• Journal of Ecology and Environment
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• v.41 no.8
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• pp.223-234
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• 2017

Background: Spatial structure of plants in a population reflects complex interactions of ecological and evolutionary processes. For dioecious plants, differences in reproduction cost between sexes and sizes might affect their spatial distribution. Abiotic heterogeneity may also affect adaptation activities, and result in a unique spatial structure of the population. Thus, we examined sex- and size-related spatial distributions of old-growth forest of dioecious tree Torreya nucifera in extremely heterogeneous Gotjawal terrain of Jeju Island, South Korea. Methods: We generated a database of location, sex, and size (DBH) of T. nucifera trees for each quadrat ($160{\times}300m$) in each of the three sites previously defined (quadrat A, B, C in Site I, II, and III, respectively). T. nucifera trees were categorized into eight groups based on sex (males vs. females), size (small vs. large trees), and sex by size (small vs. large males, and small vs. large females) for spatial point pattern analysis. Univariate and bivariate spatial analyses were conducted. Results: Univariate spatial analysis showed that spatial patterns of T. nucifera trees differed among the three quadrats. In quadrat A, individual trees showed random distribution at all scales regardless of sex and size groups. When assessing univariate patterns for sex by size groups in quadrat B, small males and small females were distributed randomly at all scales whereas large males and large females were clumped. All groups in quadrat C were clustered at short distances but the pattern changed as distance was increased. Bivariate spatial analyses testing the association between sex and size groups showed that spatial segregation occurred only in quadrat C. Males and females were spatially independent at all scales. However, after controlling for size, males and females were spatially separated. Conclusions: Diverse spatial patterns of T. nucifera trees across the three sites within the Torreya Forest imply that adaptive explanations are not sufficient for understanding spatial structure in this old-growth forest. If so, the role of Gotjawal terrain in terms of creating extremely diverse microhabitats and subsequently stochastic processes of survival and mortality of trees, both of which ultimately determine spatial patterns, needs to be further examined.

• Korean Journal of Remote Sensing
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• v.39 no.4
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• pp.459-466
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• 2023

In the last decade, artificial intelligence's dramatic advancement with the development of various deep learning techniques has significantly contributed to remote sensing fields and satellite image applications. Among many prominent areas, super-resolution research has seen substantial growth with the release of several benchmark datasets and the rise of generative adversarial network-based studies. However, most previously published remote sensing benchmark datasets represent spatial resolution within approximately 10 meters, imposing limitations when directly applying for super-resolution of small objects with cm unit spatial resolution. Furthermore, if the dataset lacks a global spatial distribution and is specialized in particular land covers, the consequent lack of feature diversity can directly impact the quantitative performance and prevent the formation of robust foundation models. To overcome these issues, this paper proposes a method to generate benchmark datasets by simulating the modulation transfer functions of the sensor. The proposed approach leverages the simulation method with a solid theoretical foundation, notably recognized in image fusion. Additionally, the generated benchmark dataset is applied to state-of-the-art super-resolution base models for quantitative and visual analysis and discusses the shortcomings of the existing datasets. Through these efforts, we anticipate that the proposed benchmark dataset will facilitate various super-resolution research shortly in Korea.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.1-18
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• 2019

This research measured and visualized the spatial dependency and the spatial heterogeneity of the small business in Cheonan-si, Asan-si with $100m{\times}100m$ grids based on global and local spatial autocorrelation. First, we confirmed positive spatial autocorrelation of small business in the research area using Moran's I Index, which is ESDA(Exploratory Spatial Data Analysis). And then, through Getis-Ord $GI{\ast}$, one kind of LISA(Local Indicators of Spatial Association), local patterns of spatial autocorrelation were visualized. These verified that Spatial Regression Model is valid for the location factor analysis on small business commercial buildings. Next, GWR(Geographically Weighted Regression) was used to analyze the spatial relations between the distribution of small business, hourly mobile traffic-based floating population, land use attributes index, residence, commercial building, road networks, and the node of traffic networks. Final six variables were applied and the accessibility to bus stops, afternoon time floating population, and evening time floating population were excluded due to multicollinearity. By this, we demonstrated that GWR is statistically improved compared to OLS. We visualized the spatial influence of the individual variables using the regression coefficients and local coefficients of determinant of the six variables. This research applied the measured population information in a practical way. Reflecting the dynamic information of the urban people using the commercial area. It is different from other studies that performed commercial analysis. Finally, this research has a differentiated advantage over the existing commercial area analysis in that it employed hourly changing commercial service population data and it applied spatial statistical models to micro spatial units. This research proposed new framework for the commercial analysis area analysis.

• Ocean Science Journal
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• v.43 no.2
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• pp.67-79
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• 2008

We investigated the relationship between mesoscale spatial distribution of environmental parameters (temperature, salinity, and sigma-t), chlorophyll-a concentration and mesozooplankton in the Yellow Sea during May 1996, 1997, and 1998, with special reference to Yellow Sea Bottom Cold Water (YSBCW). Adult calanoid copepods, Calanus sinicus, Paracalanus parvus s.l., Acartia omorii, and Centropages abdominalis were isolated by BVSTEP analysis based on the consistent explainable percentage (-32.3%) of the total mesozooplankton distributional pattern. The copepods, which accounted for 60 to 87% of the total abundances, occupied 73-78% of the copepod community. The YSBCW consistently remained in the northern part of the study area and influenced the spatial distribution of the calanoid copepods during the study periods. Abundances of C. sinicus and P. parvus s.l., which were high outside the YSBCW, were positively correlated with the whole water average temperature (p<0.01). In contrast, the abundances of C. abdominalis and A. omorii, which were relatively high in the YSBCW, were associated with the integrated chl-a concentration based on factor analysis. These results indicate that the YSBCW influenced the mesoscale spatial heterogeneity of average temperature and integrated chl-a concentration through the water column. This consequently affected the spatial distribution pattern of the dominant copepods in association with their respective preferences for environmental and biological parameters in the Yellow Sea during spring.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.14 no.6
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• pp.111-117
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• 2011

This study attempts to facilitate climate change adaptation in conservation area by spatial planning of climate adaptation zone for endangered species. Spatial area is South Korea and select leopard cat (Prionailurus bengalensis) as a target species of this study. In order to specify the climate adaptation zone, firstly, Maximum entropy method (Maxent) was used to identify suitable habitat, and then core habitat was selected for leopard cat. Secondly, land use resistance index was evaluated and least cost distance was analyzed for target species. In this step we choose dispersal capacity of leopard cat to reflect species ecological characteristic. Finally, climate adaptation zone is described and adaptation measures are suggested. The presented approach could be generalized for application into conservation planning and restoration process. Furthermore, spatial planning of climate adaptation zone could increase heterogeneity of habitat and improve adaptive capacity of species and habitat itself.

• BMB Reports
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• v.55 no.3
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• pp.113-124
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• 2022

Single-cell RNA sequencing (scRNA-seq) has greatly advanced our understanding of cellular heterogeneity by profiling individual cell transcriptomes. However, cell dissociation from the tissue structure causes a loss of spatial information, which hinders the identification of intercellular communication networks and global transcriptional patterns present in the tissue architecture. To overcome this limitation, novel transcriptomic platforms that preserve spatial information have been actively developed. Significant achievements in imaging technologies have enabled in situ targeted transcriptomic profiling in single cells at single-molecule resolution. In addition, technologies based on mRNA capture followed by sequencing have made possible profiling of the genome-wide transcriptome at the 55-100 ㎛ resolution. Unfortunately, neither imaging-based technology nor capture-based method elucidates a complete picture of the spatial transcriptome in a tissue. Therefore, addressing specific biological questions requires balancing experimental throughput and spatial resolution, mandating the efforts to develop computational algorithms that are pivotal to circumvent technology-specific limitations. In this review, we focus on the current state-of-the-art spatially resolved transcriptomic technologies, describe their applications in a variety of biological domains, and explore recent discoveries demonstrating their enormous potential in biomedical research. We further highlight novel integrative computational methodologies with other data modalities that provide a framework to derive biological insight into heterogeneous and complex tissue organization.

• Spatial Information Research
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• v.11 no.3
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• pp.227-240
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• 2003

The primary focus of this study is to provide a general methodology which can be utilized to understand and analyze environmental issues such as long term ecosystem dynamics and land use/cover change by development of 2D dynamic landscape models and model-based simulation. Change processes in land cover and ecosystem function can be understood in terms of the spatial and temporal distribution of land cover resources. In development of a system to understand major processes of change and obtain predictive information, first of all, spatial heterogeneity is to be taken into account because landscape spatial pattern affects on land cover change and interaction between different land cover types. Therefore, the relationship between pattern and processes is to be included in the research. Landscape modeling requires different approach depending on the definition, assumption, and rules employed for mechanism behind the processes such as spatial event process, land degradation, deforestration, desertification, and change in an urban environment. The rule-based models are described in the paper for land cover change by natural fires. Finally, a case study is presented as an example using spatial modeling and simulation to study and synthesize patterns and processes at different scales ranging from fine-scale to global scale.

• Journal of KIISE:Databases
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• v.31 no.4
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• pp.362-372
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• 2004

One of the most difficult problems in building a distributed GIS lies in the heterogeneity of spatial databases. In particular, positional mismatches between spatial databases, which arise due to several reasons, may incur incorrect query results. They result in unreliable outputs of query processing. One simple solution is to correct positional data in spatial databases at each site, according to the most accurate one. This solution is however not practical in cases where the autonomy of each database should be respected. In this paper, we propose a spatial query processing method without correcting positional data in each spatial database. Instead of correcting positional data, we dynamically transform a given query region or position onto each space where spatial objects of each site are located. Our proposed method is based on an elastic transformation method by using delaunay triangulation. Accuracy of this method is proved mathematically, and is confirmed by an experiment. Moreover, we implemented using common use database system for usefulness verification of this method.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.2
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• pp.71-85
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• 2012

The purpose of this study is to estimate air purification effectiveness considering the improvement of its methods related atmospheric environment. The air purification effectiveness is estimated in Daegu, one out of Korean Metropolitan cities because air pollution is getting serious in a heavily urbanized area. The absorption of pollutants is calculated by considering spatial heterogeneity that was not considered previous studies and the spatial resolution of air dispersion modeling is also improved by kriging method. According to the type and distribution of urban forest, total 26 kinds of plant communities were distributed with Pinus densiflora community, Pinus densiflora-Quercus mongolica community, Pinus densiflora-Quercus acutissima community and other kinds of communities in the study area. In the results of estimating the $CO_2$ absorption amount for identification of the air purification effectiveness on urban forest, the annual absorption amount was total 108,155t/yr. Also, the annual absorption amounts of $NO_2$ and $SO_2$ were total 183.5 ton and 410.2 ton respectively. The findings from this study can confirm the differences of pollutant absorption by concentration that could not identify if spatial distribution of pollutant concentration had not been considered.

• Journal of Soil and Groundwater Environment
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• v.11 no.5
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• pp.9-19
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• 2006

The accurate estimation of groundwater recharge is important for the proper management of groundwater systems. The widely used techniques of groundwater recharge estimation include water table fluctuation method, baseflow separation method, and annual water balance method. However, these methods can not represent the temporal-spatial variability of recharge resulting from climatic condition, land use, soil storage and hydrogeological heterogeneity because the methods are all based on the lumped concept and local scale problems. Therefore, the objective of this paper is to present an effective method for estimating groundwater recharge with spatial-temporal variability using the SWAT model which can represent the heterogeneity of the watershed. The SWAT model can simulate daily surface runoff, evapotranspiration, soil storage, recharge, and groundwater flow within the watershed. The model was applied to the Musimcheon watershed located in the upstream of Mihocheon watershed. Hydrological components were determined during the period from 2001 to 2004, and the validity of the results was tested by comparing the estimated runoff with the observed runoff at the outlet of the catchment. The results of temporal and spatial variations of groundwater recharge were presented here. This study suggests that variations in recharge can be significantly affected by subbasin slope as well as land use.