resources potential assessment is one of the fields in geosciences,which is able to take great advantage of GIS technology as a substitution of traditional working methods.The gold resources potential in the eastern Kunlun Mountains,Qinghai Province,China was assessed by combining weights-of-evidence model with GIS spatial analysis technique.All the data sets used in this paper were derived from an established multi-source geological spatial database,which contains geological,geophysical,geochemical and remote sensing data.Three multi-class variables,i.e.,structural intersection,Indosinian k-feldspar granite and regional fault,were used in proximity analysis to examine their spatial association with known gold deposits.A prospectivity map was produced by weights-of-evidence model based on seven binary evidential maps,all of which had passed a conditional independence test.The study area was divided into three target zones of high potential,moderate potential and low potential areas,among which high potential areas and moderate potential areas accounted for 20% of the total area and contained 32 of the 43 gold deposits.The results show that the gold resources potential assessment in the eastern Kunlun Mountains has a higher precision.
基金supported by the National Natural Science Foundation for Distinguished Young Scholar of China (Grant No.40225004)
文摘Popular regional inequality indexes such as variation coefficient and Gini coefficient can only reveal overall inequality, and have limited ability in revealing spatial dependence or spatial agglomeration. Recently some methods of exploratory spatial data analysis such as spatial autocorrelation have provided effective tools to analyze spatial agglomeration and cluster, which can reveal the pattern of regional inequality. This article attempts to use spatial autocorrelation at county level to get refined spatial pattern of regional disparity in Chinese northeast economic region over 2000-2006 (2001 absent). The result indicates that the basic trend of regional economy is an increasing concentration of growth among counties in northeast economic region, and there are two geographical clusters of poorer counties including the counties in western Liaoning Province and adjacent counties in Inner Mongolia, poorer counties of Heihe, Qiqihar and Suihua in Heilongjiang Province. This article also reveals that we can use the methods of exploratory spatial data analysis as the supplementary analysis methods in regional economic analysis.
基金Under the auspices of the National Natural Science Foundation of China(No.42071266)the Third Batch of Hebei Youth Top Talent ProjectNatural Science Foundation of Hebei Province(No.D2021205003)。
文摘The aviation industry has become one of the top ten greenhouse gas emission industries in the world. China’s aviation carbon emissions continue to increase, but the analysis of its influencing factors at the provincial level is still incomplete. This paper firstly uses Stochastic Impacts by Regression on Population, Affluence and Technology model(STIRPAT) model to analyze the time series evolution of China’s aviation carbon emissions from 2000 to 2019. Secondly, it uses the Logarithmic Mean Divisia Index(LDMI) model to analyze the influencing characteristics and degree of four factors on China’s aviation carbon emissions, which are air transportation revenue, aviation route structure, air transportation intensity and aviation energy intensity. Thirdly, it determines the various factors’ influencing direction and evolution trend of 31 provinces’ aviation carbon emissions in China(not including Hong Kong, Macao, Taiwan of China due to incomplete data). Finally, it derives the decoupling effort model and analyzes the decoupling relationship and decoupling effort degree between air carbon emissions and air transportation revenue in different provinces. The study found that from 2000 to2019, China’s total aviation carbon emissions continued to grow, while the growth rate of aviation carbon emissions showed a fluctuating downward trend. Air transportation revenue and aviation route structure promote the growth of total aviation carbon emissions, and air transportation intensity and aviation energy intensity have a restraining effect on the growth of total aviation carbon emissions. The scope of negative driving effect of air transportation revenue and air transportation intensity on total aviation carbon emissions in various provinces has increased. While the scope of positive driving influence of aviation route structure on total aviation carbon emissions of various provinces has increased, aviation energy intensity mainly has negative driving influence on total aviation carbon emissions of each province. Overall, the emission reduction trend in the areas to the west and north of the Qinling-Huaihe River Line is obvious. The decoupling mode between air carbon emissions and air transportation revenue in 31 provinces is mainly expansion negative decoupling.The air transportation intensity effect shows strong decoupling efforts in most provinces, the decoupling effort of aviation route structure effect and aviation energy intensity effect is not prominent.
基金Under the auspices of Public Science and Technology Research Funds of Environment(No.201009021,2011467026,2012467044)National Key Technology R&D Program of China(No.2012BAH32B03)National Natural Science Foundation of China(No.41171318,41001160)
文摘Formulation of different ecological zone plans according to the corresponding protection targets and the necessity of proper conservation policy is one of the measures to achieve the goal of ecological conservation in China.In order to clarify the interrelation among key ecological zone plans,this paper carried out the research on spatial relation of priority areas of biodiversity conservation and three key ecological areas(key ecological function areas,key regions of ecological service function,national nature reserves)and the research on ecological conditions,based on multi-scale ecological spatial theme information,which incorporates elements like ecological quality and type,and by the aid of spatial information analysis and GIS modeling.The results showed a contrastively fine spatial consistency with 68.8%of priority areas of biodiversity conservation overlapping with three key ecological areas.Although the environment in priority areas of biodiversity conservation were in good conditions,protection pressure is also increasing,powerful supervision and protection should not be ignored.The environmental conditions in the overlapping areas,as a whole,were superior to those in the non-overlapping areas.Since two areas have different characteristics,targeted protection measures should be formulated based on this difference,which will be very important for biodiversity conservation in priority areas of biodiversity conservation.
基金State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingNo.WKL((020)0302)
文摘The spatial calculating analysis model is based on GIS overlay. It will compartmentalize the land in research district into three spatial types: unchanged parts, converted parts and increased parts. By this method we can evaluate the numerical model and dynamic degree model for calculating land-use change rates. Furthermore, the paper raises the possibility of revising the calculating analysis model of spatial information in order to predicate more precisely the dynamic changing level of all types of land uses. In the most concrete terms, the model is used mainly to understand changed area and changed rates (increasing or decreasing) of different land types from microcosmic angle and establish spatial distribution and spatio-temporal principles of the changing urban lands. And we will try to find out why the situation can take place by combining social and economic situations. The result indicates the calculating analysis model of spatial information can derive more accurate procedure of spatial transference and increase of all kinds of land from microcosmic angle. By this model and technology we can conduct the research of land-use spatio-temporal structure evolution more systematically and more deeply, and can obtain a satisfactory result. The result will benefit the rational planning and management of urban land use of developed coastal areas in China in the future.
文摘Accurate and reliable predictions of pest species distributions in forest ecosystems are urgently needed by forest managers to develop management plans and monitor new areas of potential establishment.Presence-only species distribution models are commonly used in these evaluations.The maximum entropy algorithm(MaxEnt)has gained popularity for modelling species distribution.Here,MaxEnt was used to model the spatial distribution of the Mexican pine bark beetle(Dendroctonus mexicanus)in a daily fashion by using forecast data from the Weather Research and Forecasting model.This study aimed to exploit freely available geographic and environmental data and software and thus provide a pathway to overcome the lack of costly data and technical guidance that are a challenge to implementing national monitoring and management strategies in developing countries.Our results showed overall agreement values between 60 and 87%.The results of this research can be used for D.mexicanus monitoring and management and may aid as a model to monitor similar species.
基金National Natural Resource Management System(NNRMS)and Ministry of Environment and Forests(MoEF),Government of India for funding the project"Mapping of National Parks and Wildlife Sanctuaries"
文摘Landscape structure is often regarded as an important factor that governs the distribution and abundance of species. Therefore it is critical to understand the landscapes and their dynamics. Patterns of landscape elements strongly influence the ecological characteristics. This study was designed to document and map the current status of the tropi-cal dry deciduous forest of the Tadoba-Andhari Tiger Reserve （TATR）, Central India, （using IRS P6 LISS IV data） and to describe its landscape structure at three levels of organization viz. landscape, class, and patch. The study area was classified into 10 land cover classes that include 6 vegetation classes. The landscape structure was analyzed using FRAG-STATS using 12 set of indices. The TATR landscapes have a total of 2,307 patches with a mean patch size of 25.67 ha and patch density of 1.7 patches per km2. Amongst all land cover classes, mixed bamboo forest is dominant-it occupied maximum area （77.99%）-while riparian forest is least represented （0.32%）. Mixed forest has maximum number of patches among all vegetation classes. Results have shown that despite being dominant in the area, mixed bamboo forest has low patch density （0.25/100 ha）. Dominance of mixed bamboo forest is attributed to large patch sizes and not to the number of patches. This study has focussed on the approach of integrating satellite forest classification and forest inven-tory data for studying forest landscape patterns.
文摘Challenges faced by African countries in achieving the goals of sustainable development are similar and trans-boundary. Previous analysis of Africa’s progress on the Sustainable Development Goals (SDGs) has largely beennon-spatial, reducing the ability to find spatial relationships between countries and SDGs to help cooperationand proffer country-specific interventions. This study adopted techniques of exploratory and inferential spatialstatistics to assess the successes of African countries from 2016 to 2020 in achieving the goals of sustainable de-velopment. Also, the study sought to understand how the spatial synergies and trade-offs between SDGs vary percountry and time. The results revealed that spatial hotspots of countries with high SDGs scores were mostly con-fined to northern African countries with significant coldspots within central and eastern Africa and few patchesin western and southern Africa for 2016. In 2020, the number of countries forming hotspots reduced, with Cen-tral African countries as significant cold spots. Five main spatial relationships: positive linear, negative linear,concave, convex and undefined complex, were found among countries and the SDGs. However, these spatialrelationships were fluid as they changed over time and with different levels of influence from 2016 to 2020.The study concludes that generic solutions and policies by development agencies, governments, developmentfinance instiutions and other impact investors will not be enough in achieving the SDGs because of the spatialheterogeneity of the continent. Tailored and country-specific policies based on results of spatial statistics matter.
