The incorporation of graphene fillers into polymer matrices has been recognized for its potential to enhance thermal conductivity,which is particularly beneficial for applications in thermal management.The uniformity ...The incorporation of graphene fillers into polymer matrices has been recognized for its potential to enhance thermal conductivity,which is particularly beneficial for applications in thermal management.The uniformity of graphene dispersion is pivotal to achieving optimal thermal conductivity,thereby directly influencing the effectiveness of thermal management,including the mitigation of local hot-spot temperatures.This research employs a quantitative approach to assess the distribution of graphene fillers within a PBX(plastic-bonded explosive)matrix,focusing specifically on the thermal management of hot spots.Through finite element method(FEM)simulations,we have explored the impact of graphene filler orientation,proximity to the central heat source,and spatial clustering on heat transfer.Our findings indicate that the strategic distribution of graphene fillers can create efficient thermal conduction channels,which significantly reduce the temperatures at local hot spots.In a model containing 0.336%graphene by volume,the central hot-spot temperature was reduced by approximately 60 K compared to a pure PBX material,under a heat flux of 600 W/m^(2).This study offers valuable insights into the optimization of the spatial arrangement of low-concentration graphene fillers,aiming to improve the thermal management capabilities of HMX-based PBX explosives.展开更多
Nowadays,the evaluation of coal deposits becomes crucial,due to many uncontrollable factors,which affect the energy sector.A comparative evaluation of coal deposits is essential for their hierarchical classification r...Nowadays,the evaluation of coal deposits becomes crucial,due to many uncontrollable factors,which affect the energy sector.A comparative evaluation of coal deposits is essential for their hierarchical classification regarding their sustainable exploitation,when compared to other coal deposits or competitive fuels,which may be used as alternative solutions for electricity generation.In this paper,a method for spatial analysis and evaluation of a lignite deposit is proposed,by creating four spatial key indicators via GIS analysis,which are then aggregated by applying a weighted linear combination.The analytical hierarchy process is applied to estimate the relative weights of the indicators,in order to perform a weighted cartographic overlay.Through the synthesis of the indicators,an overall,total spatial quality indicator is calculated.The weighted analysis was shown to be more effective compared to the unweighted one,because it can provide more reliable results regarding the exploitation of the examined lignite deposit.The implementation of GIS-based analytical hierarchy process in spatial analysis and evaluation of lignite deposits,in terms of sustainable exploitation,demonstrates that this method can be extensively applied for evaluating the economic potential of mineral deposits.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
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
In recent years,the situation of the Hyphantria cunea(Drury)(Lepidoptera:Erebidae),infestation in China has been serious and has a tendency to continue to spread.A comprehensive analysis was carried out to examine the...In recent years,the situation of the Hyphantria cunea(Drury)(Lepidoptera:Erebidae),infestation in China has been serious and has a tendency to continue to spread.A comprehensive analysis was carried out to examine the spa-tial distribution trends and influencing factors of H.cunea.This analysis involved integrating administrative division and boundary data,distribution data of H.cunea,and envi-ronmental variables for 2021.GeoDetector and gravity analysis techniques were employed for data processing and interpretation.The results show that H.cunea exhibited high aggregation patterns in 2021 and 2022 concentrated mainly in eastern China.During these years,the focal point of the infestation was in Shandong Province with a spread towards the northeast.Conditions such as high vegetation density in eastern China provided favorable situations for growth and development of H.cunea.In China,the spatial distribution of the moth is primarily influenced by two critical factors:precipitation during the driest month and elevation.These play a pivotal role in determining the spread of the species.Based on these results,suggestions are provided for a mul-tifaceted approach to prevention and control of H.cunea infestation.展开更多
Understanding population structure provides basic ecological data related to species and ecosystems.Our objective was to understand the mechanisms involved in the maintenance of Quercus aquifolioides populations.Using...Understanding population structure provides basic ecological data related to species and ecosystems.Our objective was to understand the mechanisms involved in the maintenance of Quercus aquifolioides populations.Using a 1 ha permanent sample plot data for Q.aquifolioides on Sejila Mountain,Tibet Autonomous Region(Tibet),China,we analyzed the population structure of Q.aquifolioides by combining data for diameter class,static life table and survival curve.Simultaneously,the spatial distribution of Q.aquifolioides was studied using Ripley’s L Function in point pattern analysis.The results showed:(1) Individuals in Q.aquifolioides populations were mainly aggregated in the youngest age classes,that accounted for94.3% of the individuals; the older age classes had much smaller populations.Although the youngest age classes(ClassesⅠ and Ⅱ) had fewer individuals than Class Ⅲ,the total number of individuals in classes Ⅰ and Ⅱ was also greater than in classes Ⅳ to Ⅸ.In terms of tree height,fewsaplings,more medium-sized saplings and few large-sized trees were found.The diameter class structure of Q.aquifolioides populations formed an atypical ‘pyramid’type; the population was expanding,but growth was limited,tending toward a stable population.(2) Mortality of Q.aquifolioides increased continuously with age; life expectancy decreased over time,and the survivorship curve was close to a Deevey I curve.(3) The spatial distribution pattern of Q.aquifolioides varied widely across different developmental stages.Saplings and medium-sized tree showed aggregated distributions at the scales of 0–33 m and 0–29 m,respectively.The aggregation intensities of saplings and medium-sized trees at small scales were significantly stronger than that of large-sized trees.However,large-sized trees showed a random distribution at most scales.(4) No correlation was observed among saplings,medium-and large-sized trees at small scales,while a significant and negative association was observed as the scale increased.Strong competition was found among saplings,medium-and large-sized trees,while no significant association was observed between medium-and largesized trees at all scales.Biotic interactions and local ecological characteristics influenced the spatial distribution pattern of Q.aquifolioides populations most strongly.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
Canonical correlation analysis ( CCA ) based methods for low-resolution ( LR ) face recognition involve face images with different resolutions ( or multi-resolutions ), i.e.LR and high-resolution ( HR ) .For single-re...Canonical correlation analysis ( CCA ) based methods for low-resolution ( LR ) face recognition involve face images with different resolutions ( or multi-resolutions ), i.e.LR and high-resolution ( HR ) .For single-resolution face recognition , researchers have shown that utilizing spatial information is beneficial to improving the recognition accuracy , mainly because the pixels of each face are not independent but spatially correlated.However , for a multi-resolution scenario , there are no related works.Therefore , a method named spatial regularization of canonical correlation analysis ( SRCCA ) is developed for LR face recognition to improve the performance of CCA by the regularization utilizing spatial information of different resolution faces.Furthermore , the impact of LR and HR spatial regularization terms on LR face recognition is analyzed through experiments.展开更多
The Zagros forests are a treasure of valuable oak forests, but they have been severely degraded from long-term misuse. Geographic information systems （GIS） and multi-criteria decision analysis （MCDA） have been inc...The Zagros forests are a treasure of valuable oak forests, but they have been severely degraded from long-term misuse. Geographic information systems （GIS） and multi-criteria decision analysis （MCDA） have been increasingly used to improve the management of vulnerable ecosystems to prevent further degradation and increase the sustainability of land use. This study presents a methodology to assess land suitability using remote sensing （RS） to obtain wall-to-wall data for the calculations, GIS to analyze the data, and MCDA to rank alternative land uses. The criteria and subcriteria affecting the suitability of land for different uses were identified and weighted using an analytic hierarchy process. Variables used as subcriteria were assessed using satellite data and other sources of information such as existing maps and field surveys. Numerical values for the subcriteria were classified, and each class was given a priority rating according to expert judgments. Based on the ratings and weights of the subcriteria, a priority map was created for each land use using the weighted linear combination method. The priority maps for different land uses were overlaid to obtain a preliminary land use map, which often indicated several simultaneous land uses for the same location. The preliminary map was further edited by removing unrealistic, mutually exclusive land-use combinations. The study tested and demonstrated the potential of integrating RS, G1S and MCDA techniques for solving complicated land allocation problems in forested regions using a scientifically sound and practical approach for efficient and sustainable allocation of forestland for different uses.展开更多
Wavelets is a very effective technique for time-frequency analysis with the ability of preserving loeal information, applied to many areas such as nonlinear science, information processing.quantum physics etc.. In thi...Wavelets is a very effective technique for time-frequency analysis with the ability of preserving loeal information, applied to many areas such as nonlinear science, information processing.quantum physics etc.. In this paper. from the view of ecology spatial pattern, the authors try to process the sample data of Larix forest transects to identify the canopy gap structures by wavelet analysis. The caleulation of wavelet variance, derived from the transtform facilitates comparison based on dominant scale of pattern between multiple datasets such as the stands described.展开更多
基于SQL Server Analysis Services(简称SSAS)提供的Microsoft关联规则挖掘算法和事务数据挖掘功能,通过利用Arc GIS软件、空间数据库引擎Arc SDE和数据库SQL Server软件,提出了一种新的土地地类关系挖掘实现方案。首先结合空间数据挖掘...基于SQL Server Analysis Services(简称SSAS)提供的Microsoft关联规则挖掘算法和事务数据挖掘功能,通过利用Arc GIS软件、空间数据库引擎Arc SDE和数据库SQL Server软件,提出了一种新的土地地类关系挖掘实现方案。首先结合空间数据挖掘(Spatial Data Mining,SDM)相关技术方法,以土地利用数据库为基础,实现空间数据提取;然后通过空间关联操作将空间信息转化为事务,最后在SSAS中创建多维数据集,完成相关数据挖掘任务。基于某市实例土地利用数据库,采用该方法探测相邻地类间的隐含关系,通过建立相邻地类图斑空间关联规则挖掘模型,设置不同的参数,得到了一系列比较实用合理的关联规则,通过实践证明了这种方案的有效性。展开更多
Types and structure of plant communities in the Yellow River Delta were investigated by using detrended canonical correspondence analyses （DCCAs） and a two-way indicator species analysis （TWINSPAN）. The distributi...Types and structure of plant communities in the Yellow River Delta were investigated by using detrended canonical correspondence analyses （DCCAs） and a two-way indicator species analysis （TWINSPAN）. The distribution pattern and influential factors of the plant communities were also analyzed by testing elevation, slope, soil characteristics, longitude and latitude of 134 vegetation samples collected by representative plot sampling methods. Results showed that all the 134 vegetation samples could be divided into seven vegetation groups, separately dominated by Robinia pseucdoacacia, Imperata cylindrical, Miscanthus saccharifleus, Suaeda salsa, Aeluropus sinensis, Phragmites australis and Tamarix chinensis. The vegetation distribution pattern was mainly related to elevation, ground water depth and soil characteristics such as salinity and soluble potassium. Among the factors affecting distribution pattern of the plant communities, the species matrix explained by non-spatial environmental variation accounts for 45.2% of total variation. Spatial variation and spatial-structured environmental variation explain 11.8%, and 2.2%, respectively. Remained 40.8% of undetermined variation is attributed to biological and stochastic factors.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.U2330208).
文摘The incorporation of graphene fillers into polymer matrices has been recognized for its potential to enhance thermal conductivity,which is particularly beneficial for applications in thermal management.The uniformity of graphene dispersion is pivotal to achieving optimal thermal conductivity,thereby directly influencing the effectiveness of thermal management,including the mitigation of local hot-spot temperatures.This research employs a quantitative approach to assess the distribution of graphene fillers within a PBX(plastic-bonded explosive)matrix,focusing specifically on the thermal management of hot spots.Through finite element method(FEM)simulations,we have explored the impact of graphene filler orientation,proximity to the central heat source,and spatial clustering on heat transfer.Our findings indicate that the strategic distribution of graphene fillers can create efficient thermal conduction channels,which significantly reduce the temperatures at local hot spots.In a model containing 0.336%graphene by volume,the central hot-spot temperature was reduced by approximately 60 K compared to a pure PBX material,under a heat flux of 600 W/m^(2).This study offers valuable insights into the optimization of the spatial arrangement of low-concentration graphene fillers,aiming to improve the thermal management capabilities of HMX-based PBX explosives.
文摘Nowadays,the evaluation of coal deposits becomes crucial,due to many uncontrollable factors,which affect the energy sector.A comparative evaluation of coal deposits is essential for their hierarchical classification regarding their sustainable exploitation,when compared to other coal deposits or competitive fuels,which may be used as alternative solutions for electricity generation.In this paper,a method for spatial analysis and evaluation of a lignite deposit is proposed,by creating four spatial key indicators via GIS analysis,which are then aggregated by applying a weighted linear combination.The analytical hierarchy process is applied to estimate the relative weights of the indicators,in order to perform a weighted cartographic overlay.Through the synthesis of the indicators,an overall,total spatial quality indicator is calculated.The weighted analysis was shown to be more effective compared to the unweighted one,because it can provide more reliable results regarding the exploitation of the examined lignite deposit.The implementation of GIS-based analytical hierarchy process in spatial analysis and evaluation of lignite deposits,in terms of sustainable exploitation,demonstrates that this method can be extensively applied for evaluating the economic potential of mineral deposits.
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.
基金funded by the National Key Research and Development Program of China(2021YFD1400300)the Fundamental Research Funds for the Central Universities(2572022DP04).
文摘In recent years,the situation of the Hyphantria cunea(Drury)(Lepidoptera:Erebidae),infestation in China has been serious and has a tendency to continue to spread.A comprehensive analysis was carried out to examine the spa-tial distribution trends and influencing factors of H.cunea.This analysis involved integrating administrative division and boundary data,distribution data of H.cunea,and envi-ronmental variables for 2021.GeoDetector and gravity analysis techniques were employed for data processing and interpretation.The results show that H.cunea exhibited high aggregation patterns in 2021 and 2022 concentrated mainly in eastern China.During these years,the focal point of the infestation was in Shandong Province with a spread towards the northeast.Conditions such as high vegetation density in eastern China provided favorable situations for growth and development of H.cunea.In China,the spatial distribution of the moth is primarily influenced by two critical factors:precipitation during the driest month and elevation.These play a pivotal role in determining the spread of the species.Based on these results,suggestions are provided for a mul-tifaceted approach to prevention and control of H.cunea infestation.
基金financially supported by the National Key Technology Support Program(Grant No.2013BAC04B01)the National Natural Science Foundation of China(Grant No.31460200)
文摘Understanding population structure provides basic ecological data related to species and ecosystems.Our objective was to understand the mechanisms involved in the maintenance of Quercus aquifolioides populations.Using a 1 ha permanent sample plot data for Q.aquifolioides on Sejila Mountain,Tibet Autonomous Region(Tibet),China,we analyzed the population structure of Q.aquifolioides by combining data for diameter class,static life table and survival curve.Simultaneously,the spatial distribution of Q.aquifolioides was studied using Ripley’s L Function in point pattern analysis.The results showed:(1) Individuals in Q.aquifolioides populations were mainly aggregated in the youngest age classes,that accounted for94.3% of the individuals; the older age classes had much smaller populations.Although the youngest age classes(ClassesⅠ and Ⅱ) had fewer individuals than Class Ⅲ,the total number of individuals in classes Ⅰ and Ⅱ was also greater than in classes Ⅳ to Ⅸ.In terms of tree height,fewsaplings,more medium-sized saplings and few large-sized trees were found.The diameter class structure of Q.aquifolioides populations formed an atypical ‘pyramid’type; the population was expanding,but growth was limited,tending toward a stable population.(2) Mortality of Q.aquifolioides increased continuously with age; life expectancy decreased over time,and the survivorship curve was close to a Deevey I curve.(3) The spatial distribution pattern of Q.aquifolioides varied widely across different developmental stages.Saplings and medium-sized tree showed aggregated distributions at the scales of 0–33 m and 0–29 m,respectively.The aggregation intensities of saplings and medium-sized trees at small scales were significantly stronger than that of large-sized trees.However,large-sized trees showed a random distribution at most scales.(4) No correlation was observed among saplings,medium-and large-sized trees at small scales,while a significant and negative association was observed as the scale increased.Strong competition was found among saplings,medium-and large-sized trees,while no significant association was observed between medium-and largesized trees at all scales.Biotic interactions and local ecological characteristics influenced the spatial distribution pattern of Q.aquifolioides populations most strongly.
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Supported by the National Natural Science Foundation of China(6117015161070133+2 种基金60903130)the Natural Science Research Project of Higher Education of Jiangsu Province(12KJB520018)the Research Foundation of Nanjing University of Aeronautics and Astronautics(NP2011030)
文摘Canonical correlation analysis ( CCA ) based methods for low-resolution ( LR ) face recognition involve face images with different resolutions ( or multi-resolutions ), i.e.LR and high-resolution ( HR ) .For single-resolution face recognition , researchers have shown that utilizing spatial information is beneficial to improving the recognition accuracy , mainly because the pixels of each face are not independent but spatially correlated.However , for a multi-resolution scenario , there are no related works.Therefore , a method named spatial regularization of canonical correlation analysis ( SRCCA ) is developed for LR face recognition to improve the performance of CCA by the regularization utilizing spatial information of different resolution faces.Furthermore , the impact of LR and HR spatial regularization terms on LR face recognition is analyzed through experiments.
文摘The Zagros forests are a treasure of valuable oak forests, but they have been severely degraded from long-term misuse. Geographic information systems （GIS） and multi-criteria decision analysis （MCDA） have been increasingly used to improve the management of vulnerable ecosystems to prevent further degradation and increase the sustainability of land use. This study presents a methodology to assess land suitability using remote sensing （RS） to obtain wall-to-wall data for the calculations, GIS to analyze the data, and MCDA to rank alternative land uses. The criteria and subcriteria affecting the suitability of land for different uses were identified and weighted using an analytic hierarchy process. Variables used as subcriteria were assessed using satellite data and other sources of information such as existing maps and field surveys. Numerical values for the subcriteria were classified, and each class was given a priority rating according to expert judgments. Based on the ratings and weights of the subcriteria, a priority map was created for each land use using the weighted linear combination method. The priority maps for different land uses were overlaid to obtain a preliminary land use map, which often indicated several simultaneous land uses for the same location. The preliminary map was further edited by removing unrealistic, mutually exclusive land-use combinations. The study tested and demonstrated the potential of integrating RS, G1S and MCDA techniques for solving complicated land allocation problems in forested regions using a scientifically sound and practical approach for efficient and sustainable allocation of forestland for different uses.
文摘Wavelets is a very effective technique for time-frequency analysis with the ability of preserving loeal information, applied to many areas such as nonlinear science, information processing.quantum physics etc.. In this paper. from the view of ecology spatial pattern, the authors try to process the sample data of Larix forest transects to identify the canopy gap structures by wavelet analysis. The caleulation of wavelet variance, derived from the transtform facilitates comparison based on dominant scale of pattern between multiple datasets such as the stands described.
文摘基于SQL Server Analysis Services(简称SSAS)提供的Microsoft关联规则挖掘算法和事务数据挖掘功能,通过利用Arc GIS软件、空间数据库引擎Arc SDE和数据库SQL Server软件,提出了一种新的土地地类关系挖掘实现方案。首先结合空间数据挖掘(Spatial Data Mining,SDM)相关技术方法,以土地利用数据库为基础,实现空间数据提取;然后通过空间关联操作将空间信息转化为事务,最后在SSAS中创建多维数据集,完成相关数据挖掘任务。基于某市实例土地利用数据库,采用该方法探测相邻地类间的隐含关系,通过建立相邻地类图斑空间关联规则挖掘模型,设置不同的参数,得到了一系列比较实用合理的关联规则,通过实践证明了这种方案的有效性。
基金Foundation project： This study was financially supported by the Na- tional Natural Science Foundation of China （No. 40771172） and the orientation project of the Chinese Academy of Sciences （No. kzcx2-yw-308）
文摘Types and structure of plant communities in the Yellow River Delta were investigated by using detrended canonical correspondence analyses （DCCAs） and a two-way indicator species analysis （TWINSPAN）. The distribution pattern and influential factors of the plant communities were also analyzed by testing elevation, slope, soil characteristics, longitude and latitude of 134 vegetation samples collected by representative plot sampling methods. Results showed that all the 134 vegetation samples could be divided into seven vegetation groups, separately dominated by Robinia pseucdoacacia, Imperata cylindrical, Miscanthus saccharifleus, Suaeda salsa, Aeluropus sinensis, Phragmites australis and Tamarix chinensis. The vegetation distribution pattern was mainly related to elevation, ground water depth and soil characteristics such as salinity and soluble potassium. Among the factors affecting distribution pattern of the plant communities, the species matrix explained by non-spatial environmental variation accounts for 45.2% of total variation. Spatial variation and spatial-structured environmental variation explain 11.8%, and 2.2%, respectively. Remained 40.8% of undetermined variation is attributed to biological and stochastic factors.
