Visualization of Volcanic Ash Distribution based on Multispectral Satellite Imagery: A Comparing Method

被引:0
|
作者
Putra, Richard Mahendra [1 ]
Saputro, Adhi Harmoko [1 ]
Kharisma, Sulton [2 ]
机构
[1] Univ Indonesia, Fac Math & Nat Sci, Dept Phys, Depok, Indonesia
[2] Agcy Meteorol Climatol & Geophys, Jakarta, Indonesia
关键词
aviation; imaging; multispectral; satellite; remote sensing; volcanic ash; CLOUDS;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Volcanic ash produced by eruptions has been significantly dangerous towards aviation. The necessity of volcanic ash early warning system distribution is crucial to reduce casualties on aircraft accident. In this paper, some techniques of volcanic ash detection were compared to find the proper algorithm to visualize the volcanic ash distribution. The multispectral image was acquired from the geostationary satellite (Himawari - 8 satellite) in specific time observation. The reference data were collected from the MODIS sensor in the Aqua satellite to monitor the volcanic ash distribution at the same time and place. The first method is to generate the value of brightness temperature differences (BTD) at 11 mu m and 12 mu m wavelengths. The second method is conducted by inserting 3.9 mu m information from the product of three-band volcanic ash known as (TVAP). The third method is a combination of the first and second method while the last method utilizes RGB composite color combination from several bands of Himawari - 8. The reference data collected by MODIS Observation at 06.00 UTC. The BTD technique unable to detect low-intensity volcanic ash, while combining it with the TVAP method can increase the standard method performance. Based on expert judgment, BTD technique has a good performance for thick volcanic ash although unable to detect thin volcanic ash distribution. Three-band Volcanic Ash Product (TVAP) method could detect thick and thin volcanic ash. The combination of BTD and TVAP method has an excellent result to observe volcanic ash distribution, but the result tends to overestimate like TVAP distribution. RGB Methods from JMA Configuration have the same pattern and distribution of volcanic ash as MODIS observation. Based on the study results, BTD, TVAP, and RGB composite methods can produce good results compared to MODIS imagery for monitoring the volcanic ash distribution.
引用
收藏
页码:119 / 122
页数:4
相关论文
共 50 条
  • [41] A New Detection Method of Volcanic Ash Cloud Based on MODIS Image
    Yin, Jing-Yuan
    Dong, Jiang-Shan
    Li, Cheng-Fan
    Zhao, Jun-Juan
    JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING, 2015, 43 (02) : 429 - 437
  • [42] A Novel Method of Multispectral Imagery Registration Based on Minor and Noise Component Criterion
    Cui Jinhui
    Yang Xuesong
    2012 INTERNATIONAL WORKSHOP ON INFORMATION AND ELECTRONICS ENGINEERING, 2012, 29 : 2859 - 2863
  • [43] Data Reduction and Deep-Learning Based Recovery for Geospatial Visualization and Satellite Imagery
    Tasnim, Jarin
    Mondal, Debajyoti
    2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2020, : 5276 - 5285
  • [44] An ASIFT-Based Local Registration Method for Satellite Imagery
    Wang, Xiangjun
    Li, Yang
    Wei, Hong
    Liu, Feng
    REMOTE SENSING, 2015, 7 (06) : 7044 - 7061
  • [45] Comparing spectral angle mapper and object based approach for land use classification from multispectral imagery
    Huang, Jingfeng
    Belal, A. A.
    PROGRESS OF INFORMATION TECHNOLOGY IN AGRICULTURE, 2007, : 689 - 694
  • [46] Deep learning-based object recognition in multispectral satellite imagery for real-time applications
    Povilas Gudžius
    Olga Kurasova
    Vytenis Darulis
    Ernestas Filatovas
    Machine Vision and Applications, 2021, 32
  • [47] Deep learning-based object recognition in multispectral satellite imagery for real-time applications
    Gudzius, Povilas
    Kurasova, Olga
    Darulis, Vytenis
    Filatovas, Ernestas
    MACHINE VISION AND APPLICATIONS, 2021, 32 (04)
  • [48] A multispectral image segmentation approach for object-based image classification of high resolution satellite imagery
    Byun, Young Gi
    Han, You Kyung
    Chae, Tae Byeong
    KSCE JOURNAL OF CIVIL ENGINEERING, 2013, 17 (02) : 486 - 497
  • [49] A multispectral image segmentation approach for object-based image classification of high resolution satellite imagery
    Young Gi Byun
    You Kyung Han
    Tae Byeong Chae
    KSCE Journal of Civil Engineering, 2013, 17 : 486 - 497
  • [50] A simple method for detection and counting of oil palm trees using high-resolution multispectral satellite imagery
    Santoso, Heri
    Tani, Hiroshi
    Wang, Xiufeng
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2016, 37 (21) : 5122 - 5134