Evaluation of SMAP/Sentinel 1 High-Resolution Soil Moisture Data to Detect Irrigation over Agricultural Domain

被引：0
|
作者：
Jalilvand, Ehsan [1 ]
Abolafia-Rosenzweig, Ronnie [2 ]
Tajrishy, Masoud [3 ]
Das, Narendra [4 ]
机构：
[1] Sharif University of Technology, Tehran, Iran
[2] Research Applications Laboratory, National Center for Atmospheric Research, Boulder,CO, United States
[3] Department of Civil and Environmental Engineering, Sharif University of Technology, Tehran, Iran
[4] Department of Civil and Environmental Engineering, Department of Biosystem and Agricultural Engineering, Michigan State University, Michigan,MI, United States
来源：
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | 2021年 / 14卷
关键词：
All Open Access; Gold;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Soil moisture
引用
收藏
页码：10733 / 10747
相关论文
共 50 条
  • [21] Retrieving the irrigation actually applied at district scale: Assimilating high-resolution Sentinel-1-derived soil moisture data into a FAO-56-based model
    Laluet, Pierre
    Olivera-Guerra, Luis Enrique
    Altes, Victor
    Paolini, Giovanni
    Ouaadi, Nadia
    Rivalland, Vincent
    Jarlan, Lionel
    Villar, Josep Maria
    Merlin, Olivier
    CELLULAR SIGNALLING, 2024, 117
  • [22] Integration of Sentinel-1A Radar and SMAP Radiometer for Soil Moisture Retrieval over Vegetated Areas
    Arab, Saeed
    Easson, Greg
    Ghaffari, Zahra
    SENSORS, 2024, 24 (07)
  • [23] Evaluation of statistical methods for infilling missing values in high-resolution soil moisture data
    Dumedah, Gift
    Coulibaly, Paulin
    JOURNAL OF HYDROLOGY, 2011, 400 (1-2) : 95 - 102
  • [24] High-Resolution Mapping of Soil Moisture by AMSR2 Data Disaggregation Based on Sentinel-1 and Machine Learning
    Santi, Emanuele
    Baroni, Fabrizio
    Fontanelli, Giacomo
    Palchetti, Enrico
    Paloscia, Simonetta
    Pettinato, Simone
    Pilia, Simone
    Ramat, Giuliano
    Santurri, Leonardo
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2024, 17 : 15077 - 15088
  • [25] Downscaling CLDAS Soil Moisture Product by Integrating Sentinel-1 and Sentinel-2 Data over Agricultural Area
    Ma, Hongzhang
    Sun, Shuyi
    Wang, Zhaowei
    Jiang, Yandi
    Liu, Sumei
    CANADIAN JOURNAL OF REMOTE SENSING, 2022, 48 (06) : 737 - 746
  • [26] High resolution mapping of soil moisture in agriculture based on Sentinel-1 interferometric data
    Conde, Vasco
    Catalao, Joao
    Nico, Giovanni
    Benevides, Pedro
    REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY XX, 2018, 10783
  • [27] The Evaluation of SMAP Enhanced Soil Moisture Products Using High-Resolution Model Simulations and In-Situ Observations on the Tibetan Plateau
    Li, Chengwei
    Lu, Hui
    Yang, Kun
    Han, Menglei
    Wright, Jonathon S.
    Chen, Yingying
    Yu, Le
    Xu, Shiming
    Huang, Xiaomeng
    Gong, Wei
    REMOTE SENSING, 2018, 10 (04)
  • [28] Monitoring surface soil moisture and freeze-thaw state with the high-resolution radar of the Soil Moisture Active/Passive (SMAP) mission
    Kim, Seungbum
    van Zyl, Jakob
    McDonald, Kyle
    Njoku, Eni
    2010 IEEE RADAR CONFERENCE, 2010, : 735 - 739
  • [29] Exploiting High-Resolution Remote Sensing Soil Moisture to Estimate Irrigation Water Amounts over a Mediterranean Region
    Dari, Jacopo
    Brocca, Luca
    Quintana-Segui, Pere
    Escorihuela, Maria Jose
    Stefan, Vivien
    Morbidelli, Renato
    REMOTE SENSING, 2020, 12 (16)
  • [30] A Spatio-Temporal Data Fusion Algorithm for Estimating High-Resolution Soil Moisture In Agricultural Regions
    Chakrabarti, Subit
    Liu, Pang-Wei
    Judge, Jasmeet
    Rangarajan, Anand
    De Roo, Roger
    Bindlish, Rajat
    Colliander, Andreas
    Misra, Sidharth
    Tripp, Scott
    Latham, Barron
    Williamson, Ross
    Ramos, Isaac
    Jackson, Thomas
    England, Anthony
    Ranka, Sanjay
    Yueh, Simon
    2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2017, : 2495 - 2498
12345