Measuring the amount of vegetation in a given area on a large scale has long been accomplished using satellite and aerial imaging systems.These methods have been very reliable in measuring vegetation coverage accurate...Measuring the amount of vegetation in a given area on a large scale has long been accomplished using satellite and aerial imaging systems.These methods have been very reliable in measuring vegetation coverage accurately at the top of the canopy,but their capabilities are limited when it comes to identifying green vegetation located beneath the canopy cover.Measuring the amount of urban and suburban vegetation along a street network that is partially beneath the canopy has recently been introduced with the use of Google Street View(GSV)images,made accessible by the Google Street View Image API.Analyzing green vegetation through the use of GSV images can provide a comprehensive representation of the amount of green vegetation found within geographical regions of higher population density,and it facilitates an analysis performed at the street-level.In this paper we propose a fine-tuned color based image filtering and segmentation technique and we use it to define and map an urban green environment index.We deployed this image processing method and,using GSV images as a high-resolution GIS data source,we computed and mapped the green index of Milwaukee County,a 3,082 km^(2) urban/suburban county in Wisconsin.This approach generates a high-resolution street-level vegetation estimate that may prove valuable in urban planning and management,as well as for researchers investigating the correlation between environmental factors and human health outcomes.展开更多
Simultaneous localization and mapping(SLAM)is one of the most attractive research hotspots in the field of robotics,and it is also a prerequisite for the autonomous navigation of robots.It can significantly improve th...Simultaneous localization and mapping(SLAM)is one of the most attractive research hotspots in the field of robotics,and it is also a prerequisite for the autonomous navigation of robots.It can significantly improve the autonomous navigation ability of mobile robots and their adaptability to different application environments and contribute to the realization of real-time obstacle avoidance and dynamic path planning.Moreover,the application of SLAM technology has expanded from industrial production,intelligent transportation,special operations and other fields to agricultural environments,such as autonomous navigation,independent weeding,three-dimen-sional(3D)mapping,and independent harvesting.This paper mainly introduces the principle,sys-tem framework,latest development and application of SLAM technology,especially in agricultural environments.Firstly,the system framework and theory of the SLAM algorithm are introduced,and the SLAM algorithm is described in detail according to different sensor types.Then,the devel-opment and application of SLAM in the agricultural environment are summarized from two aspects:environment map construction,and localization and navigation of agricultural robots.Finally,the challenges and future research directions of SLAM in the agricultural environment are discussed.展开更多
With the research of the upcoming sixth generation(6 G) systems, new technologies will require wider bandwidth, larger scale antenna arrays and more diverse wireless communication scenarios on the future channel model...With the research of the upcoming sixth generation(6 G) systems, new technologies will require wider bandwidth, larger scale antenna arrays and more diverse wireless communication scenarios on the future channel modeling. Considering channel model is prerequisite for system design and performance evaluation of 6 G technologies, we face a challenging task: how to accurately and efficiently model 6 G channel for various scenarios? This paper tries to answer it. Firstly, the features of cluster-nuclei(CN) and principle of cluster-nuclei based channel model(CNCM) are introduced. Then, a novel modeling framework is proposed to implement CNCM,which consists four steps: propagation environment reconstruction, cluster-nuclei identification, multipath parameters generation, and channel coefficients generation. Three-dimensional environment with material information is utilized to map CN with scatterers in the propagation pathway. CN are identified by geometrical and electric field calculation based on environmental mapping, and multipath components within CN are calculated by statistical characteristics of angle, power and delay domains. Finally, we present a three-level verification structure to investigate the accuracy and complexity of channel modeling comprehensively. Simulation results reveal that CNCM can perform higher accuracy than geometrybased stochastic model while lower complexity compared with ray-tracing model for practical propagation environment.展开更多
The present study performed on the Angovia, Kokumbo, Hire and Agbaou sites consisted of mapping the environmental risks linked to artisanal gold mining activities in C?te d’Ivoire. An inventory was done by observing ...The present study performed on the Angovia, Kokumbo, Hire and Agbaou sites consisted of mapping the environmental risks linked to artisanal gold mining activities in C?te d’Ivoire. An inventory was done by observing the different phases of gold extraction and identifying the risks associated with these phases. Using a Geographic Information System (GIS), the representation of the spatial distribution of the pollution risks has been realized from indicator descriptives of the environmental sensitivity (i.e. slope, proximity to the watercourse, soil cover) and the transfer indicator (i.e. rainfall). The analysis of this map showed low sensitivity of mercury (Hg), arsenic (As), copper (Cu) and zinc (Zn) measured in the waters of the Hire and Agbaou localities, while moderate sensitivity in Kokumbo surface waters and high sensitivity for those of Angovia locality were observed. Moreover, analysis of Hg, As, Cu and Zn content spatial distribution maps in surface waters revealed that Hg and As come mainly from the artisanal mining activities for most localities. Among these metallic trace elements observed, only the Hg content was above the WHO Limit Values, 1994 (>0.001 mg·L-1). The continuous spread of metallic trace elements in surface water can pose serious health problems for people living around artisanal gold mining sites, hence the need to put in place a protection plan against contamination.展开更多
Environmental covariates are the basis of predictive soil mapping.Their selection determines the performance of soil mapping to a great extent,especially in cases where the number of soil samples is limited but soil s...Environmental covariates are the basis of predictive soil mapping.Their selection determines the performance of soil mapping to a great extent,especially in cases where the number of soil samples is limited but soil spatial heterogeneity is high.In this study,we proposed an integrated method to select environmental covariates for predictive soil depth mapping.First,candidate variables that may influence the development of soil depth were selected based on pedogenetic knowledge.Second,three conventional methods(Pearson correlation analysis(PsCA),generalized additive models(GAMs),and Random Forest(RF))were used to generate optimal combinations of environmental covariates.Finally,three optimal combinations were integrated to produce a final combination based on the importance and occurrence frequency of each environmental covariate.We tested this method for soil depth mapping in the upper reaches of the Heihe River Basin in Northwest China.A total of 129 soil sampling sites were collected using a representative sampling strategy,and RF and support vector machine(SVM)models were used to map soil depth.The results showed that compared to the set of environmental covariates selected by the three conventional selection methods,the set of environmental covariates selected by the proposed method achieved higher mapping accuracy.The combination from the proposed method obtained a root mean square error(RMSE)of 11.88 cm,which was 2.25–7.64 cm lower than the other methods,and an R^2 value of 0.76,which was 0.08–0.26 higher than the other methods.The results suggest that our method can be used as an alternative to the conventional methods for soil depth mapping and may also be effective for mapping other soil properties.展开更多
The development of modern cities has brought about tremendous changes in the climate environment.Faced with complex climate conditions,research on multi-scale climate change in cities is of great significance.The urba...The development of modern cities has brought about tremendous changes in the climate environment.Faced with complex climate conditions,research on multi-scale climate change in cities is of great significance.The urban environmental climate maps and the application of climate atlas tool in Stuttgart,Germany were studied,and the multi-scale application of urban environmental climate maps in Stuttgart,Germany was summarized through the analysis of the pre-planning,current construction situation,and landscape reconstruction of the German"Stuttgart 21"plan case.Besides,other important measures to cope with climate change in German were proposed,and finally multi-scale practical strategies to cope with urban climate and environment were summarized to provide ideas and methods for improving China’s future urban climate environment.展开更多
A model integrating geo-information and self-organizing map(SOM) for exploring the database of soil environmental surveys was established. The dataset of 5 heavy metals(As, Cd, Cr, Hg, and Pb) was built by the regular...A model integrating geo-information and self-organizing map(SOM) for exploring the database of soil environmental surveys was established. The dataset of 5 heavy metals(As, Cd, Cr, Hg, and Pb) was built by the regular grid sampling in Hechi, Guangxi Zhuang Autonomous Region in southern China. Auxiliary datasets were collected throughout the study area to help interpret the potential causes of pollution. The main findings are as follows:(1) Soil samples of 5 elements exhibited strong variation and high skewness. High pollution risk existed in the case study area, especially Hg and Cd.(2) As and Pb had a similar topological distribution pattern, meaning they behaved similarly in the soil environment. Cr had behaviours in soil different from those of the other 4 elements.(3) From the U-matrix of SOM networks, 3 levels of SEQ were identified, and 11 high risk areas of soil heavy metal-contaminated were found throughout the study area, which were basically near rivers,factories, and ore zones.(4) The variations of contamination index(CI) followed the trend of construction land(1.353)> forestland(1.267)> cropland(1.175)> grassland(1.056), which suggest that decision makers should focus more on the problem of soil pollution surrounding industrial and mining enterprises and farmland.展开更多
During emergency response to oil spills incident accurate information is required in order to reduce the risk associated with oil spill disasters. This study focuses on Environmental Sensitivity mapping for sustainabl...During emergency response to oil spills incident accurate information is required in order to reduce the risk associated with oil spill disasters. This study focuses on Environmental Sensitivity mapping for sustainable environmental clean-up and contingency planning along the 3.0 km of AGIP pipeline at Asemoku in Delta State, Nigeria. Geographic information systems (GIS) techniques were used to create an Environmental Sensitivity Index (ESI) map in the study area. A 2018 Google Earth Satellite imagery of the study area was downloaded, and landuse/cover classification scheme comprising of Vegetation, Farmland, Water Body, Wetland, built up area and Bare Surface was adopted. Existing categorization, ranking and classification of the inland habitat were adopted and used to create a Landuse/cover Environmental Sensitivity Index (ESI) map, while the buffer zones of 100 m, 200 m, 300 m and 400 m were adopted. In the ArcGIS 10.8 environment, the landuse/cover map was generated and buffer distances of 100 m, 200 m, 300 m and 400 m were created on the landuse/cover map to ascertain the features that are vulnerable and could be at risk in the event of oil spill. This study established that the Natural Vegetation areas are the most vulnerable and sensitive feature as a result of their size along the created buffer zones. Findings from this study thus provide insight into the most sensitive land-use/land-cover, in the event of a spill or emergency oil spill clean-up response.展开更多
We have defined the environmental interface through the exchange processes between media forming this interface. Considering the environmental interface as a complex system we elaborated the advanced mathematical tool...We have defined the environmental interface through the exchange processes between media forming this interface. Considering the environmental interface as a complex system we elaborated the advanced mathematical tools for its modelling. We have suggested two coupled maps serving the exchange processes on the environmental interfaces spatially ranged from cellular to planetary level, i.e. 1) the map with diffusive coupling for energy exchange simulation and 2) the map with affinity, which is suitable for matter exchange processes at the cellular level. We have performed the dynamical analysis of the coupled maps using the Lyapunov exponent, cross sample as well as the permutation entropy in dependence on different map parameters. Finally, we discussed the map with affinity, which shows some features making it a promising toll in simulation of exchange processes on the environmental interface at the cellular level.展开更多
Giant Hogweed is a poisonous invasive weed in Latvia that poses significant threat to biodiversity and human health. Local residents are afraid and have very special concerns about the safety of their children because...Giant Hogweed is a poisonous invasive weed in Latvia that poses significant threat to biodiversity and human health. Local residents are afraid and have very special concerns about the safety of their children because the plant causes phytophotodermatitis (severe burns), painful blistering, permanent scarring and blindness when the sap of the plant comes in contact with the human body and is exposed to sunlight. This study utilizes public participation GIS (PPGIS) involving Latvian high school students as data collectors to monitor the geographic distribution of Giant Hogweed in Northeast Latvia. This paper also explores challenges with implementing such a public program, how to maximize participation, and how participation impacts environmental awareness of participants. In this study we also assessed the accuracy of PPGIS-collected data and how the utilization of such data impacts mapping and monitoring of Giant Hogweed in the study area. Results indicate that this PPGIS program is effective in facilitating data collection for monitoring Giant Hogweed in Latvia. Tested methods of increasing participation have proven largely unsuccessful to date. Statistical analyses of survey responses indicate participation had a marked effect on sensitivity towards environmental issues. Accuracy assessments indicate that quality of point data collected by participants is sufficient for mapping and for use as ground verification.展开更多
Environment matting and compositing is a technique to extract a foreground object, including color, opacity, reflec- tive and refractive properties, from a real-world scene, and synthesize new images by placing it int...Environment matting and compositing is a technique to extract a foreground object, including color, opacity, reflec- tive and refractive properties, from a real-world scene, and synthesize new images by placing it into new environments. The description of the captured object is named environment matte. Recent matting and compositing techniques can produce quite realistic images for objects with complex optical properties. This paper presents an approximate method to transform the matte by simulating variation of the foreground object’s refractive index. Our algorithms can deal with achromatous-and-transparent ob- jects and the experimental results are visually acceptable. Our idea and method can be applied to produce some special video effects, which could be very useful in film making, compared with the extreme difficulty of physically changing an object’s refractive index.展开更多
土壤有机碳(SOC)是陆地生态系统中最重要的碳库之一。在亚热带季风气候区,SOC的变化对碳循环具有重要影响。以江西省为研究区,根据SOC含量的影响因素和数据可获得性,选取37个特征变量,分别构建1987年和2011年0—100 cm土壤有机碳密度(SO...土壤有机碳(SOC)是陆地生态系统中最重要的碳库之一。在亚热带季风气候区,SOC的变化对碳循环具有重要影响。以江西省为研究区,根据SOC含量的影响因素和数据可获得性,选取37个特征变量,分别构建1987年和2011年0—100 cm土壤有机碳密度(SOCD)的空间外推模型,实现SOCD分布制图,分析土壤有机碳储量(TSOC)和土壤碳汇速率的特征。得出以下主要结论:(1)统计分析土壤样本检测的SOC含量表明,1987年至2011年间,江西省SOCD的均值从3.70 kg C/m^(2)增至12.52 kg C/m^(2)。其中,森林SOCD均值从4.37 kg C/m^(2)增至13.99 kg C/m^(2),农田SOCD均值从2.92 kg C/m^(2)增至5.94 kg C/m^(2);(2)随机森林(RF)模型在模拟2011年SOCD的空间分布中表现良好(R2=0.73,RMSE=6.22 kg C/m^(2)),受特征数据可获得性的影响,1987年SOCD的模拟精度较低;(3)根据空间外推结果,1987年至2011年间江西省土壤表现出巨大的碳汇潜力,平均SOCD从3.62 kg C/m^(2)增至11.57 kg C/m^(2),其中:森林的平均SOCD从4.13 kg C/m^(2)增至14.01 kg C/m^(2),农田的平均SOCD从2.89 kg C/m^(2)增至7.43 kg C/m^(2),草地的平均SOCD从2.98 kg C/m^(2)增至8.83 kg C/m^(2)。此外,TSOC从0.605 Pg C增至1.932 Pg C,碳汇速率依次为:森林>草地>农田。展开更多
基金This work was supported by the National Science Foundation [DUE-1129056]This research was completed under the University of Wisconsin-Milwaukee’s Undergraduate Research in Biology and Mathematics(UBM)Program and was supported by a grant from the National Science Foundation DUE-1129056.Additional support was provided from the University of Wisconsin-Milwaukee’s Support For Undergraduate Research Fellowship(SURF),issued by UW-Milwaukee’s Office of Undergraduate Research.The authors of this paper would like to thank Prof.Gabriella Pinter,Prof.Erica Young and Prof.John Berges for their invaluable support.Finally,the authors would like recognize Google LLC for its publicly available image resource and street view API,without which this investigation would not have been possible.
文摘Measuring the amount of vegetation in a given area on a large scale has long been accomplished using satellite and aerial imaging systems.These methods have been very reliable in measuring vegetation coverage accurately at the top of the canopy,but their capabilities are limited when it comes to identifying green vegetation located beneath the canopy cover.Measuring the amount of urban and suburban vegetation along a street network that is partially beneath the canopy has recently been introduced with the use of Google Street View(GSV)images,made accessible by the Google Street View Image API.Analyzing green vegetation through the use of GSV images can provide a comprehensive representation of the amount of green vegetation found within geographical regions of higher population density,and it facilitates an analysis performed at the street-level.In this paper we propose a fine-tuned color based image filtering and segmentation technique and we use it to define and map an urban green environment index.We deployed this image processing method and,using GSV images as a high-resolution GIS data source,we computed and mapped the green index of Milwaukee County,a 3,082 km^(2) urban/suburban county in Wisconsin.This approach generates a high-resolution street-level vegetation estimate that may prove valuable in urban planning and management,as well as for researchers investigating the correlation between environmental factors and human health outcomes.
基金supported by the National Key Research and Development Program(No.2022YFD2001704).
文摘Simultaneous localization and mapping(SLAM)is one of the most attractive research hotspots in the field of robotics,and it is also a prerequisite for the autonomous navigation of robots.It can significantly improve the autonomous navigation ability of mobile robots and their adaptability to different application environments and contribute to the realization of real-time obstacle avoidance and dynamic path planning.Moreover,the application of SLAM technology has expanded from industrial production,intelligent transportation,special operations and other fields to agricultural environments,such as autonomous navigation,independent weeding,three-dimen-sional(3D)mapping,and independent harvesting.This paper mainly introduces the principle,sys-tem framework,latest development and application of SLAM technology,especially in agricultural environments.Firstly,the system framework and theory of the SLAM algorithm are introduced,and the SLAM algorithm is described in detail according to different sensor types.Then,the devel-opment and application of SLAM in the agricultural environment are summarized from two aspects:environment map construction,and localization and navigation of agricultural robots.Finally,the challenges and future research directions of SLAM in the agricultural environment are discussed.
基金supported by National Science Fund for Distinguished Young Scholars (No.61925102)Beijing University of Posts and TelecommunicationsChina Mobile Research Institute Joint Innovation Center。
文摘With the research of the upcoming sixth generation(6 G) systems, new technologies will require wider bandwidth, larger scale antenna arrays and more diverse wireless communication scenarios on the future channel modeling. Considering channel model is prerequisite for system design and performance evaluation of 6 G technologies, we face a challenging task: how to accurately and efficiently model 6 G channel for various scenarios? This paper tries to answer it. Firstly, the features of cluster-nuclei(CN) and principle of cluster-nuclei based channel model(CNCM) are introduced. Then, a novel modeling framework is proposed to implement CNCM,which consists four steps: propagation environment reconstruction, cluster-nuclei identification, multipath parameters generation, and channel coefficients generation. Three-dimensional environment with material information is utilized to map CN with scatterers in the propagation pathway. CN are identified by geometrical and electric field calculation based on environmental mapping, and multipath components within CN are calculated by statistical characteristics of angle, power and delay domains. Finally, we present a three-level verification structure to investigate the accuracy and complexity of channel modeling comprehensively. Simulation results reveal that CNCM can perform higher accuracy than geometrybased stochastic model while lower complexity compared with ray-tracing model for practical propagation environment.
文摘The present study performed on the Angovia, Kokumbo, Hire and Agbaou sites consisted of mapping the environmental risks linked to artisanal gold mining activities in C?te d’Ivoire. An inventory was done by observing the different phases of gold extraction and identifying the risks associated with these phases. Using a Geographic Information System (GIS), the representation of the spatial distribution of the pollution risks has been realized from indicator descriptives of the environmental sensitivity (i.e. slope, proximity to the watercourse, soil cover) and the transfer indicator (i.e. rainfall). The analysis of this map showed low sensitivity of mercury (Hg), arsenic (As), copper (Cu) and zinc (Zn) measured in the waters of the Hire and Agbaou localities, while moderate sensitivity in Kokumbo surface waters and high sensitivity for those of Angovia locality were observed. Moreover, analysis of Hg, As, Cu and Zn content spatial distribution maps in surface waters revealed that Hg and As come mainly from the artisanal mining activities for most localities. Among these metallic trace elements observed, only the Hg content was above the WHO Limit Values, 1994 (>0.001 mg·L-1). The continuous spread of metallic trace elements in surface water can pose serious health problems for people living around artisanal gold mining sites, hence the need to put in place a protection plan against contamination.
基金supported financially by the National Natural Science Foundation of China (91325301, 41571212 and 41137224)the Project of "One-Three-Five" Strategic Planning & Frontier Sciences of the Institute of Soil Science, Chinese Academy of Sciences (ISSASIP1622)the National Key Basic Research Special Foundation of China (2012FY112100)
文摘Environmental covariates are the basis of predictive soil mapping.Their selection determines the performance of soil mapping to a great extent,especially in cases where the number of soil samples is limited but soil spatial heterogeneity is high.In this study,we proposed an integrated method to select environmental covariates for predictive soil depth mapping.First,candidate variables that may influence the development of soil depth were selected based on pedogenetic knowledge.Second,three conventional methods(Pearson correlation analysis(PsCA),generalized additive models(GAMs),and Random Forest(RF))were used to generate optimal combinations of environmental covariates.Finally,three optimal combinations were integrated to produce a final combination based on the importance and occurrence frequency of each environmental covariate.We tested this method for soil depth mapping in the upper reaches of the Heihe River Basin in Northwest China.A total of 129 soil sampling sites were collected using a representative sampling strategy,and RF and support vector machine(SVM)models were used to map soil depth.The results showed that compared to the set of environmental covariates selected by the three conventional selection methods,the set of environmental covariates selected by the proposed method achieved higher mapping accuracy.The combination from the proposed method obtained a root mean square error(RMSE)of 11.88 cm,which was 2.25–7.64 cm lower than the other methods,and an R^2 value of 0.76,which was 0.08–0.26 higher than the other methods.The results suggest that our method can be used as an alternative to the conventional methods for soil depth mapping and may also be effective for mapping other soil properties.
基金Sponsored by General Project of Natural Science Foundation of Beijing City(8202017)。
文摘The development of modern cities has brought about tremendous changes in the climate environment.Faced with complex climate conditions,research on multi-scale climate change in cities is of great significance.The urban environmental climate maps and the application of climate atlas tool in Stuttgart,Germany were studied,and the multi-scale application of urban environmental climate maps in Stuttgart,Germany was summarized through the analysis of the pre-planning,current construction situation,and landscape reconstruction of the German"Stuttgart 21"plan case.Besides,other important measures to cope with climate change in German were proposed,and finally multi-scale practical strategies to cope with urban climate and environment were summarized to provide ideas and methods for improving China’s future urban climate environment.
基金Strategic Priority Research Program of the Chinese Academy of Sciences,No.XDA19040302The Key Research Program of the Chinese Academy of Sciences,No.KFZD-SW-111
文摘A model integrating geo-information and self-organizing map(SOM) for exploring the database of soil environmental surveys was established. The dataset of 5 heavy metals(As, Cd, Cr, Hg, and Pb) was built by the regular grid sampling in Hechi, Guangxi Zhuang Autonomous Region in southern China. Auxiliary datasets were collected throughout the study area to help interpret the potential causes of pollution. The main findings are as follows:(1) Soil samples of 5 elements exhibited strong variation and high skewness. High pollution risk existed in the case study area, especially Hg and Cd.(2) As and Pb had a similar topological distribution pattern, meaning they behaved similarly in the soil environment. Cr had behaviours in soil different from those of the other 4 elements.(3) From the U-matrix of SOM networks, 3 levels of SEQ were identified, and 11 high risk areas of soil heavy metal-contaminated were found throughout the study area, which were basically near rivers,factories, and ore zones.(4) The variations of contamination index(CI) followed the trend of construction land(1.353)> forestland(1.267)> cropland(1.175)> grassland(1.056), which suggest that decision makers should focus more on the problem of soil pollution surrounding industrial and mining enterprises and farmland.
文摘During emergency response to oil spills incident accurate information is required in order to reduce the risk associated with oil spill disasters. This study focuses on Environmental Sensitivity mapping for sustainable environmental clean-up and contingency planning along the 3.0 km of AGIP pipeline at Asemoku in Delta State, Nigeria. Geographic information systems (GIS) techniques were used to create an Environmental Sensitivity Index (ESI) map in the study area. A 2018 Google Earth Satellite imagery of the study area was downloaded, and landuse/cover classification scheme comprising of Vegetation, Farmland, Water Body, Wetland, built up area and Bare Surface was adopted. Existing categorization, ranking and classification of the inland habitat were adopted and used to create a Landuse/cover Environmental Sensitivity Index (ESI) map, while the buffer zones of 100 m, 200 m, 300 m and 400 m were adopted. In the ArcGIS 10.8 environment, the landuse/cover map was generated and buffer distances of 100 m, 200 m, 300 m and 400 m were created on the landuse/cover map to ascertain the features that are vulnerable and could be at risk in the event of oil spill. This study established that the Natural Vegetation areas are the most vulnerable and sensitive feature as a result of their size along the created buffer zones. Findings from this study thus provide insight into the most sensitive land-use/land-cover, in the event of a spill or emergency oil spill clean-up response.
文摘We have defined the environmental interface through the exchange processes between media forming this interface. Considering the environmental interface as a complex system we elaborated the advanced mathematical tools for its modelling. We have suggested two coupled maps serving the exchange processes on the environmental interfaces spatially ranged from cellular to planetary level, i.e. 1) the map with diffusive coupling for energy exchange simulation and 2) the map with affinity, which is suitable for matter exchange processes at the cellular level. We have performed the dynamical analysis of the coupled maps using the Lyapunov exponent, cross sample as well as the permutation entropy in dependence on different map parameters. Finally, we discussed the map with affinity, which shows some features making it a promising toll in simulation of exchange processes on the environmental interface at the cellular level.
文摘Giant Hogweed is a poisonous invasive weed in Latvia that poses significant threat to biodiversity and human health. Local residents are afraid and have very special concerns about the safety of their children because the plant causes phytophotodermatitis (severe burns), painful blistering, permanent scarring and blindness when the sap of the plant comes in contact with the human body and is exposed to sunlight. This study utilizes public participation GIS (PPGIS) involving Latvian high school students as data collectors to monitor the geographic distribution of Giant Hogweed in Northeast Latvia. This paper also explores challenges with implementing such a public program, how to maximize participation, and how participation impacts environmental awareness of participants. In this study we also assessed the accuracy of PPGIS-collected data and how the utilization of such data impacts mapping and monitoring of Giant Hogweed in the study area. Results indicate that this PPGIS program is effective in facilitating data collection for monitoring Giant Hogweed in Latvia. Tested methods of increasing participation have proven largely unsuccessful to date. Statistical analyses of survey responses indicate participation had a marked effect on sensitivity towards environmental issues. Accuracy assessments indicate that quality of point data collected by participants is sufficient for mapping and for use as ground verification.
基金Project supported by the National Natural Science Foundation of China (No. 60403044) and Microsoft Research Asia (PROJECT-2004-IMAGE-01)
文摘Environment matting and compositing is a technique to extract a foreground object, including color, opacity, reflec- tive and refractive properties, from a real-world scene, and synthesize new images by placing it into new environments. The description of the captured object is named environment matte. Recent matting and compositing techniques can produce quite realistic images for objects with complex optical properties. This paper presents an approximate method to transform the matte by simulating variation of the foreground object’s refractive index. Our algorithms can deal with achromatous-and-transparent ob- jects and the experimental results are visually acceptable. Our idea and method can be applied to produce some special video effects, which could be very useful in film making, compared with the extreme difficulty of physically changing an object’s refractive index.
文摘土壤有机碳(SOC)是陆地生态系统中最重要的碳库之一。在亚热带季风气候区,SOC的变化对碳循环具有重要影响。以江西省为研究区,根据SOC含量的影响因素和数据可获得性,选取37个特征变量,分别构建1987年和2011年0—100 cm土壤有机碳密度(SOCD)的空间外推模型,实现SOCD分布制图,分析土壤有机碳储量(TSOC)和土壤碳汇速率的特征。得出以下主要结论:(1)统计分析土壤样本检测的SOC含量表明,1987年至2011年间,江西省SOCD的均值从3.70 kg C/m^(2)增至12.52 kg C/m^(2)。其中,森林SOCD均值从4.37 kg C/m^(2)增至13.99 kg C/m^(2),农田SOCD均值从2.92 kg C/m^(2)增至5.94 kg C/m^(2);(2)随机森林(RF)模型在模拟2011年SOCD的空间分布中表现良好(R2=0.73,RMSE=6.22 kg C/m^(2)),受特征数据可获得性的影响,1987年SOCD的模拟精度较低;(3)根据空间外推结果,1987年至2011年间江西省土壤表现出巨大的碳汇潜力,平均SOCD从3.62 kg C/m^(2)增至11.57 kg C/m^(2),其中:森林的平均SOCD从4.13 kg C/m^(2)增至14.01 kg C/m^(2),农田的平均SOCD从2.89 kg C/m^(2)增至7.43 kg C/m^(2),草地的平均SOCD从2.98 kg C/m^(2)增至8.83 kg C/m^(2)。此外,TSOC从0.605 Pg C增至1.932 Pg C,碳汇速率依次为:森林>草地>农田。
