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토지특성 고저조사를 위한 공간정보 데이터 구축과 데이터 마이닝 분석

Spatial Information Data Construction and Data Mining Analysis for Topography Investigation of Land Characteristics

  • Choi, Jin Ho (Public Announcement Research Department, Korea Appraisal Board) ;
  • Kim, Jun Hyun (Dept. of Geodetic and Cadastral Information, Taegu Science University)
  • 투고 : 2019.11.20
  • 심사 : 2019.12.12
  • 발행 : 2019.12.31

초록

토지특성조사는 토지가격비준표 작성 및 표준지와 개별지의 특성차이 비교를 통한 지가 산정 과정에서 매우 중요한 과정이다. 따라서 토지특성조사는 최대한 객관적이고 합리적이며 일관성 있게 이루어져야 한다. 그러나 현재 토지특성조사는 지자체 공무원과 감정평가사의 경험이 상당수 반영되고 있기 때문에 객관성과 일관성을 보장하기 어렵다. 본 연구에서는 현행 토지특성조사 항목 중 고저의 조사방식을 분석하여 문제를 정의하고, 고저 분류를 위해 토지의 고저 정보를 공간정보 기술 기반으로 수치화하여 이를 데이터 마이닝 기법 중 하나인 C4.5을 적용하여 고저를 분류하는 방법을 제시하였다. 서울시의 표준지 고저 조사 결과와 필지의 공간정보를 C4.5 모델에 적용한 결과에서는 기존 감정평가사의 조사 결과 약 93.5% 일치 하는 것으로 나타났다.

The investigation of land characteristics is an important task for the calculation of officially land prices and standard comparison table of land price. Therefore, it should be done objectively and consistently. However, the current investigation system is mainly done by researcher's subjective judgment. Therefore, the objectivity and consistency of this investigation is not guaranteed and questionable. In this study, we first defined the problem by analyzing the current land topography investigation method. In addition, in order to investigate the land topography, the geometry of the parcel is quantified by spatial information and applied to the decision tree based method(C4.5) to produce the final result. This study intended to extract the parcel characteristics data of the topographic by the use of spatial information and to apply the information to the C4.5, there by suggesting a method for addressing the problems. The findings showed approximately 93.5% between the results of topography classification estimated with rules learned by C4.5.

키워드

참고문헌

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피인용 문헌

  1. 네트워크 RTK와 연계한 비금속 상수관의 GPR 탐사 vol.22, pp.2, 2019, https://doi.org/10.5762/kais.2021.22.2.296