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This study identified the spatial and temporal patterns of national park visitors by combining global positioning system (GPS) technologies and surveys using the sequence alignment method (SAM) based on the concept of space–time path of time geography. Data were collected from a sample of 344 GPS tracks and questionnaires obtained from Gyeryongsan National Park in South Korea. A complex random stratified sampling method was employed to represent a national sample based on mobile positioning data. The result of the SAM analysis revealed that the derived visitor typologies constituted three groups from 83 unique paths extracted from 341 sequences. Significant intergroup differences were found for the paths based on average travel distance, average visit duration, and average travel speed. The main theoretical contribution of this study is in expanding the application of the theory by providing methodological improvements using SAM and GPS analysis of the theoretical basis of time geography.

Hydrological droughts are important for agriculture and other human activities such as navigation and groundwater pumping, so it is necessary to understand their characteristics at various temporal...

Today, unpredictable damage can result from extreme weather such as heat waves and floods. This damage makes communities that cannot respond quickly to disasters more vulnerable than cities. Thus, people living in such communities can easily become isolated, which can cause unavoidable loss of life or property. In the meantime, many disaster management studies have been conducted, but studies on effective disaster response for areas surrounded by mountains or with weak transportation infrastructure are very rare. To fill the gap, this research aimed at developing an automated analysis tool that can be directly used for disaster response and recovery by identifying in real time the communities at risk of isolation using a web-based geographic information system (GIS) application. We first developed an algorithm to automatically detect communities at risk of isolation due to disaster. Next, we developed an analytics module to identify buildings and populations within the communities and efficiently place at-risk residents in shelters. In sum, the analysis tool developed in this study can be used to support disaster response decisions regarding, for example, rescue activities and supply of materials by accurately detecting isolated areas when a disaster occurs in a mountainous area where communication and transportation infrastructure is lacking.

Largely due to data unavailability, the spatial pattern of urban growth in North Korea has been rarely studied. This study explored urban changes in North Korea and provided their plausible causes. The present study used satellite‐based land cover data sets produced by the government of South Korea to examine the extent and distribution of urban land cover in North Korea between the late 1980s (1987–1989) and late 2000s (2008–2010) at the municipal level. The urban expansion intensity index (UEII) was calculated for two 10‐year intervals, and the spatial autocorrelation of UEII values was examined. Major findings from the study are summarized as follows: (a) the capital city Pyongyang's dominance continued without any obvious sign of slowing down, (b) economic development districts do not appear to have much influence on urban land cover changes, and (c) the extent of urban land cover slightly decreased in much of the country between the late 1990s (1997–1999) and late 2000s (2008–2010). The results and discussion in this study suggest internal migration and stagnant economy as probably important causes for the phenomena.

This paper aimed to suggest a method to evaluate the quality of spatial data in order to increase the interoperability of national geospatial data. The national geospatial data is managed by the government and is provided to the public according to the Spatial Data Industry Promotion Act. Although the quality control is necessary in the every processing steps including data production, processing, distribution, and service. This paper focused data quality only on the distribution stage. The evaluation rules suitable for national geospatial data were derived by comparing and analyzing domestic and foreign standards for data quality. Then, the quality diagnosis were carried out using commercial software. Two diagnostic methods were applied to test data quality. One is ‘Layer-based Approach’ that requires a comparison between two layers and the other is ‘Geometry-based Approach’ that diagnose feature geometries in a single layer. The diagnostic methods have been applied to the building and road layers in Seoul. In conclusion, this paper presented the standard quality evaluation rules and criteria that could be applied immediately for spatial data distribution industry, although some of items checked by direct visual inspection. Later, it is expected all quality evaluation rules are fully automated.

This study examined meteorological and streamflow droughts for the period from 1951 to 2006 using the Milwaukee River basin in Wisconsin as the study area in an effort to improve the understanding ...

Spatiotemporal characteristics and anthropogenic signals of aerosol optical thickness (AOT) distributions over Korea are investigated in this study using AOT time-series data from the Moderate Resolution Imaging Spectroradiometer (MODIS). AOT observations, a quantitative measure of the atmospheric quality, had significant geographical variations during the study period (2000–2010). Comparing metro cities or counties with similar populations, western regions showed higher AOT values than eastern regions. Particular matter with a diameter < 10 µm (PM10), including aeolian dust or yellow dust, is the primary component of atmospheric aerosols, and their transport into the region has shown a strong seasonal pattern with its peak from March to April and lows from July to September. These seasonal dust patterns, however, did not correspond well to temporal AOT records, which typically reached the maximum level in June nationwide. Rather, widespread regional fire events and humidity showed significant correlation...

There has been a significant lack of land cover change studies in relation to deforestation in the Democratic People’s Republic of Korea (North Korea). The purpose of this study is to characterize deforestation in North Korea through land cover change trajectory and spatial analysis. We used three 30-m gridded land cover data sets for North Korea representing the conditions of the late 1980s, 1990s, and 2000s, respectively, as well as a digital elevation model. We examined the land cover trajectories during the two decades, i.e., which land cover became which at the pixel level. In addition, we calculated topographic characteristics of deforested pixels. Major findings from the study are summarized as follows: (1) net forest loss in North Korea was negligible in the latter decade compared to the former (>5000 km2), whereas other land cover changes were still active; (2) as a result of deforestation, forest land cover became mostly agricultural, particularly in the latter decade (95 %); (3) expansion of agricultural land cover continued during the time, increasing by >42 %; and (4) elevation and slope of deforested areas decreased slightly in the latter decade. The key contribution of the study is that it has demonstrated which land cover became which at the 30-m pixel level, complementing existing studies that examined overall forest stock in North Korea.

In modern societies, considerable efforts have been devoted in building an effective land management model. In 2012, the Korea country profile of the Land Administration Domain Model (LADM) was proposed to the ISO/TC211. In 2014 ‘the special Cadastral Resurvey Act’ was announced. This law includes the representation of 3D partitioned superficies for buildings and underground facilities into the land information system. In this study, a 3D land administration model is proposed using a cadastral resurvey form, including the representation of 3D physical properties and 3D rights. The new 3D cadastre model can contain underground utility and superficies information to present the physical and legal information on both buildings and underground features. The shape of land units and terrain, and azimuth are also included as secondary information on features in this new model. Thus, the proposed 3D new version of the Korean country profile of the Land Administration Domain Model would be the next generation land administration model in Korea to represent all types of Cadastre information.

To understand the changing rainfall–runoff relationship, this study examined climate and streamflow data in the Milwaukee River Basin in southeastern Wisconsin, of which four catchments with different degrees of urbanization were selected for analysis. This study analyzed temperature, precipitation, and streamflow data with a range of statistical methods, including the Mann–Kendall test, double-mass technique, and quantile regression. Runoff ratios and extreme flow indexes were higher in more urbanized catchments. Catchments with long-term data (>forty years) showed significantly increasing runoff ratios and slopes in double-mass curves. Overall, there are signs of changes in the rainfall–runoff relationship, but how much they can be attributed to land use changes is uncertain.

Outdoor light at night (LAN) would be a public concern potentially associated with adverse health outcomes mainly in developed countries, but it might also be an environmental health issue in developing countries. However, there have been few studies reporting the spatial and temporal aspects of LAN level changes incorporated with population exposure in such nations. Therefore, we analyzed the spatiotemporal patterns of outdoor LAN exposure changes across the Republic of Korea (ROK), a developing country in Asia, between 1995 and 2010. In addition, we incorporated the population and its demographic characteristics of light exposure in this research. We utilized Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) observations as a spatial proxy of LAN and the ROK census data. This research observed 57.6% (≈57,800 km2) of land areas in the country to experience increases in outdoor artificial illumination at nights. The highest levels of LAN were found to affect about 58% of th...

Snowpack is an important source of freshwater. Snowmelt runoff models provide a means to predict the timing and magnitude of spring snowmelt. This study assessed the sensitivity of the conceptual, degree-day Snowmelt Runoff Model (SRM) to snow covered area and temperature inputs in a small mountainous catchment in Utah, USA. It was found that snow cover products from the Moderate Resolution Imaging Spectroradiometer (MODIS) underestimate snow covered area during the second half of the melt season, leading to inadequate modeling of spring snowmelt with SRM (Nash-Sutcliffe Efficiency = 0.59; bias of −26.9%). Incorporation of ancillary snow covered area information provided by Landsat ETM+ imagery greatly improved streamflow simulations (Nash-Sutcliffe Efficiency = 0.92; bias of −0.01%). For the temperature input, SRM appeared more sensitive to the elevation and location of the temperature reference station than to the lapse rate scenario used to extrapolate temperatures throughout the watershed. These findings will be useful for snowmelt runoff research and water resource management.

The amount and distribution of impervious surfaces are important input parameters of hydrological models, especially in highly urbanized basins. This study tests three different methods to input impervious surface area information to a semi-distributed hydrological model in order to examine their effects on storm flow. The three methods being evaluated include: (1) a constant value for impervious surfaces in the entire urban area, (2) constant values of imperviousness for commercial and residential land uses, respectively, and (3) different imperviousness for the residential land use in each subbasin. Storm flow of the Milwaukee River Basin in southeastern Wisconsin (USA) was modeled using the Hydrological Simulation Program—Fortran. The results show that the three methods resulted in substantially different amounts of storm flow. The storm flow simulated with the third method was the largest and had the largest variability between the subbasins. The differences between the scenarios are generally larger in subbasins with high percentage of urban land use types. The results suggest that the effect of different input methods is amplified in urbanized subbasins and the spatial variability of imperviousness should be commensurate with the spatial variability of the model configuration.

Orbital- and millennial-scale climate and vegetation changes between 32.5 and 6.9k cal a BP from Hanon Maar paleolake on Jeju Island, Korea, were demonstrated by high-resolution multi-proxy data (pollen, magnetic susceptibility, total organic carbon, carbon/nitrogen ratios and sediment grain size). High-resolution pollen records provided detailed information on the vegetation response to climate change. The Thalictrum pollen percentage, which corresponded to the magnetic susceptibility data, and the first principal component of principal-component analysis of pollen data were good indicators of the orbital- and millennial-scale dry/wet cycle in the study area. Hanon pollen and magnetic susceptibility records suggested that colder and drier conditions were prevalent between 25.2 and 17.6k cal a BP in the study area due to a precession-induced decrease in summer insolation. Hanon multi-proxy data were correlated with oxygen isotope records from Greenland and Hulu cave, suggesting the possible teleconnection of millennial-scale climate oscillations between North Atlantic and East Asian regions. According to our results, Heinrich-like cold events probably occurred around 31.1, 25.2 and 16.7k cal a BP, and the warm intervals observed around 30.7 and 29.9k cal a BP may have corresponded to Dansgaard–Oeschger warm events 4 and 3, respectively.

Travel is derived from activity participation. Details of activity participation are strongly affected by social settings and transportation system. Understanding the changes in travel behavior is essential to comprehending the association between travel behavior and the settings. The paper aims at analyzing the changes in travel behavior over the last 8 years using household travel survey data collected in Seoul Metropolitan Area (SMA) in 2002, 2006 and 2010, respectively. Changes of travel behavior were identified from the overall sample, and the detailed aspects of the changes were further investigated. The results show that the temporal and spatial characteristics of changes in travel behavior were interpretable regarding socio-economic/regional characteristics and travel characteristics. Implications of the results are discussed in the final section.

Large flood events in recent years in the state of Wisconsin, USA raised a question of whether high precipitation events are on the rise. The objective of the research was to examine temporal and spatial patterns of extreme precipitation in Wisconsin during 1950–2006. The daily precipitation data used in the study were created by researchers at the University of Wisconsin-Madison using spatial interpolation of weather stations data across the state to a grid mesh with a spatial resolution of 8 km. For extreme precipitation indices, we calculated 99th, 95th, 90th, 85th, and 80th percentiles of daily total precipitation (>1 mm) in a year and the number of days per year with daily precipitation exceeding 10 mm, 20 mm, and 50 mm. We also conducted the Mann–Kendall test for trend, examined how geographical heterogeneity varied over time, and built quantile regression models for annual summer precipitation. Main findings include the following: the temporal trend of extreme precipitation varied widely across the state; the highest percentile index showed an increasing trend over the largest area, whereas indices of less extreme precipitation tended to generally decrease; extreme precipitation tended to show more dispersed and skewed spatial patterns than annual total precipitation. Overall, indices related to frequency showed more similar spatial and temporal trends to total precipitation than magnitude indices.

There is growing interest in the role the food environment as well as demographic and socio-economic factors play in the prevalence of obesity in the US. Existing empirical evidence examining the association between the food environment and obesity risk, however, remains equivocal. We hypothesized that spatial heterogeneity may account for the conflicting results. Using Geographically Weighted Regression, we examined how the associations between the food environment, and demographic and socio-economic variables associated with obesity vary over space at the county level in the US. The analysis shows that higher ratios of convenience-to-grocery stores, poverty rate, and urban environments were positively associated with obesity risk in the US. Conversely, areas with better physical environments were negatively associated with obesity risk. Most importantly, the association between obesity and all major explanatory variables in our analysis significantly varied over space.

This study tried to show the usability of Asian air pollution emission data in order to improve a visibility modeling for the operation of numerical weather prediction models. For this purpose, the three most popular Asian air pollution emission data (TRACE-P, INTEX-B, REAS) were compared with domestic air pollution emission data by root mean square error. In this study, root mean square errors of air pollution materials including SOx, NOx, and VOC in Asia air pollution emission data were analyzed for 2001 and 2006. In the results, INTEX-B would be useful when the measurement data is required, while REAS would be acceptable if multi-year data were required and estimation data were allowed. Air pollutant diffusion model with Asian air pollution data can be used to estimate hourly air pollution concentration data by altitude, which would improve the accuracy of numerical weather prediction models.

We present pollen and sediment evidence for late-Holocene human impact from the Seonam-dong archeological site in Gwangju in southwest Korea. Due to the lack of undisturbed profiles with high sedimentation rates, the relationship between the environment and agricultural activities has not been properly investigated in Korea using a paleoenvironmental approach. This study shows possible climate-induced changes in chestnut production, which was contemporaneously recognized by the Chinese as an important and unique local food source in southwestern Korea. Our results also show that human adaptation to climate change may have resulted in both the degradation and recovery of the local forest ecosystem in the study area. The data from the Seonam-dong archeological site provided evidence supporting the following hypotheses. 1) Chestnut cultivation declined from 400 BC to AD 200 (2350–1750 cal BP), as herbaceous crop production may have sufficiently expanded to sustain the population, possibly due to agricultural improvements and/or climatic amelioration. 2) Chestnut cultivation was enhanced from AD 200 to AD 800 (1750–1150 cal BP), probably to compensate for decreased herbaceous crop yields due to climatic deterioration. 3) The increase in chestnut cultivation led to forest disturbance and increased flooding, with intermittent forest recovery during periods of decreased cultivation.

The term “Tornado Alley” is a gross approximation of the most tornado-prone region in the United States. Depending on calculation methods, Tornado Alley can vary dramatically across the area between the Rocky and Appalachian Mountains. There is some evidence that multiple alleys of peak tornado activity exist around the country, including “Dixie Alley” in the Southeast. Therefore, we assess the spatial tornado risk and seek any regions of elevated tornado risk that are distinctly separate from the traditional Tornado Alley of the Great Plains. Results show there are no tornado risk areas statistically separate from Tornado Alley, but there are large portions of the Southeast that experience more tornadoes than the rest of the country. It appears that Tornado Alley and Dixie Alley are part of a single large region of high tornado risk with a relative minimum near the middle due to the Ozark and Ouachita Mountains. Placement of the maximum tornado density in Mississippi, along with other regions of relative maxima across the Southeast, may warrant modification of the traditional tornado risk map that focuses only on the Great Plains. Understanding such patterns is important for preparing the public and mitigating tornado hazards.

Building design has a large impact on emergency evacuation. To identify the best location of doors in a room for fast evacuation, building egress times were computed using agent-based simulation. Human behavior in a building was based on a social force model. The evacuation route was based on the shortest path in a 3D geometric network in a GIS environment. Our results indicated that building egress time is minimized when doorways are located to make the egress path shortest. The integration of an agent-based model and 3D geometric network can be applied further to evaluate more complex structures such as multi-story buildings and subway stations.

This paper discusses a novel methodology for multi-scale rendering of geographic features depending upon changes in visual scale. The methodology consists of geometry collapse and a symbol knowledge base. Two collapse algorithms are implemented: polygon to point and polygon to line. In particular, we develop a partial collapse algorithm for linear features. A river is represented by lines and polygons depending on the width. To render features with scale changes, a symbol knowledge base is designed to specify scale ranges and symbols for each feature. Finally, a multi-scale rendering tool is developed and applied to the map of Camp Lejune, NC. The symbols in the knowledge base can be accumulated and adapted for various mapping applications.

In this study, we used image-processing techniques to examine the spatial pattern of land-use and land-cover (LULC) change that occurred in the coffee growing area in the Western Ghats of India during the international coffee crisis in the 1990s. The study also ascertains the driving forces of these changes using qualitative research methods that include archival studies and interviews of knowledgeable individuals. We analyzed Landsat Thematic Mapper (TM) for 1991 and Landsat ETM+ for 2002 to quantify LULC. Historical land-use changes in different land ownership regimes were also analyzed. Global coffee market fluctuations were found to be the major cause of landscape change in the study region. When the global coffee prices increased, more forested areas were cleared for coffee cultivation. Failure of global coffee market forced farmers to convert land from subsistence farming (rice) to short-period commercial crops like ginger. This also resulted in land degradation in rice paddies. For the farmers in the Western Ghats, LULC decisions are one of the methods used to cope with the vulnerability created due to the international coffee crisis. Copyright © 2009 John Wiley & Sons, Ltd.

Using a feature data model, geographic phenomena can be represented effectively by integrating space, theme, and time. This paper extends and implements a feature data model that supports query and visualization of geographic features using their non-spatial and temporal relationships. A prototype feature-oriented geographic information system (FOGIS) is then developed and storage of features named Feature Database is designed. Buildings from the U.S. Marine Corps Base, Camp Lejeune, North Carolina and subways in Chicago, Illinois are used to test the developed system. The results of the applications show the strength of the feature data model and the developed system 'FOGIS' when they utilize non-spatial and temporal relationships in order to retrieve and visualize individual features.

A water budget is important for environmental models such as a fire potential model. For the eastern United States, water budget indices derived from the cumulative interplay of precipitation and evaporation characterizes moisture condi- tions better than the Keech-Byram drought index. Because there are various sources of precipitation and evaporation data, it is difficult to manage those data consistently through time in order to derive cumulative water budget indices. In this study, we developed a water budget management system (WBMS) that downloads climate data and calculates a water budget. A geodatabase was designed to support the WBMS. Finally, the WBMS was tested for mapping fire potential in Mississippi.

We developed an ATL software component that calculates point-to-point distance with geographic latitude, longitude, and elevation. GEODIST3D was also developed with the ATL component to handle the PolylineZ shapefile format. GEODIST3D was applied to the Amazon and Nile rivers, as well as to the Seoul road network. Distance calculation results showed about a 4% increases in the Amazon and Nile rivers compared with ellipsoidal geodesic distances. Roughly a 0.2% increase was also found in the total length of the major roads in Seoul, South Korea. Survey professionals and GIS analysts will benefit from using the ATL component and GEODIST3D by calculating distance more accurately with digital geospatial features.

A feature relies on three dimensions (space, theme, and time) for its representation. Even though spatiotemporal models have been proposed, they have principally focused on the spatial changes of a feature. In this paper, a feature-based temporal model is proposed to represent the changes of both space and theme independently. The proposed model modifies the ISO's temporal schema and adds new explicit temporal relationship structure that stores temporal topological relationship with the ISO's temporal primitives of a feature in order to keep track feature history. The explicit temporal relationship can enhance query performance on feature history by removing topological comparison during query process. Further, a prototype system has been developed to test a proposed feature-based temporal model by querying land parcel history in Athens, Georgia. The result of temporal query on individual feature history shows the efficiency of the explicit temporal relationship structure.

A hybrid method that incorporates the advantages of supervised and unsupervised approaches as well as hard and soft classifications was proposed for mapping the land use/cover of the Atlanta metropolitan area using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data. The unsupervised ISODATA clustering method was initially used to segment the image into a large number of clusters of pixels. With reference to ground data based on 1 : 40 000 colour infrared aerial photographs in the form of Digital Orthophoto Quarter Quadrangle (DOQQ), homogeneous clusters were labelled. Clusters that could not be labelled because of mixed pixels were clipped out and subjected to a supervised fuzzy classification. A final land use/cover map was obtained by a union overlay of the two partial land use/cover maps. This map was evaluated by comparing with maps produced using unsupervised ISODATA clustering, supervised fuzzy and supervised maximum likelihood classification methods. It was found that the hybrid approach was sligh...

A rule-based expert system has been the most common artificial intelligence (AI) technique for system integration with geographic information systems (GIS) because of its simple rule structure. In this paper, a rule-based expert system is presented that uses an interactive question-and-answer sequence integrated with GIS for spatial data mapping. The integrated system consists of three main parts: expert, user, and map. Rules can be constructed easily in the expert part using English. Users can derive a solution to a specific problem from the rules in the user part through the interactive question-and-answer sequence. The solution can then be mapped directly in the GIS (map) part. This system is applied to the interactive interpretation and mapping of aerial photographs for an urban area. The land-use/land-cover map results in 93.44 percent overall accuracy with a kappa index of 0.9288.

Variability of activity travel patterns has long been an important issue in transportation research. Such variability has been typically explained in relation to covariance with a set of sociodemographic characteristics of travelers. However, variability also stems from differences in knowledge about the environment, which changes over time. To improve understanding of the contribution of different sources to variability in observed activity travel patterns, this paper applies sequence alignment to investigate different sources of variability in longitudinal patterns. The data on activity travel patterns were collected in 2010 for 3 months from newcomers to the city of Eindhoven, Netherlands. GPS technology was used to obtain traces that were processed with TraceAnnotator to impute activities and trips. A set of activity travel sequences for 8 weeks for 27 respondents was used in the analysis. The results show that (a) interpersonal variability is significantly higher than intrapersonal variability, although intrapersonal variability is yet substantial and should not be ignored; (b) intrapersonal variability reflecting different speeds of learning the new environment substantially changes over time; and (c) both interpersonal and intrapersonal variability are affected by sociodemographic characteristics such as gender and country of origin. The paper also discusses the implications of these findings for future research.

Spatial datasets including elevation, land cover, and population of urban areas provide a basis for modeling and animating sea-level rise and surges resulting from storms and other catastrophic events. With a geographic information system (GIS), elevation data can be used to determine urban areas with large population numbers and densities in low-lying areas subject to inundation from rising water. This chapter provides details of the analysis and modeling procedure, as well as animations for specific areas of the world that are at risk from inundation from moderate rises or surges of sea level. The work is not an attempt to predict sea-level rise, but rather a methodological study of how to use GIS data layers to create the models and animations. Whereas global sea level rise is currently measured by millimeters per year, this work examines theoretical rise measured in meters as well as coastal threats posed by tsunamis, such as occurred in the Indian Ocean in 2004. Global, regional, and local animations can be created using widely available elevation, land cover, and population data. The models and animations provide a basis for determining areas with large population numbers in relatively low-lying areas and potentially subject to inundation risk, as was the case when Hurricane Katrina devastated New Orleans. This determination can provide a basis for more detailed modeling and policy planning such as development and evacuation.