원격탐사자료를 바탕으로 인구밀도 분포 작성을 위한 하이브리드 대시메트릭 지도법

A Hybrid Dasymetric Mapping for Population Density Surface using Remote Sensing Data

  • 투고 : 2010.11.08
  • 심사 : 2011.01.03
  • 발행 : 2011.02.28

초록

단계구분도는 인구분포를 나타내기 위해 흔히 사용되는 방법으로 인구가 단위지역 내에 균등하게 존재함을 가정한다. 대시메트릭 지도제작법은 주거지역 정보를 통해 단계구분도보다 공간적으로 더 세밀한 인구분포를 작성할 수 있게 한다. 또한 피크노필랙틱 보간법은 단위지역 내 총인구를 유지하면서 주변지역의 인구를 고려하여 인구분포를 보간하는 방법으로 대시메트릭 지도제작법에 의한 인구분포를 연속적이고 부드럽게 하여 좀더 현실적인 인구분포도를 작성할 수 있게 한다. 따라서, 본 연구에서는 대시메트릭 지도제작법과 피크노필랙틱 보간법을 연계하는 방법을 제시하여 인구분포도의 정확도를 향상하고자 하였다. 제시한 방법을 적용하여 인구분포도를 작성하기 위해 1990년도 미국조지아주 Athens 시의 인구자료와 위성영상으로부터 추출된 주거지역 자료를 활용하였다. 결과를 검증하기 위해 인구분포도 작성에 활용된 공간단위보다 더 세밀한 공간단위의 인구자료를 활용하였으며 하이브리드 방법에 의해 높은 정확도를 확보할 수 있음을 확인하였다. 본 연구에서 제시한 하이브리드 대시메트릭에 의한 인구분포는 선거구, 학군, 분수계 등 각종 경계지역으로 변환이 용이해 다양한 응용분야에서 활용될 수 있을 것이다.

Choropleth mapping of population distribution is based on the assumption that people are uniformly distributed throughout each enumeration unit. Dasymetric mapping technique improves choropleth mapping by refining spatially aggregated data with residential information. Further, pycnophylactic interpolation can upgrade dasymetric mapping by considering population distribution of neighboring areas, while preserving the volumes of original units. This study proposed a combined solution of dasymetric mapping and pycnophylactic interpolation to improve the accuracy of population density distribution. Specifically, the dasymetric method accounts for the spatial distribution of population within each census unit, while pycnophylactic interpolation considers population distribution of neighboring area. This technique is demonstrated with 1990 census data of the Athens, GA. with land use land cover information derived from remotely-sensed imagery for the areal extent of populated areas. The results are evaluated by comparison between original population counts of smaller census units (census block groups) and population counts of the grid map built from larger units (census tracts) aggregated to the same areal units. The estimated populations indicate a satisfactory level of accuracy. Population distribution acquired by the suggested method can be re-aggregated to any type of geographic boundaries such as electoral boundaries, school districts, and even watershed for a variety of applications.

키워드

참고문헌

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