Change Detection Based on the Coefficient of Variation in SAR Time-Series of Urban Areas

被引:25
|
作者
Koeniguer, Elise Colin [1 ]
Nicolas, Jean-Marie [2 ]
机构
[1] Univ Paris Saclay, Onera, F-91123 Palaiseau, France
[2] Inst Polytech Paris, Telecom Paris, LCTI, F-91120 Paris, France
关键词
multitemporal; change detection; time series; SAR; coefficient of variation; IMAGE;
D O I
10.3390/rs12132089
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper discusses change detection in SAR time-series. First, several statistical properties of the coefficient of variation highlight its pertinence for change detection. Subsequently, several criteria are proposed. The coefficient of variation is suggested to detect any kind of change. Furthermore, several criteria that are based on ratios of coefficients of variations are proposed to detect long events, such as construction test sites, or point-event, such as vehicles. These detection methods are first evaluated on theoretical statistical simulations to determine the scenarios where they can deliver the best results. The simulations demonstrate the greater sensitivity of the coefficient of variation to speckle mixtures, as in the case of agricultural plots. Conversely, they also demonstrate the greater specificity of the other criteria for the cases addressed: very short event or longer-term changes. Subsequently, detection performance is assessed on real data for different types of scenes and sensors (Sentinel-1, UAVSAR). In particular, a quantitative evaluation is performed with a comparison of our solutions with baseline methods. The proposed criteria achieve the best performance, with reduced computational complexity. On Sentinel-1 images containing mainly construction test sites, our best criterion reaches a probability of change detection of 90% for a false alarm rate that is equal to 5%. On UAVSAR images containing boats, the criteria proposed for short events achieve a probability of detection equal to 90% of all pixels belonging to the boats, for a false alarm rate that is equal to 2%.
引用
收藏
页数:23
相关论文
共 50 条
  • [31] Displacement Estimation and Monitoring Experiments Based on Time-series SAR Imaging
    Wang, Yanping
    Hong, Wen
    Qi, Yaolong
    Yang, Xiaolin
    Ma, Haitao
    2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2016, : 28 - 31
  • [32] COEFFICIENT OF DIRECTIONAL CORRELATION FOR TIME-SERIES ANALYSES
    STRAHAN, RF
    PSYCHOLOGICAL BULLETIN, 1971, 76 (03) : 211 - &
  • [33] MODELING TIME-SERIES WITH CALENDAR VARIATION
    BELL, WR
    HILLMER, SC
    JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1983, 78 (383) : 526 - 534
  • [34] TIME-SERIES VARIATION IN DIVIDEND PRICING
    EADES, KM
    HESS, PJ
    KIM, EH
    JOURNAL OF FINANCE, 1994, 49 (05): : 1617 - 1638
  • [35] Anomaly Detection Approach for Urban Sensing Based on Credibility and Time-Series Analysis Optimization Model
    Zhang, Hong
    Li, Zhanming
    IEEE ACCESS, 2019, 7 : 49102 - 49110
  • [36] OUTLIERS DETECTION IN TIME-SERIES
    LEE, AH
    HUI, YV
    JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 1993, 45 (1-2) : 77 - 95
  • [37] ON OUTLIER DETECTION IN TIME-SERIES
    LJUNG, GM
    JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-METHODOLOGICAL, 1993, 55 (02): : 559 - 567
  • [38] A Time-series based Prediction Analysis of Rainfall Detection
    Varghese, Lince Rachel
    Vanitha, K.
    PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON INVENTIVE COMPUTATION TECHNOLOGIES (ICICT-2020), 2020, : 513 - 518
  • [39] Characterizing urban growth in Vientiane from 2000 to 2019 using time-series optical and SAR-based estimates of urban land
    Huang, Chong
    Zhang, Chenchen
    INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2022, 109
  • [40] Deformation Detection and Attribution Analysis of Urban Areas near Dianchi Lake in Kunming Using the Time-Series InSAR Technique
    Wang, Junyu
    Li, Menghua
    Yang, Mengshi
    Tang, Bo-Hui
    APPLIED SCIENCES-BASEL, 2022, 12 (19):