The accurate and rapid identification of landslide region is the basis for emergency disaster processing and analysis. The identification methods based on change information among multi-temporal remote optical sensing images are simple and intuitive. But its performance is remarkably limited by issues, such as unable to distinguish the changes according to the causes, improper processing strategy for impact of the adjacent pixels and the low efficiency. Thus, an approach based on digital elevation model and change information is presented in this paper. At first, the potential landslide region is calculated through slope information. And then the change information constrained by aspect information is used to identify and extract the final landslide regions. The experiment results show that, this approach can effectively distinguish the change information caused by city construction or landscaping planning. The extracted landslide regions are greatly consistent with interpretations. Meanwhile, it is effectively satisfy the demands for emergency disaster processing.
목차
Abstract 1. Introduction 2. Methodology 2.1. Potential Landslide Region 2.2. Change Characteristic Information 3. Experiments and Analysis 3.1. Data Collection and Preprocess 3.2. Potential Landslide Region of AOI 3.3. The Change Characteristics Information 3.4. Results and Analysis 4. Conclusion Acknowledgements References
보안공학연구지원센터(IJSIP) [Science & Engineering Research Support Center, Republic of Korea(IJSIP)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Signal Processing, Image Processing and Pattern Recognition
간기
격월간
pISSN
2005-4254
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.7 No.1