Multi-Annual Evaluation of Time Series of Sentinel-1 Interferometric Coherence as a Tool for Crop Monitoring

被引:9
|
作者
Villarroya-Carpio, Arturo [1 ]
Lopez-Sanchez, Juan M. [1 ]
机构
[1] Univ Alicante, Inst Comp Res, Alicante 03080, Spain
关键词
crop monitoring; vegetation index; Sentinel-1; synthetic aperture radar (SAR); interferometry; coherence; Sentinel-2; NDVI; RETRIEVAL; PARAMETERS; HEIGHT;
D O I
10.3390/s23041833
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Interferometric coherence from SAR data is a tool used in a variety of Earth observation applications. In the context of crop monitoring, vegetation indices are commonly used to describe crop dynamics. The most frequently used vegetation indices based on radar data are constructed using the backscattered intensity at different polarimetric channels. As coherence is sensitive to the changes in the scene caused by vegetation and its evolution, it may potentially be used as an alternative tool in this context. The objective of this work is to evaluate the potential of using Sentinel-1 interferometric coherence for this purpose. The study area is an agricultural region in Sevilla, Spain, mainly covered by 18 different crops. Time series of different backscatter-based radar vegetation indices and the coherence amplitude for both VV and VH channels from Sentinel-1 were compared to the NDVI derived from Sentinel-2 imagery for a 5-year period, from 2017 to 2021. The correlations between the series were studied both during and outside the growing season of the crops. Additionally, the use of the ratio of the two coherences measured at both polarimetric channels was explored. The results show that the coherence is generally well correlated with the NDVI across all seasons. The ratio between coherences at each channel is a potential alternative to the separate channels when the analysis is not restricted to the growing season of the crop, as its year-long temporal evolution more closely resembles that of the NDVI. Coherence and backscatter can be used as complementary sources of information, as backscatter-based indices describe the evolution of certain crops better than coherence.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] Sentinel-1 interferometric coherence and backscattering analysis for crop monitoring
    Nasirzadehdizaji, Rouhollah
    Cakir, Ziyadin
    Sanli, Fusun Balik
    Abdikan, Saygin
    Pepe, Antonio
    Calo, Fabiana
    [J]. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2021, 185
  • [2] Time-Series of Sentinel-1 Interferometric Coherence and Backscatter for Crop-Type Mapping
    Mestre-Quereda, Alejandro
    Lopez-Sanchez, Juan M.
    Vicente-Guijalba, Fernando
    Jacob, Alexander W.
    Engdahl, Marcus E.
    [J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2020, 13 : 4070 - 4084
  • [3] SENSITIVITY OF SENTINEL-1 INTERFEROMETRIC COHERENCE TO CROP STRUCTURE AND SOIL MOISTURE
    Palmisano, Davide
    Satalino, Giuseppe
    Balenzano, Anna
    Bovenga, Fabio
    Mattia, Francesco
    Rinaldi, Michele
    Ruggieri, Sergio
    Skriver, Henning
    Davidson, Malcolm W. J.
    Cartus, Oliver
    Wegmuller, Urs
    [J]. 2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019), 2019, : 6219 - 6222
  • [4] Sentinel-1 Time Series for Crop Identification in the Framework of the Future CAP Monitoring
    Beriaux, Emilie
    Jago, Alban
    Lucau-Danila, Cozmin
    Planchon, Viviane
    Defourny, Pierre
    [J]. REMOTE SENSING, 2021, 13 (14)
  • [5] Assessment of interferometric coherence contribution to corn and soybean mapping with Sentinel-1 data time series
    Amherdt, Sebastian
    Di Leo, Nestor Cristian
    Pereira, Ayelen
    Cornero, Cecilia
    Pacino, Maria Cristina
    [J]. GEOCARTO INTERNATIONAL, 2022,
  • [6] SENTINEL-1 TOPS INTERFEROMETRIC TIME SERIES RESULTS AND VALIDATION
    Prats-Iraola, Pau
    Nannini, Matteo
    Yague-Martinez, Nestor
    Scheiber, Rolf
    Minati, Federico
    Vecchioli, Francesco
    Costantini, Mario
    Borgstrom, Sven
    De Martino, Prospero
    Siniscalchi, Valeria
    Walter, Thomas
    Nikkhoo, Mehdi
    Foumelis, Michael
    Desnos, Yves-Louis
    [J]. 2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2016, : 3894 - 3897
  • [7] Monitoring Irrigation Events and Crop Dynamics Using Sentinel-1 and Sentinel-2 Time Series
    Ma, Chunfeng
    Johansen, Kasper
    McCabe, Matthew F.
    [J]. REMOTE SENSING, 2022, 14 (05)
  • [8] Sentinel-1 interferometric coherence as a vegetation index for agriculture
    Villarroya-Carpio, Arturo
    Lopez-Sanchez, Juan M.
    Engdahl, Marcus E.
    [J]. REMOTE SENSING OF ENVIRONMENT, 2022, 280
  • [9] Detection of Crop Seeding and Harvest through Analysis of Time-Series Sentinel-1 Interferometric SAR Data
    Shang, Jiali
    Liu, Jiangui
    Poncos, Valentin
    Geng, Xiaoyuan
    Qian, Budong
    Chen, Qihao
    Dong, Taifeng
    Macdonald, Dan
    Martin, Tim
    Kovacs, John
    Walters, Dan
    [J]. REMOTE SENSING, 2020, 12 (10)
  • [10] CROP TYPE MAPPING BASED ON SENTINEL-1 BACKSCATTER TIME SERIES
    Arias, M.
    Campo-Bescos, M. A.
    Alvarez-Mozos, J.
    [J]. IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2018, : 6623 - 6626