Remote Sensing for Disaster Projection Model

4th International Conference of Indonesian Society for Remote Sensing

物理学;能源学

Sutrisno, D.^1 ; Iksal, M.^2 ; Suwarno, Y.^1 ; Setiawan, I.^3 ; Yusmur, A.^4

Geospatial Information Agency/ISRS, Jalan Raya Jakarta Bogor KM 46, Cibinong

16911, Indonesia^1

Ibnu Kaldun University, Jalan KH Soleh Iskandar Km 2, Kedung Badak Bogor

16164, Indonesia^2

PT Agrisoft, Jl. Achmad Adnawijaya No.162A, Tegal Gundil, Bogor Utara, Kota Bogor, Jawa Barat

16152, Indonesia^3

Seameo Biotrop, Jalan Raya Tajur KM.6, Pakuan, Bogor Selatan, Kota Bogor, Jawa Barat

16134, Indonesia^4

关键词: Banjarnegara;    Landslides hazards;    projection;    Remote sensing approaches;    Remote sensing satellites;    Remote sensing techniques;    Remote sensing technology;    Spatial informations;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/280/1/012037/pdf
DOI  :  10.1088/1755-1315/280/1/012037

来源: IOP

【 摘 要 】

Natural disasters are natural phenomena that cannot be avoided by humans, but human beings are able to mitigate its impact for the humanitarian aspects. Therefore monitoring, predicting and managing natural phenomenon in the earth is one of the methods to mitigate disaster - one of them by using remote sensing technology. Integrated of imageries from near real-time remote sensing satellite system to the higher resolution with the support of the ancillary data may develop spatial information for any mitigation purposes. Therefore, the aim of the study is to assess rapid information of the prone area and the possibility of developing a projection model with the remote sensing approach. The steps included the assessment of prone area by implemented the integrated method of NDVI, fussy and high pass and the overview of the projection model using remote sensing approach. The disasters associated with landslides may be used for example, because this disaster often struck the Asian region. The result of the assessment indicated the integration of NDVI, fussy and high pass method can give faster information of the landslides hazards that is needed for disaster and humanitarian institutions. Meanwhile, to develop a projection model for the hazards cannot be developed only on remote sensing technique, but better support by GIS technique and other in situ ancillary information.