The sharing of geographical analysis models is of crucial importance for simulating geographic processes and phenomena in the current geographical information systems(e.g.Digital Earth),but there remain some issues th...The sharing of geographical analysis models is of crucial importance for simulating geographic processes and phenomena in the current geographical information systems(e.g.Digital Earth),but there remain some issues that have not been completely resolved.The challenges include,eliminating model heterogeneity and searching for suitable infrastructures to support the open sharing and effective execution of models.Taking advantage of cloud computing,this article aims to address the above issues and develop an open environment for geographical analysis model sharing.On the basis of the analysis of the applicability of cloud computing,the architecture of the open environment is proposed.More importantly,key strategies designed for heterogeneous model description,model encapsulating as well as model deploying and transparent accessing in the cloud are discussed in detail to establish such an environment.Finally,the prototype environment is implemented,and experiments were conducted to verify the environment’s feasibility to support the sharing of geographical analysis models.展开更多
Drug use （DU）, particularly injecting drug use （IDU） has been the main route of transmission and spread of Human Immunodeficiency Virus （HIV）/Acquired Immune Deficiency Syndrome （AIDSJ among injecting drug use...Drug use （DU）, particularly injecting drug use （IDU） has been the main route of transmission and spread of Human Immunodeficiency Virus （HIV）/Acquired Immune Deficiency Syndrome （AIDSJ among injecting drug users （IDUs）[1]. Previous studies have proven that needles or cottons sharing during drug injection were major risk factors for HIV/AIDS transmission at the personal level[z4]. Being a social behavioral issue, HIV/AIDS related risk factors should be far beyond the personal level. Therefore, studies on HIV/AIDS related risk factors should focus not only on the individual factors, but also on the association between HIV/AIDS cases and macroscopic-factors, such as economic status, transportation, health care services, etc[1]. The impact of the macroscopic-factors on HIV/AIDS status might be either positive or negative, which are potentially reflected in promoting, delaying or detecting HIV/AIDS epidemics.展开更多
Since the release of ChatGPT in late 2022,Generative Artificial Intelligence(GAI)has gained widespread attention because of its impressive capabilities in language comprehension,reasoning,and generation.GAI has been s...Since the release of ChatGPT in late 2022,Generative Artificial Intelligence(GAI)has gained widespread attention because of its impressive capabilities in language comprehension,reasoning,and generation.GAI has been successfully applied across various aspects(e.g.,creative writing,code generation,translation,and information retrieval).In cartography and GIS,researchers have employed GAI to handle some specific tasks,such as map generation,geographic question answering,and spatiotemporal data analysis,yielding a series of remarkable results.Although GAI-based techniques are developing rapidly,literature reviews of their applications in cartography and GIS remain relatively limited.This paper reviews recent GAI-related research in cartography and GIS,focusing on three aspects:①map generation,②geographical analysis,and③evaluation of GAI’s spatial cognition abilities.In addition,the paper analyzes current challenges and proposes future research directions.展开更多
The main purpose of this paper is to analyze the necessity of a Geographical Observatory of Atmospheric Pollution （GEOAP） in the Greek territory. The analysis performed is mainly focused on the benefits of the futur...The main purpose of this paper is to analyze the necessity of a Geographical Observatory of Atmospheric Pollution （GEOAP） in the Greek territory. The analysis performed is mainly focused on the benefits of the future function of the GEOAP to the environmental planning of the country and it could also provide an environmental management tool for the whole region. Measuring and mapping the pollution data and at the same time performing the geographical analysis of the complexity and the characteristics of natural and human environment can be useful tool in observation, management, and planning of the environmental policy of the country.展开更多
Mobile information and communication technologies(MICTs) have fully penetrated everyday life in smart societies;this has greatly compressed time, space, and distance, and consequently, reshaped residents’ travel beha...Mobile information and communication technologies(MICTs) have fully penetrated everyday life in smart societies;this has greatly compressed time, space, and distance, and consequently, reshaped residents’ travel behaviour patterns. As a new mode of shared mobility, the sharing bicycle offers a variety of options for the daily travel of urban residents. Extant studies have mainly examined the travel characteristics and influencing factors of public bicycles with piles, while the travel patterns for sharing bicycles and their driving mechanisms have been largely ignored. Using one week’s travel data for Mobike, this study investigated the spatial and temporal distribution patterns of sharing bicycle travel behaviours in the central urban area of Guangzhou, China;furthermore, it identified the influences of built environment density factors on sharing bicycle travel behaviours based on the geographically weighted regression method. Obvious morning and evening peaks were observed in the sharing bicycle travel patterns for both weekdays and weekends. The old urban area, which had a high degree of mixed function, dense road networks, and cycling-friendly built environments, was the main travel area that attracted sharing bicycles on both weekdays and weekends. Furthermore, factors including the point of interest(POI) for the density of public transport stations, the functional mixing degree, and the density of residential POIs significantly affected residents’ travel behaviours. These findings could enrich discourse regarding shared mobility with a Chinese case characterised by rapidly developing MICTs and also provide references to local authorities for improving slow traffic environments.展开更多
Objective To clarify the distribution of hepatitis A virus (HAV) genotype in geographical regions of China Methods Seventeen representative HAV strains were isolated from the stool or serum of hepatitis A patients...Objective To clarify the distribution of hepatitis A virus (HAV) genotype in geographical regions of China Methods Seventeen representative HAV strains were isolated from the stool or serum of hepatitis A patients in different geographical regions Viral RNA was recovered from stool or serum by proteinase K digestion and phenol chloroform extraction, followed by ethanol precipitation prior to reverse transcription and polymerase chain reaction (RT PCR) amplification The nucleotide sequences of VP1/2A junction region were tested by using a direct sequencing technique Results A pairwise comparison of sequences within 168 bases at the VP1/2A junction revealed that all the sequences clustered within genotype Ⅰ About 53% of strains clustered in genotype ⅠB, with less than 6% variability; while the others clustered in genotype ⅠA, with less than 5 3% variability Sequence homology between genotype ⅠA and ⅠB varied from 88 7% to 92 3% Conclusion Epidemic or sporadic HAV strains in China may belong to HAV genotype ⅠA or ⅠB Epidemiologically related strains may be identical or closely related in sequence展开更多
The paramo,plays an important role in our ecosystems as They balance the water resources and can retain substantial quantities of carbon.This research was carried out in the province of Tungurahua,specifically the Que...The paramo,plays an important role in our ecosystems as They balance the water resources and can retain substantial quantities of carbon.This research was carried out in the province of Tungurahua,specifically the Quero district.The aim is to develop a classification of the land use land cover(LULC)in the paramo using satellite imagery using several classifiers and determine which one obtains the best performance,for which three different approaches were applied:Pixel-Based Image Analysis(PBIA),Geographic Object-Based Image Analysis(GEOBIA),and a Deep Neural Network(DNN).Various parameters were used,such as the Normalized Difference Vegetation Index(NDVI),the Bare Soil Index(BSI),texture,altitude,and slope.Seven classes were used:paramo,pasture,crops,herbaceous vegetation,urban,shrubrainland,and forestry plantations.The data was obtained with the help of onsite technical experts,using geo-referencing and reference maps.Among the models used the highest-ranked was DNN with an overall precision of 87.43%,while for the paramo class specifically,GEOBIA reached a precision of 95%.展开更多
Citrus(Citrus reticulata),which is an important economic crop worldwide,is often managed in a labor-intensive and inefficient manner in developing countries,thereby necessitating more rapid and accurate alternatives t...Citrus(Citrus reticulata),which is an important economic crop worldwide,is often managed in a labor-intensive and inefficient manner in developing countries,thereby necessitating more rapid and accurate alternatives tofield surveys for improved crop management.In this study,we propose a novel method for individual tree segmentation from unmanned aerial vehicle remote sensing(RS)using a combination of geographic object-based image analysis(GEOBIA)and layer-adaptive Euclidean distance transformation-based watershed segmentation(LAEDT-WS).First,we use a GEOBIA support vector machine classifier that is optimized for features and parameters to identify the boundaries of citrus tree canopies accurately by generating mask images.Thereafter,our LAEDT workflow separates connected canopies and facilitates the accurate segmentation of individual canopies using WS.Our method exhibited an F1-score improvement of 10.75%compared to the traditional WS method based on the canopy height model.Furthermore,it achieved 0.01%and 1.38%higher F1-scores than the state-of-the-art deep learning detection networks YOLOX and YOLACT,respectively,on the test plot.Our method can be extended to detect larger-scale or more complex structured crops or economic plants by introducing morefinely detailed and transferable RS images,such as high-resolution or LiDAR-derived images,to improve the mask base map.展开更多
基金The work described in this article was supported by the Key Program of National Natural Science Foundation of China(Grant No.40730527)the National Natural Science Foundation of China(Grant No.41001223,Grant No.41101439)the open fund from the Guangdong Key Laboratory for Urbanization and Geo-simulation in Sun Yat-sen University.
文摘The sharing of geographical analysis models is of crucial importance for simulating geographic processes and phenomena in the current geographical information systems(e.g.Digital Earth),but there remain some issues that have not been completely resolved.The challenges include,eliminating model heterogeneity and searching for suitable infrastructures to support the open sharing and effective execution of models.Taking advantage of cloud computing,this article aims to address the above issues and develop an open environment for geographical analysis model sharing.On the basis of the analysis of the applicability of cloud computing,the architecture of the open environment is proposed.More importantly,key strategies designed for heterogeneous model description,model encapsulating as well as model deploying and transparent accessing in the cloud are discussed in detail to establish such an environment.Finally,the prototype environment is implemented,and experiments were conducted to verify the environment’s feasibility to support the sharing of geographical analysis models.
基金supported by the National Scientific Research Mega-Project under the 12th Five-Year Plan of China(2012ZX10001001)
文摘Drug use （DU）, particularly injecting drug use （IDU） has been the main route of transmission and spread of Human Immunodeficiency Virus （HIV）/Acquired Immune Deficiency Syndrome （AIDSJ among injecting drug users （IDUs）[1]. Previous studies have proven that needles or cottons sharing during drug injection were major risk factors for HIV/AIDS transmission at the personal level[z4]. Being a social behavioral issue, HIV/AIDS related risk factors should be far beyond the personal level. Therefore, studies on HIV/AIDS related risk factors should focus not only on the individual factors, but also on the association between HIV/AIDS cases and macroscopic-factors, such as economic status, transportation, health care services, etc[1]. The impact of the macroscopic-factors on HIV/AIDS status might be either positive or negative, which are potentially reflected in promoting, delaying or detecting HIV/AIDS epidemics.
基金National Natural Science Foundation of China(Nos.4210144242394063).
文摘Since the release of ChatGPT in late 2022,Generative Artificial Intelligence(GAI)has gained widespread attention because of its impressive capabilities in language comprehension,reasoning,and generation.GAI has been successfully applied across various aspects(e.g.,creative writing,code generation,translation,and information retrieval).In cartography and GIS,researchers have employed GAI to handle some specific tasks,such as map generation,geographic question answering,and spatiotemporal data analysis,yielding a series of remarkable results.Although GAI-based techniques are developing rapidly,literature reviews of their applications in cartography and GIS remain relatively limited.This paper reviews recent GAI-related research in cartography and GIS,focusing on three aspects:①map generation,②geographical analysis,and③evaluation of GAI’s spatial cognition abilities.In addition,the paper analyzes current challenges and proposes future research directions.
文摘The main purpose of this paper is to analyze the necessity of a Geographical Observatory of Atmospheric Pollution （GEOAP） in the Greek territory. The analysis performed is mainly focused on the benefits of the future function of the GEOAP to the environmental planning of the country and it could also provide an environmental management tool for the whole region. Measuring and mapping the pollution data and at the same time performing the geographical analysis of the complexity and the characteristics of natural and human environment can be useful tool in observation, management, and planning of the environmental policy of the country.
基金Under the auspices of National Natural Science Foundation of China(No.41801150,41571146,41801144)Natural Science Foundation of Guangdong Province(No.2018A030310392)+2 种基金Guangdong Planning Project of Philosophy and Social Science(No.GD17YGL01)Science and Technology Program of Guangzhou(No.201906010033)GDAS’(Guangdong Academy of Sciences)Project of Science and Technology Development(No.2020GDASYL-20200104007)。
文摘Mobile information and communication technologies(MICTs) have fully penetrated everyday life in smart societies;this has greatly compressed time, space, and distance, and consequently, reshaped residents’ travel behaviour patterns. As a new mode of shared mobility, the sharing bicycle offers a variety of options for the daily travel of urban residents. Extant studies have mainly examined the travel characteristics and influencing factors of public bicycles with piles, while the travel patterns for sharing bicycles and their driving mechanisms have been largely ignored. Using one week’s travel data for Mobike, this study investigated the spatial and temporal distribution patterns of sharing bicycle travel behaviours in the central urban area of Guangzhou, China;furthermore, it identified the influences of built environment density factors on sharing bicycle travel behaviours based on the geographically weighted regression method. Obvious morning and evening peaks were observed in the sharing bicycle travel patterns for both weekdays and weekends. The old urban area, which had a high degree of mixed function, dense road networks, and cycling-friendly built environments, was the main travel area that attracted sharing bicycles on both weekdays and weekends. Furthermore, factors including the point of interest(POI) for the density of public transport stations, the functional mixing degree, and the density of residential POIs significantly affected residents’ travel behaviours. These findings could enrich discourse regarding shared mobility with a Chinese case characterised by rapidly developing MICTs and also provide references to local authorities for improving slow traffic environments.
文摘Objective To clarify the distribution of hepatitis A virus (HAV) genotype in geographical regions of China Methods Seventeen representative HAV strains were isolated from the stool or serum of hepatitis A patients in different geographical regions Viral RNA was recovered from stool or serum by proteinase K digestion and phenol chloroform extraction, followed by ethanol precipitation prior to reverse transcription and polymerase chain reaction (RT PCR) amplification The nucleotide sequences of VP1/2A junction region were tested by using a direct sequencing technique Results A pairwise comparison of sequences within 168 bases at the VP1/2A junction revealed that all the sequences clustered within genotype Ⅰ About 53% of strains clustered in genotype ⅠB, with less than 6% variability; while the others clustered in genotype ⅠA, with less than 5 3% variability Sequence homology between genotype ⅠA and ⅠB varied from 88 7% to 92 3% Conclusion Epidemic or sporadic HAV strains in China may belong to HAV genotype ⅠA or ⅠB Epidemiologically related strains may be identical or closely related in sequence
基金funded by the EU ERDF and the Spanish Ministry of Economy and Competitiveness(MINECO)under AEI Project TIN2017-83964-Rthe Directorate-General for Research and Knowledge Transfer-Junta de Andalucia under Project UrbanITA P2000809.
文摘The paramo,plays an important role in our ecosystems as They balance the water resources and can retain substantial quantities of carbon.This research was carried out in the province of Tungurahua,specifically the Quero district.The aim is to develop a classification of the land use land cover(LULC)in the paramo using satellite imagery using several classifiers and determine which one obtains the best performance,for which three different approaches were applied:Pixel-Based Image Analysis(PBIA),Geographic Object-Based Image Analysis(GEOBIA),and a Deep Neural Network(DNN).Various parameters were used,such as the Normalized Difference Vegetation Index(NDVI),the Bare Soil Index(BSI),texture,altitude,and slope.Seven classes were used:paramo,pasture,crops,herbaceous vegetation,urban,shrubrainland,and forestry plantations.The data was obtained with the help of onsite technical experts,using geo-referencing and reference maps.Among the models used the highest-ranked was DNN with an overall precision of 87.43%,while for the paramo class specifically,GEOBIA reached a precision of 95%.
基金supported by the Forestry Peak Discipline Construction Project of Fujian Agriculture and Forestry University[grant number 72202200205]National Natural Science Foundation of China[grant number 31901298]+1 种基金the Natural Science Foundation of Fujian Province[grant number 2021J01059]Fujian Agriculture and Forestry University Innovation Foundation[grant number KFb22033XA].
文摘Citrus(Citrus reticulata),which is an important economic crop worldwide,is often managed in a labor-intensive and inefficient manner in developing countries,thereby necessitating more rapid and accurate alternatives tofield surveys for improved crop management.In this study,we propose a novel method for individual tree segmentation from unmanned aerial vehicle remote sensing(RS)using a combination of geographic object-based image analysis(GEOBIA)and layer-adaptive Euclidean distance transformation-based watershed segmentation(LAEDT-WS).First,we use a GEOBIA support vector machine classifier that is optimized for features and parameters to identify the boundaries of citrus tree canopies accurately by generating mask images.Thereafter,our LAEDT workflow separates connected canopies and facilitates the accurate segmentation of individual canopies using WS.Our method exhibited an F1-score improvement of 10.75%compared to the traditional WS method based on the canopy height model.Furthermore,it achieved 0.01%and 1.38%higher F1-scores than the state-of-the-art deep learning detection networks YOLOX and YOLACT,respectively,on the test plot.Our method can be extended to detect larger-scale or more complex structured crops or economic plants by introducing morefinely detailed and transferable RS images,such as high-resolution or LiDAR-derived images,to improve the mask base map.
