• Korean Journal of Remote Sensing
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• v.27 no.1
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• pp.69-74
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• 2011

It may be an important issue to estimate population of a concerned country. In this study, an appropriate variable was selected to establish a model which fits best the relationship between the night time imagery of DMSP-OLS and population data. Exponential model was selected which was proposed by previous study. Accuracy validation was also performed for each variable extracted from the night time imagery of DMSP-OLS. Consequently, the model showed high accuracy when applied to the area of a certain amount of light was existed. However, further consideration should be necessary when to applied other country or other part of regions.

• Korea journal of population studies
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• v.28 no.1
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• pp.149-172
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• 2005

장래인구추계(population projection)는 한 사회의 인구수 및 구조 변화를 추정하는 것으로 사회의 잠재적 자원 수요와 노동력 공급을 위한 기초정보를 제공한다. 정확한 장래인구를 추계하는 것은 국가 및 중앙정부 뿐 아니라 지방정부 혹은 그보다 규모가 작은 기초자치단체도 미래의 사회적 변화에 대응하고 지역 특성에 알맞은 정책을 마련하기 위하여 중요한 일임에 틀림없다. 우리나라의 경우 장래인구추계는 통계청에서 담당하고 있는데 현재까지 국가 및 시도단위의 장래인구추계 결과를 발표하고 있으며 기초자치단체는 인구추계의 대상에서 제외되어 있다. 이 글은 Hamilton과 Perry에 의해서 최초 개발되어 실제 미국의 소규모지역별 장래인구추계에 사용되어 온 추계기법을 사용하여 한국의 기초자치단체에의 적용가능성에 대해 검토해 본 연구이다. 장래인구추계를 위한 H-P기법은 도시와 농촌지역의 기초자치단체에 각각 적용해 본 결과 통계청에서 주로 사용하고 있는 코호트 조성법을 이용한 추계기법보다 단순하고 추계를 위해 필요한 정보도 쉽게 얻을 수 있으면서도 비교적 정확한 추계결과를 제시하였다.

• Proceedings of the Population Association of Korea Conference
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• 2006.12a
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• pp.37-55
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• 2006

• Korea journal of population studies
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• v.11 no.1
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• pp.1-13
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• 1988

This study examines the sampling bias that may have resulted from the large number of missing observations. Despite well-designed and reliable sampling procedures, the observed sample values in DSFH(Demographic Survey on Changes in Family and Household Structure, Japan) included many missing observations. The head administerd survey method of DSFH resulted in a large number of missing observations regarding characteristics of elderly non-head parents and their children. In addition, the response probability of a particular item in DSFH significantly differs by characteristics of elderly parents and their children. Furthermore, missing observations of many items occurred simultaneously. This complex pattern of missing observations critically limits the ability to produce an unbiased analysis. First, the large number of missing observations is likely to cause a misleading estimate of the standard error. Even worse, the possible dependency of missing observations on their latent values is likely to produce biased estimates of covariates. Two models are employed to solve the possible inference biases. First, EM algorithm is used to infer the missing values based on the knowledge of the association between the observed values and other covariates. Second, a selection model was employed given the suspicion that the probability of missing observations of proximity depends on its unobserved outcome.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.11
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• pp.3302-3307
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• 2009

The objective of the present study lies in providing the method to construct the precision population-statistical map for statistical demographics making full advantage of GIS and the national census data in an attempt to improve accuracy and reliability of population estimation applicable for a variety of location analysis. More specifically, it adopts the multiple regression analysis by segmented land use type(biotope) taking into account that the land use diversified as residence, commercial and office areas has the close connectivity and interdependence with population. Based on the analyzed result above, the study finalizes the modeling to construct demographic map with higher precision by prioritizing the population density by weight value and then re-distributing the population according to jurisdictional dong's and types of use for the land. The study consequently is expected to be conducive to improving precision and reliability rather than the existing method for population estimation widely acceptable thus far.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.6
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• pp.3797-3806
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• 2015

A population decline in rural area is correlated with the number of household, with agricultural workers, as a result, affects the farming income. Agricultural population is a foundation of agriculture structure. Agricultural population decline influences agricultural policies to be implemented for the future and there is concern about slowdown in productivity. The purpose of this study is to build the ability to use the model and conduct applied analyses of various kinds and to make rational agricultural policies by forecasting and analyzing agricultural population change. Unlike previous studies, which have some assumptions about the giving-up farming rate (GFR) of the key points on the agricultural population model or, After estimating only one equation with respect to the total population, and then distribute by sex and age. This study was conducted to investigate the reactions are different from the farmhouse, gender, age by estimating giving-up farming rate (GFR) equations each gender & age. Through this research, we can find that Farm Population changes of the simulation can be performed for a variety of agricultural policy in conjunction with existing agricultural simulation models as well.

• Proceedings of the Korean Statistical Society Conference
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• 2002.05a
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• pp.7-12
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• 2002

경제활동인구조사에서 시군구의 실업자를 추정하는데 소지역 추정법을 이용하는 방안에 대한 연구는 관심의 대상이 되고 있다. 본 연구에서는 합성 추정법과 복합 추정법을 이용한 시군구 실업통계 작성법을 소개하였고 추정량이 편향이므로 잭나이프 방법을 이용한 추정량의 정도를 계산하는 절차를 설명하였으며, 광주광역시의 구별 실업통계작성을 사례로 제시하였다.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.163-174
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• 2008

The conventional four-step travel demand model is still widely used as the state-of-practice in most transportation planning agencies even though it does not provide reliable estimates of travel demand. In order to improve the accuracy of travel demand estimation, implementing an alternative approach would be critical as much as acquiring reliable socioeconomic and travel data. Recently, the role of travel demand model is diverse to satisfy the needs of microscopic analysis regarding various policies of travel demand management and traffic operations. In this context, the activity-based approach for travel demand estimation is introduced and a case study of developing a spatial-temporal activity presence-based approach that estimates travel demand through forecasting number of people present at certain place and time is accomplished. Results show that the spatial-temporal activity presence-based approach provides reliable estimates of both number of people present and trips actually people made. It is expected that the proposed approach will provide better estimates and be used in not only long-term transport plans but short-term transport impact studies with respect to various transport policies. Finally, in order to introduce the spatial-temporal activity presence-based approach, the data such as activity-based travel diary and land use based on geographic information system are essential.

• Korea journal of population studies
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• v.23 no.1
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• pp.197-215
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• 2000

이 논문에서는 선형·비선형 성장곡선모형의 종류와 특성을 살펴보고, 이들을 비교·검토하고, 모형선호기준 통계량에 입각하여 추정결과를 비교한다. 또한 최종사용자 환경을 위한 SAS/AF로 구현한 성장곡선모형에 의한 인구예측시스템을 소개한다.

• 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.