THE APPLICATION OF PYRAMID LUCAS-KANADE OPTICAL FLOW METHOD FOR TRACKING RAIN MOTION USING HIGH-RESOLUTION RADAR IMAGES

被引:4
|
作者
Hambali, Roby [1 ]
Legono, Djoko [2 ]
Jayadi, Rachmad [2 ]
机构
[1] Univ Bangka Belitung, Dept Civil Engn, Kampus Terpadu UBB, Bangka, Indonesia
[2] Univ Gadjah Mada, Dept Civil & Environm Engn, JL Graf 2, Yogyakarta, Indonesia
来源
关键词
Rain motion; displacement vector; optical flow; nowcastig; X-band MP radar; PRECIPITATION;
D O I
10.11113/jurnalteknologi.v83.14494
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Short-duration rainfall characteristics in the form of certain intensity, time, and spatial distribution become valuable contribution for lahar flow disaster mitigation in a mountainous region. Due to mitigation purpose, such information can be provided through the rainfall nowcasting process. One of the promising rainfall nowcasting applications is the extrapolation-based method. Rain motion tracking is a crucial part of the rainfall nowcasting based on this method. This paper discusses the application of Pyramid Lucas-Kanade Optical Flow (PLKOF) method on the rain motion tracking analysis using 150x150m resolution radar image. The study of rain motion tracking is carried out using 112 successive rainfall images with 10-minutes time interval originating from Mt. Merapi X-band multiparameter radar. The rainfall movement patterns in short duration are presented in the displacement vector (u,v) images and scatter diagrams of rain motions at x- and y-directions. From the simulations, it was found that the average displacement of rain motions in the Mt. Merapi region is 9 pixels (8.3 km/h) with the dominant direction is northeast. The results show that PLKOF is relatively good at detecting small displacements, yet unable to identify the occurrence of rain growth and decay properly. The ability of PLKOF method in predicting the position of rain cell displacement is satisfied as indicated by the POD, CSI, and FAR indexes.
引用
收藏
页码:105 / 115
页数:11
相关论文
共 50 条
  • [1] A Motion-Based Tracking System Using the Lucas-Kanade Optical Flow Method
    Leonida, Karl Leyven
    Sevilla, Karla Veronica
    Mantises, Cyrel O.
    2022 14TH INTERNATIONAL CONFERENCE ON COMPUTER AND AUTOMATION ENGINEERING (ICCAE 2022), 2022, : 86 - 90
  • [2] Moving Target Detection and Tracking Based on Pyramid Lucas-Kanade Optical Flow
    Wang, Zhen
    Yang, Xiaojun
    2018 IEEE 3RD INTERNATIONAL CONFERENCE ON IMAGE, VISION AND COMPUTING (ICIVC), 2018, : 66 - 69
  • [3] Lucas-Kanade Optical Flow Based Camera Motion Estimation Approach
    Meng, Zelin
    Kong, Xiangbo
    Meng, Lin
    Tomiyama, Hiroyuki
    2019 INTERNATIONAL SOC DESIGN CONFERENCE (ISOCC), 2019, : 77 - 78
  • [4] Measurement of ocular torsion using iterative Lucas-Kanade optical flow method
    Lee, I. B.
    Park, K. S.
    2005 27TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-7, 2005, : 6433 - 6436
  • [5] APPLICATION OF LUCAS-KANADE DENSE FLOW FOR TERRAIN MOTION IN LANDSLIDE MONITORING APPLICATION
    Yordanov, V.
    Truong, X. Q.
    Corti, M.
    Longoni, L.
    Brovelli, M. A.
    GEOSPATIAL WEEK 2023, VOL. 48-1, 2023, : 1089 - 1096
  • [6] Subpixel-Based Precipitation Nowcasting with the Pyramid Lucas-Kanade Optical Flow Technique
    Li, Ling
    He, Zhengwei
    Chen, Sheng
    Mai, Xiongfa
    Zhang, Asi
    Hu, Baoqing
    Li, Zhi
    Tong, Xinhua
    ATMOSPHERE, 2018, 9 (07):
  • [7] Moving Object Tracking Method Based on Improved Lucas-Kanade Sparse Optical Flow Algorithm
    Li Dan
    Jiang Dai-hong
    Bao Rong
    Sun Jin-ping
    Zhao Wen-jing
    Wang Chao
    2017 INTERNATIONAL SMART CITIES CONFERENCE (ISC2), 2017,
  • [8] A New Motion Estimation Method using Modified Hexagonal Search Algorithm and Lucas-Kanade Optical Flow Technique
    Ghoul, Khalid
    Zaidi, Sofiane
    Laboudi, Zakaria
    ADVANCES IN ELECTRICAL AND COMPUTER ENGINEERING, 2024, 24 (01) : 33 - 40
  • [9] Large Displacement Detection Using Improved Lucas-Kanade Optical Flow
    Al-Qudah, Saleh
    Yang, Mijia
    SENSORS, 2023, 23 (06)
  • [10] Robust nose detection and tracking using GentleBoost and improved Lucas-Kanade optical flow algorithms
    Ren, Xiaobo
    Song, Jiatao
    Ying, Hongwei
    Zhu, Yam
    Qiu, Xuena
    ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS: WITH ASPECTS OF THEORETICAL AND METHODOLOGICAL ISSUES, 2007, 4681 : 1240 - +