Tens of thousands of landslides were triggered by May 12, 2008 earthquake over a broad area. The main purpose of this article is to apply and verify earthquake-triggered landslide hazard analysis techniques by using w...Tens of thousands of landslides were triggered by May 12, 2008 earthquake over a broad area. The main purpose of this article is to apply and verify earthquake-triggered landslide hazard analysis techniques by using weight of evidence modeling in Qingshui （清水） River watershed, Deyang （德阳） City, Sichuan （四川） Province, China. Two thousand three hundred and twenty-one landslides were interpreted in the study area from aerial photographs and multi-source remote sensing imageries post-earthquake, verified by field surveys. The landslide inventory in the study area was established. A spatial database, including landslides and associated controlling parameters that may have influence on the occurrence of landslides, was constructed from topographic maps, geological maps, and enhanced thematic mapper （ETM＋） remote sensing imageries. The factors that influence landslide occurrence,such as slope angle, aspect, curvature, elevation, flow accumulation, distance from drainages, and distance from roads were calculated from the topographic maps. Lithology, distance from seismogenic fault, distance from all faults, and distance from stratigraphic boundaries were derived from the geological maps. Normalized difference vegetation index （NDV1） was extracted from ETM＋ images. Seismic intensity zoning was collected from Wenchuan （汶川） Ms8.0 Earthquake Intensity Distribution Map published by the China Earthquake Administration.Landslide hazard indices were calculated using the weight of evidence model, and landslide hazard maps were calculated from using different controlling parameters cases. The hazard map was compared with known landslide locations and verified. The success accuracy percentage of using all 13 controlling parameters was 71.82%. The resulting landslide hazard map showed five classes of landslide hazard, i.e., very high, high, moderate, low, and very low. The validation results showed satisfactory agreement between the hazard map and the existing landslides distribution data.展开更多
根据农田的实际操作要求,包括对数据采集的实时与移动等,设计开发了一套基于GIS的农田信息管理系统。系统以GIS技术为支撑,包括农田属性数据管理模块、农资操作管理模块、农事操作管理模块等。系统数据库采用Microsoft SQL Server 2005...根据农田的实际操作要求,包括对数据采集的实时与移动等,设计开发了一套基于GIS的农田信息管理系统。系统以GIS技术为支撑,包括农田属性数据管理模块、农资操作管理模块、农事操作管理模块等。系统数据库采用Microsoft SQL Server 2005,服务器端采用C#语言开发,移动客户端使用VS2005环境,浏览器端基于XHTML与JavaScript。在农田数据管理模块中,系统具有数据获取、数据导出、属性查询、数据统计分析、涂层编辑等功能。在商业通信运营商的支持下,操作员在田间利用智能手机或PDA使用系统获取田间数据或者田间作业相关信息,最后传送给系统服务器,管理人员可以在办公室进行远程操作。该系统可为具有科研、教学、生产等功能为主的试验田提供系统有效的服务。展开更多
This paper applies Yourdon's (1989) structured systems analysis techniques to transport planning, and the environmental analysis of transport plans. It is usual for planners to treat these activities as separate p...This paper applies Yourdon's (1989) structured systems analysis techniques to transport planning, and the environmental analysis of transport plans. It is usual for planners to treat these activities as separate processes or 'systems'. Six serious shortcomings are identified in prevailing approaches to accounting for the environmental impacts of transport plans. The application of systems analysis has elucidated opportunities for overcoming these problems by integrating the two processes. The paper highlights the benefits of using these methods to direct research into, and development of, an integrated transport planning- environmental analysis system. Techniques applied are data flow diagrams, a Venn diagram and an entity-relationship diagram. Significant potential exists for integration within a geographic information system(GIS), although adoption of integrated methods by transport planners is likely to be incremental. Research confirms the usefulness of systems analysis in guiding the development of a GIS application to accommodate integrated transport planning and environmental analysis. Systems analysis also facilitates more careful and effective design of the databases underlying GIS analysis.展开更多
The coronavirus disease 2019(COVID-19)and its mutant viruses are still wreaking global havoc over the last two years,but the impact of human activity on the transmission of the pandemic is difficult to ascertain.Estim...The coronavirus disease 2019(COVID-19)and its mutant viruses are still wreaking global havoc over the last two years,but the impact of human activity on the transmission of the pandemic is difficult to ascertain.Estimating human dynamic spatiotemporal distribution can help in our understanding of how to mitigate COVID-19 spread,which can help in maintaining urban health within a county and between counties within a country.This distribution can be computed using the Volunteered Geographic Information(VGI)of the citizens in conjunction with other variables,such as climatic conditions,and used to analyze how human’s daily density distribution quantitatively affects COVID-19 transmission.Based on the estimated population density,when the population density increases daily by 1 person/km^(2) in a county or prefectural-level administrative unit with an average size of 26,000 km^(2),the county would have an additional 3.6 confirmed cases and 0.054 death cases after 5 days,which is the illness onset time for a new COVID-19 case.After 14 days,which is the maximum incubation period of the COVID-19 virus,there would be 5 new confirmed cases and 0.092 death cases.However,in neighboring regions,there can be 0.96 fewer people infected with COVID-19 on average per day as a result of strong intervention of local and neighboring authorities.The primary innovation and contribution are that this is the first quantitative assessment of the impacts of dynamic population density on the COVID-19 pandemic.Additionally,the direct and indirect effects of the impact are estimated using spatial panel models.The models that control the unobserved factors improve the reliability of the estimation,as validated by random experiments and the use of the Baidu migration dataset.展开更多
Metropolitan cities in China are commonly confronted with unresolved traffic congestion issues, primarily due to rapidly increasing traffic demand. Group disparity between commuting mode choice and its spatial distrib...Metropolitan cities in China are commonly confronted with unresolved traffic congestion issues, primarily due to rapidly increasing traffic demand. Group disparity between commuting mode choice and its spatial distribution on road networks has enabled us to examine the factors that give rise to the discrepancies and the fundamental spatial causes of traffic congestion. In recent years, mi- cro-perspective, individual, and behavior-based spatial analysis have mushroomed and been facilitated with effective tools such as tem- poral geographic information systems （T-GIS）. It is difficult to study the interrelations between transport and space on the basis of commuting mode choice since the mode choice data are invisible in a specific space such as a particular road network. Therefore, in the field of transport, the classical origin destination （OD） four-stage model （FSM） is usually employed to calculate data when studying commuting mode choice. Based on the relative principles of T-GIS and the platform of ArcGIS, this paper considers Guangzhou as a case study and develops a spatio-temporal tool to examine the daily activities of residents. Meanwhile, the traffic volume distribution in rush hours, which was analyzed according to commuting modes and how they were reflected in the road network, was scrutinized with data extracted from travel diaries. Moreover, efforts were made to explain the relationship between traffic demand and urban spatial structure. Based on the investigation, this research indicates that traffic volumes in divergent groups and on the road networks is driven by： l） the socio-economie characteristics of travelers; 2） a jobs-housing imbalance under suburbanization; 3） differences in the spatial supply of transport modes; 4） the remains of the Danwei （work unit） system and market development in China; and 5） the transition of urban spatial structure and other factors.展开更多
According to many previous studies,application of remote sensing for the complex and heterogeneous urban environments in Sub-Saharan African countries is challenging due to the spectral confusion among features caused...According to many previous studies,application of remote sensing for the complex and heterogeneous urban environments in Sub-Saharan African countries is challenging due to the spectral confusion among features caused by diversity of construction materials.Resorting to classification based on spectral indices that are expected to better highlight features of interest and to be prone to unsupervised classification,this study aims(1)to evaluate the effectiveness of index-based classification for Land Use Land Cover(LULC)using an unsupervised machine learning algorithm Product Quantized K-means(PQk-means);and(2)to monitor the urban expansion of Luanda,the capital city of Angola in a Logistic Regression Model(LRM).Comparison with state-of-the-art algorithms shows that unsupervised classification by means of spectral indices is effective for the study area and can be used for further studies.The built-up area of Luanda has increased from 94.5 km2 in 2000 to 198.3 km2 in 2008 and to 468.4 km2 in 2018,mainly driven by the proximity to the already established residential areas and to the main roads as confirmed by the logistic regression analysis.The generated probability maps show high probability of urban growth in the areas where government had defined housing programs.展开更多
Spatio-temporal patterns of flowering in forest ecosystems are hard to quantify and monitor. The objectives of this study were to investigate spatio-temporal patterns（e.g. soilssimple slope classesslope aspectand flo...Spatio-temporal patterns of flowering in forest ecosystems are hard to quantify and monitor. The objectives of this study were to investigate spatio-temporal patterns（e.g. soilssimple slope classesslope aspectand flow accumulation） of flowering around Lake IssaqueenaSouth Carolina（SCUSA） using plant-flowering database collected with GPS- enabled camera（stored in Picasa 3 web albums and project website） on a monthly basis in 2012 and Li DAR-based topography. Pacolet fine sandy loam had the most flowering plantsfollowed by Madison sandy loamboth dominant soil types around the lake. Most flowering plants were on moderately steep（17%–30%） and gently sloping（4%–8%） slopes. Most flowering plants were on west（247.5°–292.5°）southwest（202.5°–247.5°）and northwest（292.5°–337.5°） aspects. Most flowering plants were associated with minimum and maximum flows within the landscape. Chi-square tests indicated differences in the distributions of the proportions of flowering plants were significant by soil typeslopeaspectand flow accumulation for each month（February-November）for all months（overall）and across months. The Chi-square test on area-normalized data indicated significant differences for all months and individual differences by each month with some months not statistically significant. Cluster analysis on flowering counts for nine plant families with the most flowering counts indicated no unique separation by clusterbut implied that the majority of these families were flowering on strongly sloping（9%–16%） slopeson southwest（202.5°–247.5°） aspectsand low flow accumulation（0–200）. Presented methodology can serve as a template for future efforts to quantify spatio-temporal patterns of flowering and other phenological events.展开更多
The primary objective of this paper was to identify flood-prone areas in Southeast of Louisiana to help decision-makers to develop appropriate adaptation strategies and flood prediction, and mitigation of the effects ...The primary objective of this paper was to identify flood-prone areas in Southeast of Louisiana to help decision-makers to develop appropriate adaptation strategies and flood prediction, and mitigation of the effects on the community. In doing so, the paper uses satellite remote sensing and Geographic Information System (GIS) data for this purpose. Elevation data was obtained from the National Elevation Dataset (NED) produced by the United States Geological Survey (USGS) seamless data warehouse. Satellite data was also acquired from USGS Earth explorer website. Topographical information on runoff characteristics such as slope, aspect and the digital elevation model was generated. Grid interpolation TIN (triangulated irregular network) was carried from the digital elevation model (DEM) to create slope map. Image Drape was performed using ERDAS IMAGINE Virtual GIS. The output image was then draped over the NED elevation data for visualization purposes with vertical exaggeration of 16 feet. Results of the study revealed that majority of the study area lies in low-lying and very low-lying terrain below sea level. Policy recommendation in the form of the need to design and build a comprehensive Regional Information Systems (RIS) in the form of periodic inventorying, monitoring and evaluation with full support of the governments was made for the study area.展开更多
Average credit scores for people in the United States （US） differ from state to state. Some states have high, and some states have low average credit scores. Since lenders and employers use credit scores to make loa...Average credit scores for people in the United States （US） differ from state to state. Some states have high, and some states have low average credit scores. Since lenders and employers use credit scores to make loan and employment decisions, people living in states where average credit scores are high should experience the benefits of living where credit scores tend to allow more favorable loan and employment decisions. Although credit scores are the direct result of credit histories, credit histories may be impacted by demographic factors. If the demographic factors that impact credit histories are identified, ways to improve credit scores are likely to be discovered and available to people and state government policymakers. This study looks for demographic factors to indirectly explain the average credit scores for people living in each state of the US. The methodology includes statistical analyses and geographic information systems （GIS） mapping. Statistical analyses provide evidence to suggest that state average credit scores are explained by the demographic factors of education, family, income, and health. GIS mapping reveals clusters of states with similar demographics and credit scores.展开更多
Since the introduction of geographic information systems(GIS)in the 1960s,it has evolved tremendously to an extent that it permeates our daily lives.Initially,GIS usage started in the developed countries and now incre...Since the introduction of geographic information systems(GIS)in the 1960s,it has evolved tremendously to an extent that it permeates our daily lives.Initially,GIS usage started in the developed countries and now increasingly filtered to developing countries.The town planning profession was one of the early adopters of GIS.Geospatial information is a useful source of data that is needed in urban planning.In these days of the New Urban Agenda 2030,smart cities are even more required from planners in using geospatial information to face urban challenges such as sustainable urban development and climate change.Although GIS has promised a lot for urban planning,it has not reached its full potential.Moreover,many studies have focused on developed countries with limited studies on geospatial information application in municipalities and GIS education from a perspective of developing countries.In this study,a survey on the usage of geospatial information science(GSIS)in two cities,namely Bulawayo in Zimbabwe and Ekurhuleni in South Africa,was conducted,and an overview of the state of GIS curricula in planning schools is discussed.The results indicate that considerable progress has been made in the application of geospatial information in municipal planning;however,there are impediments limiting the full utilization of geospatial information in local municipalities.These impediments include:inadequate GIS curricula in planning schools,lack of resources,and lack of political will.These challenges manifest differently in well-resourced municipalities and those with limited resources.The study proposes planning-relevant GIS curricula to improve the level of GIS use in planning practice.展开更多
This study considers the regional characteristics of the Tohoku region and the extent of the damage caused by the Great East Japan Earthquake and makes proposals for recovery and reconstruction of the areas affected b...This study considers the regional characteristics of the Tohoku region and the extent of the damage caused by the Great East Japan Earthquake and makes proposals for recovery and reconstruction of the areas affected by this disaster as well as for a reduction of the impact of natural disasters that may occur in the future with GIS （geographic information systems） as a social infrastructure positioned at the heart of the information infrastructure. Due to the fact that social media that used ICT （information and communication technology） was useful in the days directly after the disaster, it can be said that it is necessary to investigate the provision of an information infrastructure that uses ICT to reduce the impact of disasters. Therefore, this study proposes the construction of a geographical information database using GIS and the provision and sharing of information using social media GIS after discussion of the relationship between the development of the computerization of Japan and GIS as a valid example of using information systems for recovery and reconstruction after the Great East Japan Earthquake.展开更多
The aim of this study was to determine how well the landslide susceptibility parameters,obtained by data-dependent statistical models,matched with the parameters used in the literature.In order to achieve this goal,20...The aim of this study was to determine how well the landslide susceptibility parameters,obtained by data-dependent statistical models,matched with the parameters used in the literature.In order to achieve this goal,20 different environmental parameters were mapped in a well-studied landslide-prone area,the Asarsuyu catchment in northwest Turkey.A total of 4400 seed cells were generated from 47 different landslides and merged with different attributes of 20 different environmental causative variables into a database.In order to run a series of logistic regression models,different random landslide-free sample sets were produced and combined with seed cells.Different susceptibility maps were created with an average success rate of nearly 80%.The coherence among the models showed spatial correlations greater than 90%.Models converged in the parameter selection peculiarly,in that the same nine of 20 were chosen by different logistic regression models.Among these nine parameters,lithology,geological structure(distance/density),landcover-landuse,and slope angle were common parameters selected by both the regression models and literature.Accuracy assessment of the logistic models was assessed by absolute methods.All models were field checked with the landslides resulting from the 12 November 1999,Kaynas¸li Earthquake(Ms7.2).展开更多
基金supported by the International Scientific Joint Project of China (No. 2009DFA21280)the National Natural Science Foundation of China (No. 40821160550)the Doctoral Candidate Innovation Research Support Program by Science & Technology Review (No. kjdb200902-5)
文摘Tens of thousands of landslides were triggered by May 12, 2008 earthquake over a broad area. The main purpose of this article is to apply and verify earthquake-triggered landslide hazard analysis techniques by using weight of evidence modeling in Qingshui （清水） River watershed, Deyang （德阳） City, Sichuan （四川） Province, China. Two thousand three hundred and twenty-one landslides were interpreted in the study area from aerial photographs and multi-source remote sensing imageries post-earthquake, verified by field surveys. The landslide inventory in the study area was established. A spatial database, including landslides and associated controlling parameters that may have influence on the occurrence of landslides, was constructed from topographic maps, geological maps, and enhanced thematic mapper （ETM＋） remote sensing imageries. The factors that influence landslide occurrence,such as slope angle, aspect, curvature, elevation, flow accumulation, distance from drainages, and distance from roads were calculated from the topographic maps. Lithology, distance from seismogenic fault, distance from all faults, and distance from stratigraphic boundaries were derived from the geological maps. Normalized difference vegetation index （NDV1） was extracted from ETM＋ images. Seismic intensity zoning was collected from Wenchuan （汶川） Ms8.0 Earthquake Intensity Distribution Map published by the China Earthquake Administration.Landslide hazard indices were calculated using the weight of evidence model, and landslide hazard maps were calculated from using different controlling parameters cases. The hazard map was compared with known landslide locations and verified. The success accuracy percentage of using all 13 controlling parameters was 71.82%. The resulting landslide hazard map showed five classes of landslide hazard, i.e., very high, high, moderate, low, and very low. The validation results showed satisfactory agreement between the hazard map and the existing landslides distribution data.
文摘根据农田的实际操作要求,包括对数据采集的实时与移动等,设计开发了一套基于GIS的农田信息管理系统。系统以GIS技术为支撑,包括农田属性数据管理模块、农资操作管理模块、农事操作管理模块等。系统数据库采用Microsoft SQL Server 2005,服务器端采用C#语言开发,移动客户端使用VS2005环境,浏览器端基于XHTML与JavaScript。在农田数据管理模块中,系统具有数据获取、数据导出、属性查询、数据统计分析、涂层编辑等功能。在商业通信运营商的支持下,操作员在田间利用智能手机或PDA使用系统获取田间数据或者田间作业相关信息,最后传送给系统服务器,管理人员可以在办公室进行远程操作。该系统可为具有科研、教学、生产等功能为主的试验田提供系统有效的服务。
文摘This paper applies Yourdon's (1989) structured systems analysis techniques to transport planning, and the environmental analysis of transport plans. It is usual for planners to treat these activities as separate processes or 'systems'. Six serious shortcomings are identified in prevailing approaches to accounting for the environmental impacts of transport plans. The application of systems analysis has elucidated opportunities for overcoming these problems by integrating the two processes. The paper highlights the benefits of using these methods to direct research into, and development of, an integrated transport planning- environmental analysis system. Techniques applied are data flow diagrams, a Venn diagram and an entity-relationship diagram. Significant potential exists for integration within a geographic information system(GIS), although adoption of integrated methods by transport planners is likely to be incremental. Research confirms the usefulness of systems analysis in guiding the development of a GIS application to accommodate integrated transport planning and environmental analysis. Systems analysis also facilitates more careful and effective design of the databases underlying GIS analysis.
基金funding from the National Science and Technology Major Project of the Ministry of Science and Technology of China[grant number 2017YFB0503605]the National Natural Science Foundation of China[grant number 41771478]+3 种基金the Fundamental Research Funds for the Central Universities[grant number 2019B02514]Natural Science Foundation of Beijing,China[grant number 8172046]the China Scholarship Council(CSC)Queen Mary University of London.
文摘The coronavirus disease 2019(COVID-19)and its mutant viruses are still wreaking global havoc over the last two years,but the impact of human activity on the transmission of the pandemic is difficult to ascertain.Estimating human dynamic spatiotemporal distribution can help in our understanding of how to mitigate COVID-19 spread,which can help in maintaining urban health within a county and between counties within a country.This distribution can be computed using the Volunteered Geographic Information(VGI)of the citizens in conjunction with other variables,such as climatic conditions,and used to analyze how human’s daily density distribution quantitatively affects COVID-19 transmission.Based on the estimated population density,when the population density increases daily by 1 person/km^(2) in a county or prefectural-level administrative unit with an average size of 26,000 km^(2),the county would have an additional 3.6 confirmed cases and 0.054 death cases after 5 days,which is the illness onset time for a new COVID-19 case.After 14 days,which is the maximum incubation period of the COVID-19 virus,there would be 5 new confirmed cases and 0.092 death cases.However,in neighboring regions,there can be 0.96 fewer people infected with COVID-19 on average per day as a result of strong intervention of local and neighboring authorities.The primary innovation and contribution are that this is the first quantitative assessment of the impacts of dynamic population density on the COVID-19 pandemic.Additionally,the direct and indirect effects of the impact are estimated using spatial panel models.The models that control the unobserved factors improve the reliability of the estimation,as validated by random experiments and the use of the Baidu migration dataset.
基金Under the auspices of National Natural Science Foundation of China(No.40971098)National High Technology Research and Development Program of China(No.2012AA121402)
文摘Metropolitan cities in China are commonly confronted with unresolved traffic congestion issues, primarily due to rapidly increasing traffic demand. Group disparity between commuting mode choice and its spatial distribution on road networks has enabled us to examine the factors that give rise to the discrepancies and the fundamental spatial causes of traffic congestion. In recent years, mi- cro-perspective, individual, and behavior-based spatial analysis have mushroomed and been facilitated with effective tools such as tem- poral geographic information systems （T-GIS）. It is difficult to study the interrelations between transport and space on the basis of commuting mode choice since the mode choice data are invisible in a specific space such as a particular road network. Therefore, in the field of transport, the classical origin destination （OD） four-stage model （FSM） is usually employed to calculate data when studying commuting mode choice. Based on the relative principles of T-GIS and the platform of ArcGIS, this paper considers Guangzhou as a case study and develops a spatio-temporal tool to examine the daily activities of residents. Meanwhile, the traffic volume distribution in rush hours, which was analyzed according to commuting modes and how they were reflected in the road network, was scrutinized with data extracted from travel diaries. Moreover, efforts were made to explain the relationship between traffic demand and urban spatial structure. Based on the investigation, this research indicates that traffic volumes in divergent groups and on the road networks is driven by： l） the socio-economie characteristics of travelers; 2） a jobs-housing imbalance under suburbanization; 3） differences in the spatial supply of transport modes; 4） the remains of the Danwei （work unit） system and market development in China; and 5） the transition of urban spatial structure and other factors.
基金supported by the Japanese Government:Ministry of Science,Education,Sport and Technology“Mombukagakusho”a.k.a MEXT as part of a scholarship programthe APC was supported by the Open research fund program of LIESMARS,Wuhan University.
文摘According to many previous studies,application of remote sensing for the complex and heterogeneous urban environments in Sub-Saharan African countries is challenging due to the spectral confusion among features caused by diversity of construction materials.Resorting to classification based on spectral indices that are expected to better highlight features of interest and to be prone to unsupervised classification,this study aims(1)to evaluate the effectiveness of index-based classification for Land Use Land Cover(LULC)using an unsupervised machine learning algorithm Product Quantized K-means(PQk-means);and(2)to monitor the urban expansion of Luanda,the capital city of Angola in a Logistic Regression Model(LRM).Comparison with state-of-the-art algorithms shows that unsupervised classification by means of spectral indices is effective for the study area and can be used for further studies.The built-up area of Luanda has increased from 94.5 km2 in 2000 to 198.3 km2 in 2008 and to 468.4 km2 in 2018,mainly driven by the proximity to the already established residential areas and to the main roads as confirmed by the logistic regression analysis.The generated probability maps show high probability of urban growth in the areas where government had defined housing programs.
基金funding from Clemson University.This is technical contribution No.6345 of the Clemson University Experiment Stationsupported by NIFA/USDA,under project number SC-1700452
文摘Spatio-temporal patterns of flowering in forest ecosystems are hard to quantify and monitor. The objectives of this study were to investigate spatio-temporal patterns（e.g. soilssimple slope classesslope aspectand flow accumulation） of flowering around Lake IssaqueenaSouth Carolina（SCUSA） using plant-flowering database collected with GPS- enabled camera（stored in Picasa 3 web albums and project website） on a monthly basis in 2012 and Li DAR-based topography. Pacolet fine sandy loam had the most flowering plantsfollowed by Madison sandy loamboth dominant soil types around the lake. Most flowering plants were on moderately steep（17%–30%） and gently sloping（4%–8%） slopes. Most flowering plants were on west（247.5°–292.5°）southwest（202.5°–247.5°）and northwest（292.5°–337.5°） aspects. Most flowering plants were associated with minimum and maximum flows within the landscape. Chi-square tests indicated differences in the distributions of the proportions of flowering plants were significant by soil typeslopeaspectand flow accumulation for each month（February-November）for all months（overall）and across months. The Chi-square test on area-normalized data indicated significant differences for all months and individual differences by each month with some months not statistically significant. Cluster analysis on flowering counts for nine plant families with the most flowering counts indicated no unique separation by clusterbut implied that the majority of these families were flowering on strongly sloping（9%–16%） slopeson southwest（202.5°–247.5°） aspectsand low flow accumulation（0–200）. Presented methodology can serve as a template for future efforts to quantify spatio-temporal patterns of flowering and other phenological events.
文摘The primary objective of this paper was to identify flood-prone areas in Southeast of Louisiana to help decision-makers to develop appropriate adaptation strategies and flood prediction, and mitigation of the effects on the community. In doing so, the paper uses satellite remote sensing and Geographic Information System (GIS) data for this purpose. Elevation data was obtained from the National Elevation Dataset (NED) produced by the United States Geological Survey (USGS) seamless data warehouse. Satellite data was also acquired from USGS Earth explorer website. Topographical information on runoff characteristics such as slope, aspect and the digital elevation model was generated. Grid interpolation TIN (triangulated irregular network) was carried from the digital elevation model (DEM) to create slope map. Image Drape was performed using ERDAS IMAGINE Virtual GIS. The output image was then draped over the NED elevation data for visualization purposes with vertical exaggeration of 16 feet. Results of the study revealed that majority of the study area lies in low-lying and very low-lying terrain below sea level. Policy recommendation in the form of the need to design and build a comprehensive Regional Information Systems (RIS) in the form of periodic inventorying, monitoring and evaluation with full support of the governments was made for the study area.
文摘Average credit scores for people in the United States （US） differ from state to state. Some states have high, and some states have low average credit scores. Since lenders and employers use credit scores to make loan and employment decisions, people living in states where average credit scores are high should experience the benefits of living where credit scores tend to allow more favorable loan and employment decisions. Although credit scores are the direct result of credit histories, credit histories may be impacted by demographic factors. If the demographic factors that impact credit histories are identified, ways to improve credit scores are likely to be discovered and available to people and state government policymakers. This study looks for demographic factors to indirectly explain the average credit scores for people living in each state of the US. The methodology includes statistical analyses and geographic information systems （GIS） mapping. Statistical analyses provide evidence to suggest that state average credit scores are explained by the demographic factors of education, family, income, and health. GIS mapping reveals clusters of states with similar demographics and credit scores.
文摘Since the introduction of geographic information systems(GIS)in the 1960s,it has evolved tremendously to an extent that it permeates our daily lives.Initially,GIS usage started in the developed countries and now increasingly filtered to developing countries.The town planning profession was one of the early adopters of GIS.Geospatial information is a useful source of data that is needed in urban planning.In these days of the New Urban Agenda 2030,smart cities are even more required from planners in using geospatial information to face urban challenges such as sustainable urban development and climate change.Although GIS has promised a lot for urban planning,it has not reached its full potential.Moreover,many studies have focused on developed countries with limited studies on geospatial information application in municipalities and GIS education from a perspective of developing countries.In this study,a survey on the usage of geospatial information science(GSIS)in two cities,namely Bulawayo in Zimbabwe and Ekurhuleni in South Africa,was conducted,and an overview of the state of GIS curricula in planning schools is discussed.The results indicate that considerable progress has been made in the application of geospatial information in municipal planning;however,there are impediments limiting the full utilization of geospatial information in local municipalities.These impediments include:inadequate GIS curricula in planning schools,lack of resources,and lack of political will.These challenges manifest differently in well-resourced municipalities and those with limited resources.The study proposes planning-relevant GIS curricula to improve the level of GIS use in planning practice.
文摘This study considers the regional characteristics of the Tohoku region and the extent of the damage caused by the Great East Japan Earthquake and makes proposals for recovery and reconstruction of the areas affected by this disaster as well as for a reduction of the impact of natural disasters that may occur in the future with GIS （geographic information systems） as a social infrastructure positioned at the heart of the information infrastructure. Due to the fact that social media that used ICT （information and communication technology） was useful in the days directly after the disaster, it can be said that it is necessary to investigate the provision of an information infrastructure that uses ICT to reduce the impact of disasters. Therefore, this study proposes the construction of a geographical information database using GIS and the provision and sharing of information using social media GIS after discussion of the relationship between the development of the computerization of Japan and GIS as a valid example of using information systems for recovery and reconstruction after the Great East Japan Earthquake.
文摘The aim of this study was to determine how well the landslide susceptibility parameters,obtained by data-dependent statistical models,matched with the parameters used in the literature.In order to achieve this goal,20 different environmental parameters were mapped in a well-studied landslide-prone area,the Asarsuyu catchment in northwest Turkey.A total of 4400 seed cells were generated from 47 different landslides and merged with different attributes of 20 different environmental causative variables into a database.In order to run a series of logistic regression models,different random landslide-free sample sets were produced and combined with seed cells.Different susceptibility maps were created with an average success rate of nearly 80%.The coherence among the models showed spatial correlations greater than 90%.Models converged in the parameter selection peculiarly,in that the same nine of 20 were chosen by different logistic regression models.Among these nine parameters,lithology,geological structure(distance/density),landcover-landuse,and slope angle were common parameters selected by both the regression models and literature.Accuracy assessment of the logistic models was assessed by absolute methods.All models were field checked with the landslides resulting from the 12 November 1999,Kaynas¸li Earthquake(Ms7.2).
