• Spatial Information Research
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• v.8 no.2
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• pp.233-241
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• 2000

The objective of this study were to develop landscape scale ecosystem assessment model, and apply the model for the assessment of the state and change of ecosystem of the study area, Yongin, Korea. Since natural ecosystem of the site has been deteriorated significantly during recent extensive residential development, it is essential to correctly assess ecosystem of the study site. Traditional ecosystem assessment mainly utilizing intensive field survey requires high cost, but the outcome rarely represents spatial pattern of the regional ecosystems. Ecosystem assesment of landscape scale based on landscape ecology can resolve most of the shortfalls of the traditional approach. The research method can be summarized as follows. First, extensive literature review on such topics as spatial pattern of ecosystem, ecosystem assessment of landscape scale, ecological analysis was carried out. Second, a model for the ecosystem assessment of landscape scale emphasizing spatial pattern of ecosystem was developed. This model evaluates three indicators; ecological integrity and biological diversity, watershed integrity, and landscape resilience of 11 watersheds in the study area. Finally, ecological assessment utilizing two sets of indicators, enhancement of and disturbance of ecosystem stability, was carried out. This assessment method is based on Environmental Monitoring and Assessment Program´s Landscape component(EMAP-L) of EPA(1994). The results of this study are as follows. First, the ecosystem assessment of landscape scale of the study area of Yongin, Korea, showed that escosystems of Tanchun01 and Chungmichun01 watersheds had the worst state in the study site in 1991. On the other hand, the ecosystems of Jinwechun01, Kyunganchun02, and Bokhachun01 watersheds had the most stable ecosystem in 1991. Second, ecosystems of Tanchun01, Shingal reservoir, and Kyunganchun01 watersheds were evaluated to be the worst state in the study site in 1996. And, ecosystems of Jinwechun01 and Gosam reservoir watersheds had the most stable ecosystem. Third, ecosystem of Tanchun01 watershed which incudes Suji residential development project site changed the most drastically between 1991 and 1996. The ecosystem of the watershed the most drastically deteriorated due to it´s proximity to Seoul and Bundang new town.

• Journal of KIISE:Databases
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• v.30 no.3
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• pp.273-285
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• 2003

Generally, vector spatial data, with richer information than raster spatial data enabledata, enables a mere flexible and effective manipulation of the data sets. However, one of challenges against the publication of vector spatial information on the Internet is the efficient transmission of the big and complex vector spatial datadata, which is both large and complex, across the narrow-bandwidth of the Internet. This paper proposes a new transmission method, namely, the Scale-Dependent Transmission method, with the purpose of improving the efficiency of vector spatial data transmission on the narrow-bandwidthacross the Internet. Simply put, its nam idea is “Transmit what can be seen””. Scale is regarded as a factor naturally associated with spatial features so that not all features are visible to users at a certain scale. With the aid of the Wavelet-Wavelet-based Map Generalization Algorithm, the proposed method filters out invisible features from spatial objects according to the display scale and then to transmit onlytransmits only the visible features as athe final answer for an individual operation. Experiments show that the response times ofan individual operation has been reducedoperations were substantially by the usage of reduced when using the proposed method.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.9
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• pp.1218-1225
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• 2002

Large-scale vortical structure of a turbulent separation bubble affected by unsteady wake is essential to understand flow mechanisms in various fluid devices. A spoked-wheel type of wake generator provides unsteady wake, which modifies the turbulent separation bubble significantly by changing rotation directions and passing frequencies. A detailed mechanism of vortex shedding from the separation bubble with unsteady wake is analyzed by taking a conditional average with spatial box filtering, which spatially integrates measured signals at pre-determined wavelength. A convecting nature of the large-scale vortical structure is analyzed carefully. Spatial evolution of the large-scale vortical structure with frequency variance is also exemplified.

• Wind and Structures
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• v.14 no.4
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• pp.301-319
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• 2011

The full-scale measurements are compared with the wind tunnel test results for the long-span roof latticed spatial structure of Shenzhen Citizen Center. A direct comparison of model testing results to full-scale measurements is always desirable, not only in validating the experimental data and methods but also in providing better understanding of the physics such as Reynolds numbers and scale effects. Since the quantity and location of full-scale measurements points are different from those of the wind tunnel tests taps, the weighted proper orthogonal decomposition technique is applied to the wind pressure data obtained from the wind tunnel tests to generate a time history of wind load vector, then loads acted on all the internal nodes are obtained by interpolation technique. The nodal mean wind pressure coefficients, root-mean-square of wind pressure coefficients and wind pressure power spectrum are also calculated. The time and frequency domain characteristics of full-scale measurements wind load are analyzed based on filtered data-acquisitions. In the analysis, special attention is paid to the distributions of the mean wind pressure coefficients of center part of Shenzhen Citizen Center long-span roof spatial latticed structure. Furthermore, a brief discussion about difference between the wind pressure power spectrum from the wind tunnel experiments and that from the full-scale in-site measurements is compared. The result is important fundament of wind-induced dynamic response of long-span spatial latticed structures.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.12
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• pp.1674-1680
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• 2002

An experimental study was made of a large-scale vortical structure over a backward-facing step. The Reynolds number based on the step height was R $e_{H}$ =33,000. To recognize the large-scale vortex, three components of velocity were measured. The measurements were performed in the recirculation zone (x/H=4.0) and the reattachment zone(x/H=7.5). To measure the wall pressure fluctuations in a turbulent flow over a backward-facing step, a 32-channel microphone array was installed beneath the wall in the streamwise and spanwise directions. From the measured pressure field, the size of large-scale vortex was obtained. As a detailed study, a conditionally-averaging technique was employed to characterize the coherent structure of the large-scale vortex. To see the relationship between the flow field and the relevant spatial mode of the pressure field, the spatial box filtering (SBF) was examined. A cross-correlation between velocity and pressure fluctuations was performed to identify the structure and the length scale of the large-scale vortex.x.

• Journal of the Korean Geographical Society
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• v.46 no.2
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• pp.197-211
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• 2011

Due to the complexity of spatial interaction and the necessity of spatial representation and modeling, aggregation of spatial interaction data is indispensible. Given this, the purpose of this paper is to evaluate the effects of modifiable areal unit problem (MAUP) on a spatial interaction model. Four aggregation schemes are utilized at eight different scales: 1) randomly select seeds of district and then allocate basic spatial units to them, 2) minimize the sum of population weighted distance within a district, 3) maximize the proportion of flow within a district, and 4) minimize the proportion of flow within a district. A simple Poisson regression model with origin and destination constraints is utilized. Analysis results demonstrate that spatial characteristics of residuals, parameter values, and goodness-of-fit of the model were influenced by aggregation scale and schemes. Overall, the model responded more sensitively to aggregation scale than aggregation schemes and the scale effect on the model was varied according to aggregation schemes.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.25-33
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• 2016

In order to visualize point based Location-Based Social Network Services(LBSNS) data on multi-scaled tile map effectively, it is necessary to apply tile-based clustering method. Then determinating reasonable numbers and size of tiles is required. However, there is no such criteria and the numbers and size of tiles are modified based on data type and the purpose of analysis. In other words, researchers' subjectivity is always involved in this type of study. This is when Modifiable Areal Unit Problem(MAUP) occurs, that affects the results of analysis. Among LBSNS, geotagged Twitter data were chosen to find the influence of MAUP in scale effects perspective. For this purpose, the degree of spatial autocorrelation using spatial error model was altered, and change of distributions was analyzed using Morna's I. As a result, positive spatial autocorrelation showed in the original data and the spatial autocorrelation was decreased as the value of spatial autoregressive coefficient was increasing. Therefore, the intensity of the spatial autocorrelation of Twitter data was adjusted to five levels, and for each level, nine different size of grid was created. For each level and different grid sizes, Moran's I was calculated. It was found that the spatial autocorrelation was increased when the aggregation level was being increased and decreased in a certainpoint. Another tendency was found that the scale effect of MAUP was decreased when the spatial autocorrelation was high.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1209-1211
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• 2003

The wavelet and semivariogram analysis method are used to identify the city landscape and farmland landscape pattern on the 1m resolution IKONOS images. The results prove that wavelet method is a potential way for landscape pattern analysis. Compared to semivariogram analysis, Wavelet analysis can not only detect the overall spatial pattern, but also find multi-scale and direction structures. In this experiment, the wavelet analysis results indicate: (1) the city landscape image is mainly composed of three level structures whose spatial pattern characters appear at 2m, 16m, 128m and 256m accordingly; (2) the farmland landscape is mainly two scale spatial patterns appearing at the 2m, 128m and 256m. IKONOS Remote sensing, with the high spatial and spectral information, is a powerful tool that can use in many ecological systems research and sustainable management.

• Journal of the Korean association of regional geographers
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• v.7 no.1
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• pp.35-50
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• 2001

Since remotely sensed images of coastal wetlands are very sensitive to spatial resolution, it is very important to select an optimum resolution for particular geographic phenomena needed to be represented. Scale is one of the most important factors in spatial analysis techniques, which is defined as a spatial and temporal interval for a measurement or observation and is determined by the spatial extent of study area or the measurement unit. In order to acquire the optimum scale for a particular subject (i.e., coastal wetlands), measuring and representing the characteristics of attribute information extracted from the remotely sensed images are required. This study aims to explore and analyze the scale effects of attribute information extracted from remotely sensed coastal wetlands images. Specifically, it is focused on identifying the effects of scale in response to spatial resolution changes and suggesting a methodology for exploring the optimum spatial resolution. The LANDSAT TM image of Sunchon Bay was classified by a supervised classification method, Six land cover types were classified and the Kappa index for this classification was 84.6%. In order to explore the effects of scale in the classification procedure, a set of images that have different spatial resolutions were created by a aggregation method. Coarser images were created with the original image by averaging the DN values of neighboring pixels. Sixteen images whose resolution range from 30 m to 480 m were generated and classified to obtain land cover information using the same training set applied to the initial classification. The values of Kappa index show a distinctive pattern according to the spatial resolution change. Up to 120m, the values of Kappa index changed little, but Kappa index decreased dramatically at the 150m. However, at the resolution of 240 m and 270m, the classification accuracy was increased. From this observation, the optimum resolution for the study area would be either at 240m or 270m with respect to the classification accuracy and the best quality of attribute information can be obtained from these resolutions. Procedures and methodologies developed from this study would be applied to similar kinds and be used as a methodology of identifying and defining an optimum spatial resolution for a given problem.

• Journal of Biosystems Engineering
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• v.39 no.4
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• pp.377-388
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• 2014

Purpose: Determining the spatial structure of data is important in understanding within-field variability for site-specific crop management. An understanding of the spatial structures present in the data may help illuminate interrelationships that are important in subsequent explanatory analyses, especially when site variables are correlated or are a combined response to multiple causative factors. Methods: In this study, correlation, principal component analysis, and single and nested variogram models were applied to soil electrical conductivity and chemical property data of two fields in central Missouri, USA. Results: Some variables that were highly correlated, or were strongly expressed in the same principal component, exhibited similar spatial ranges when fitted with a single variogram model. However, single variogram results were dependent on the active lag distance used, with short distances (30 m) required to fit short-range variability. Longer active lag distances only revealed long-range spatial components. Nested models generally yielded a better fit than single models for sensor-based conductivity data, where multiple scales of spatial structure were apparent. Gaussian-spherical nested models fit well to the data at both short (30 m) and long (300 m) active lag distances, generally capturing both short-range and long-range spatial components. As soil conductivity relates strongly to profile texture, we hypothesize that the short-range components may relate to the scale of erosion processes, while the long-range components are indicative of the scale of landscape morphology. Conclusion: In this study, we investigated the effect of changing active lag distance on the calculation of the range parameter. Future work investigating scale effects on other variogram parameters, including nugget and sill variances, may lead to better model selection and interpretation. Once this is achieved, separation of nested spatial components by factorial kriging may help to better define the correlations existing between spatial datasets.