Monitoring of maize lodging using multi-temporal Sentinel-1 SAR data

被引:50
|
作者
Shu, Meiyan [1 ,2 ,4 ]
Zhou, Longfei [1 ,2 ,3 ]
Gu, Xiaohe [1 ,2 ]
Ma, Yuntao [4 ]
Sun, Qian [1 ,2 ,3 ]
Yang, Guijun [1 ,2 ,3 ]
Zhou, Chengquan [1 ,2 ,3 ]
机构
[1] Beijing Res Ctr Informat Technol Agr, Key Lab Quantitat Remote Sensing Agr, Minist Agr, Beijing 100097, Peoples R China
[2] Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China
[3] Shandong Univ Sci & Technol, Coll Geomat, Qingdao 266590, Peoples R China
[4] China Agr Univ, Coll Land Sci & Technol, Beijing 100094, Peoples R China
基金
中国国家自然科学基金; 北京市自然科学基金;
关键词
Maize; Lodging; Polarization combination; Plant height; Lodging angle; GRAIN QUALITY; RICE; YIELD; RETRIEVAL; CANOPY; INDEX; WHEAT;
D O I
10.1016/j.asr.2019.09.034
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
Lodging is a common phenomenon in maize production, which seriously affects its yield, quality, and mechanical harvesting capacity. With good penetrating power, satellite radar can monitor crop growth even under cloudy weather conditions. In this study, a method based on the change in plant height before and after lodging in maize is proposed to calculate the lodging angle and monitor the lodging degree by using dual-polarization Sentinel-1A data. The results show that the optimal sensitive polarization combinations of maize plant height before and after lodging are VH/VV and VV, respectively. The lodging angle is calculated using the plant height inversion results before and after lodging. The overall accuracy of classifying lodging grade of maize is 67%. The proposed model based on lodging angle could effectively mapped the maize lodging range on a regional scale and classify the lodging grades. (C) 2019 COSPAR. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:470 / 480
页数:11
相关论文
共 50 条
  • [41] Backscatter Characteristics Analysis for Flood Mapping Using Multi-Temporal Sentinel-1 Images
    Huang, Minmin
    Jin, Shuanggen
    REMOTE SENSING, 2022, 14 (15)
  • [42] A methodology for mapping annual flood extent using multi-temporal Sentinel-1 imagery
    McCormack, T.
    Campanya, J.
    Naughton, O.
    REMOTE SENSING OF ENVIRONMENT, 2022, 282
  • [43] Assessing lodging damage of jute crop due to super cyclone Amphan using multi-temporal Sentinel-1 and Sentinel-2 data over parts of West Bengal, India
    Abhishek Chakraborty
    P. Srikanth
    C. S. Murthy
    P. V. N. Rao
    Santanu Chowdhury
    Environmental Monitoring and Assessment, 2021, 193
  • [44] ESTIMATION OF MAIZE BIOMASS COMPONENTS FROM SENTINEL-1 SAR DATA USING MULTI-TARGET REGRESSORS
    Xu, Chi
    Ding, Yanling
    Dai, Zewen
    2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022), 2022, : 1392 - 1395
  • [45] LAKE DETECTION WITH SENTINEL-1 DATA USING A GRAB-CUT METHOD AND ITS MULTI-TEMPORAL EXTENSION
    Gasnier, Nicolas
    Denis, Loic
    Fjortoft, Roger
    Liege, Frederic
    Tupin, Florence
    2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022), 2022, : 2175 - 2178
  • [46] Recent changes in two outlet glaciers in the Antarctic Peninsula using multi-temporal Landsat and Sentinel-1 data
    Simoes, Carolina L.
    Rosa, Katia K.
    Simoes, Jefferson C.
    Vieira, Rosemary
    Costa, Rafaela M.
    Silva, Aline B.
    GEOCARTO INTERNATIONAL, 2020, 35 (11) : 1233 - 1244
  • [47] Evaluating the potential of multi-temporal Sentinel-1 and Sentinel-2 data for regional mapping of olive trees
    Akcay, Haydar
    Aksoy, Samet
    Kaya, Sinasi
    Sertel, Elif
    Dash, Jadu
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2023, 44 (23) : 7338 - 7364
  • [48] MONITORING WATER HYACINTH IN KUTTANAD, INDIA USING SENTINEL-1 SAR DATA
    Simpson, Morgan
    Marino, Armando
    Prabhu, G. Nagendra
    Bhowmik, Deepayan
    Rupavatharam, Srikanth
    Datta, Aviraj
    Kleczkowski, Adam
    Sujeetha, J. Alice R. P.
    Maharaj, Savitri
    2020 IEEE INDIA GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (INGARSS), 2020, : 13 - 16
  • [49] Soil Moisture Retrievals Using Multi-Temporal Sentinel-1 Data over Nagqu Region of Tibetan Plateau
    Yang, Mengying
    Wang, Hongquan
    Tong, Cheng
    Zhu, Luyao
    Deng, Xiaodong
    Deng, Jinsong
    Wang, Ke
    REMOTE SENSING, 2021, 13 (10)
  • [50] Deformation monitoring using Persistent Scatterer Interferometry and Sentinel-1 SAR data
    Devanthery, Nuria
    Crosetto, Michele
    Cuevas-Gonzalez, Maria
    Monserrat, Oriol
    Barra, Anna
    Crippa, Bruno
    INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS/INTERNATIONAL CONFERENCE ON PROJECT MANAGEMENT/INTERNATIONAL CONFERENCE ON HEALTH AND SOCIAL CARE INFORMATION SYSTEMS AND TECHNOLOGIES, CENTERIS/PROJMAN / HCIST 2016, 2016, 100 : 1121 - 1126