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Estimating Volume of Martian Valleys using Adaptive TIN Filtering Algorithm

Adaptive TIN 필터링을 이용한 화성 계곡의 체적 추정

  • Received : 2012.05.11
  • Accepted : 2012.09.06
  • Published : 2012.09.30

Abstract

The investigation of valley networks and their volume provide important information about past water activities on Mars. As an alternative of conventional image processing methods, terrain filtering algorithm using pointcloud data is suggested in this study. First, the topography of pointcloud is inverted so that the valleys become positive features and the algorithm is then applied to distinguish the valleys from the surface. Ground DEM and object DEM are generated from both the valleys and the surface pointcloud then the volume of valleys is estimated by multiplying the height difference between the surface with valleys and the area of valleys based on grid cellsize. In the test of valleys adjacent to Tuscaloosa crater, the total volume of valleys was estimated to be $1.41{\times}10^{11}m^3$ with the difference of 12% and 16% compared with the infill volume of Tuscaloosa crater and BTH result respectively.

화성의 계곡망 추출 및 체적 분석은 과거 화성에 존재했을 지표수의 흐름을 규명할 수 있는 중요한 정보를 제공하고 있다. 이를 위해 본 연구에서는 기존의 이미지 프로세싱 분석을 대체할 수 있는 포인트 클라우드 기반의 지형 필터링 알고리즘을 사용한 새로운 방법론을 제시하였다. 우선 추출하고자 하는 계곡을 지면으로부터 분류하기 위해 대상지역에서 취득한 포인트 클라우드 자료의 고도값을 역전한 뒤, Adaptive TIN 필터링을 적용하였다. 분류한 지면과 대상물의 포인트 클라우드로부터 각각 ground DEM과 object DEM을 생성하고, 격자 단위로 두 DEM 간의 고도차와 object DEM으로부터 취득한 계곡 면적을 곱함으로써 최종적으로 계곡의 체적을 추정하였다. 화성 Tuscaloosa 분화구에 인접한 두 계곡을 대상으로 추정된 체적의 총 합은 약 $1.41{\times}10^{11}m^3$으로 Tuscaloosa 분화구 내 퇴적물의 체적 및 기존의 이미지 프로세싱 기법인 BTH 결과와 각각 12% 및 16%의 차이를 나타내었다.

Keywords

References

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