Potential of X-Band Images from High-Resolution Satellite SAR Sensors to Assess Growth and Yield in Paddy Rice

被引:28
作者
Inoue, Yoshio [1 ]
Sakaiya, Eiji [2 ]
Wang, Cuizhen [3 ]
机构
[1] Natl Inst Agroenvironm Sci, Tsukuba, Ibaraki 3058604, Japan
[2] Aomori ITC Agr Res Inst, Kuroishi, Aomori 0360522, Japan
[3] Univ S Carolina, Dept Geog, Columbia, SC 29208 USA
来源
REMOTE SENSING | 2014年 / 6卷 / 07期
关键词
backscattering; COSMO-SkyMed; grain yield; microwave; paddy rice; synthetic aperture radar (SAR); TerraSAR-X; X-band; SOIL SURFACE PARAMETERS; LEAF-AREA INDEX; TERRASAR-X; BACKSCATTERING COEFFICIENTS; BIOPHYSICAL VARIABLES; TIME-SERIES; RADAR DATA; RETRIEVAL; MICROWAVE; CLASSIFICATION;
D O I
10.3390/rs6075995
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The comprehensive relationship of backscattering coefficient (sigma(0)) values from two current X-band SAR sensors (COSMO-SkyMed and TerraSAR-X) with canopy biophysical variables were investigated using the SAR images acquired at VV polarization and shallow incidence angles. The difference and consistency of the two sensors were also examined. The chrono-sequential change of sigma(0) in rice paddies during the transplanting season revealed that sigma(0) reached the value of nearby water surfaces a day before transplanting, and increased significantly just after transplanting event (3 dB). Despite a clear systematic shift (6.6 dB) between the two sensors, the differences in sigma(0) between target surfaces and water surfaces in each image were comparable in both sensors. Accordingly, an image-based approach using the "water-point" was proposed. It would be useful especially when absolute sigma(0) values are not consistent between sensors and/or images. Among the various canopy variables, the panicle biomass was found to be best correlated with X-band sigma(0). X-band SAR would be promising for direct assessments of rice grain yields at regional scales from space, whereas it would have limited capability to assess the whole-canopy variables only during the very early growth stages. The results provide a clear insight on the potential capability of X-band SAR sensors for rice monitoring.
引用
收藏
页码:5995 / 6019
页数:25
相关论文
共 50 条
  • [41] AUTOMATED INFORMATION EXTRACTION FROM HIGH RESOLUTION SAR IMAGES: TERRASAR-X INTERPRETATION APPLICATIONS
    Schwarz, G.
    Soccorsi, M.
    Chaabouni-Chouayakh, H.
    Espinoza, D.
    Cerra, D.
    Rodriguez, F.
    Datcu, M.
    2009 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-5, 2009, : 3057 - 3060
  • [42] Generation of wide-swath and high-resolution SAR images from multichannel small spaceborne SAR systems
    Li, ZF
    Wang, HY
    Su, T
    Bao, Z
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2005, 2 (01) : 82 - 86
  • [43] Investigating the Relationship between X-Band SAR Data from COSMO-SkyMed Satellite and NDVI for LAI Detection
    Capodici, Fulvio
    D'Urso, Guido
    Maltese, Antonino
    REMOTE SENSING, 2013, 5 (03) : 1389 - 1404
  • [44] Vegetation abundance on the Barton Peninsula, Antarctica: estimation from high-resolution satellite images
    Shin, Jung-Il
    Kim, Hyun-Cheol
    Kim, Sang-Il
    Hong, Soon Gyu
    POLAR BIOLOGY, 2014, 37 (11) : 1579 - 1588
  • [45] Road detection from high-resolution satellite images using artificial neural networks
    Mokhtarzade, M.
    Zoej, M. J. Valadan
    INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2007, 9 (01): : 32 - 40
  • [46] On the scale-dependent propagation of hydrologic uncertainty using high-resolution X-band radar rainfall estimates
    Vieux, B. E.
    Imgarten, J. M.
    ATMOSPHERIC RESEARCH, 2012, 103 : 96 - 105
  • [47] NESEA-Rice10: high-resolution annual paddy rice maps for Northeast and Southeast Asia from 2017 to 2019
    Han, Jichong
    Zhang, Zhao
    Luo, Yuchuan
    Cao, Juan
    Zhang, Liangliang
    Cheng, Fei
    Zhuang, Huimin
    Zhang, Jing
    Tao, Fulu
    EARTH SYSTEM SCIENCE DATA, 2021, 13 (12) : 5969 - 5986
  • [48] Building Extraction From High-Resolution Multispectral and SAR Images Using a Boundary-Link Multimodal Fusion Network
    Zhao, Zhe
    Zhao, Boya
    Wu, Yuanfeng
    He, Zutian
    Gao, Lianru
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2025, 18 : 3864 - 3878
  • [49] A Very High-Resolution Urban Green Space from the Fusion of Microsatellite, SAR, and MSI Images
    Ramdani, Fatwa
    REMOTE SENSING, 2024, 16 (08)
  • [50] Accurately estimated the complex relative permittivity of materials using a super high-resolution algorithm at X-band microwave propagation
    Manh Cuong Ho
    Trong-Hieu Le
    Le Cuong Nguyen
    ELECTROMAGNETICS, 2020, 40 (01) : 1 - 12