• Journal of the Korean association of regional geographers
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• v.12 no.5
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• pp.614-630
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• 2006

Improved estimates of populations at risk for quick and effective response to natural and man-made disasters require spatial disaggregation of zonal population data because of the spatial mismatch problem in areal units between census and impact zones. This paper implements a dasymetric surface model to facilitate spatial disaggregation of the population of a census block group into populations associated with each constituent pixel and evaluates the performance of the surface-based spatial disaggregation model visually and statistically. The surface-based spatial disaggregation model employed geographic information systems (GIS) to enable dasymetric interpolation to be guided by satellite-derived land use and land cover data as additional information about the geographic distributor of population. In the spatial disaggregation, percent cover based empirical sampling and areal weighting techniques were used to objectively determine dasymetric weights for each grid cell. The dasymetric population surface for the Atlanta metropolitan area was generated by the surface-based spatial disaggregation model. The accuracy of the dasymetric population surface was tested on census counts using the root mean square error (RMSE) and an adjusted RMSE. The errors related to each census track and block group were also visualized by percent error maps. Results indicate that the dasymetric population surface provides high-precision estimates of populations as well as the detailed spatial distribution of population within census block groups. The results also demonstrate that the population surface largely tends to overestimate or underestimate population for both the rural and forested and the urban core areas.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.2
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• pp.11-22
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• 2007

This paper is to discuss analytical techniques to estimate demand sizes and volumes that determine optimal locations for multiple facilities for a given services. While demand size estimation is a core part of location modeling to enhance solution quality and practical applicability, the estimation method has been used in limited and restrict parts such as a single population centroid in a given larger census boundary area or small theoretical application experiments(e.s. census track and enumeration district). Therefore, this paper strives to develop an analytical estimation method of demand size that converts area based demand data to point based population weighted centroids. This method is free to spatial boundary units and more robust to estimate accurate demand volumes regardless of geographic boundaries. To improve the estimation accuracy, this paper uses house weighted value to the population centroid calculation process. Then the population weighted centroids are converted to individual demand points on a grid formated surface area. In turn, the population weighted centroids, demand points and network distance measures are operated into location-allocation models to examine their roles to enhance solution quality and applicability of GIS location models. Finally, this paper demonstrates the robustness of the weighted estimation method with the application of location-allocation models.

• Korean Journal of Environmental Biology
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• v.37 no.1
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• pp.82-87
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• 2019

Global warming has a significant impact on diverse ecosystems including agroecosystem through; changing of phenology, physiology and distribution. Monitoring of biological responses emanating from global warming is required to understand the challenges of biological diversity conservation posed by climate change. The Korean government selected four butterfly species as indicators of climate change in agroecosystem: Papilio xuthus, Pieris rapae, Colias erate, and Eurema mandarina. The aim of this study was to investigate the different monitoring methods of the butterflies in Korea and suggest a suitable monitoring method to track the population trends of butterflies in the agroecosystem. Butterfly monitoring was conducted in eight sites throughout Korea from April to October, 2018 using three survey methods: point census at rice paddy area, point census at the border between rice paddy and hill and line transect along the rice paddy and hill. Each method took approximately 30 min. to count the butterflies. A total of 4,691 butterflies and 92 species were counted: The most dominant species was Pieris rapae with a total count of 1,205 individuals followed by Polygonia c-aureum, Zizeeria maha, Colias erate, Cupido argiades and Papilio xuthus. Among the three census methods, the total number of species and individuals when using line transect method was statistically higher than in the other methods. However, the numbers of the four butterflies indicators showed no difference throughout three census methods. Based on the number of species and the total individuals butterflies in agroecosystem, we advocate for the application of line transect method as it can find more butterflies in agroecosystem. In addition, we advised for the implementation of education programs on the line transect method in butterfly identification to participants of the national monitoring program.

• Spatial Information Research
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• v.22 no.3
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• pp.89-99
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• 2014

The aim of this study is to represent the residential population distribution in Seoul, Korea more precisely through the dasymetric mapping method. Dasymetric mapping can be defined as a mapping method to calculate details from truncated spatial distribution of main statistical data by using ancillary data which is spatial data related to the main data. In this research, there are two types of data used for dasymetric mapping: the population data (2010) based on a output area survey in Seoul as the main data and the building footprint data including register information as ancillary spatial data. Using the binary method, it extracts residential buildings as actual areas where residents do live in. After that, the regression method is used for calculating the weights on population density by considering the building types and their gross floor areas. Finally, it can be reproduced three-dimensional density of residential population and drew a detailed dasymetric map. As a result, this allows to extract a more realistic calculating model of population distribution and draw a more accurate map of population distribution in Seoul. Therefore, this study has an important meaning as a source which can be applied in various researches concerning regional population in the future.