Monitoring the impacts of waterlogging on winter wheat using high spatial resolution satellite data

被引:0
|
作者
Liu, Weiwei [1 ]
Huang, Jingfeng [1 ]
Song, Xiaodong [1 ]
Wei, Chuanwen [2 ]
Zhang, Dongdong [2 ]
Wang, Xiuzhen [3 ]
Zhang, Lijie [3 ]
Zhou, Zhen [4 ]
Han, Jiahui [4 ]
Chen, Yaoliang [5 ]
机构
[1] Zhejiang Univ, Inst Remote Sensing & Informat Technol Applicat, Hangzhou, Zhejiang, Peoples R China
[2] Key Lab Agr Remote Sensing & Informat Syst, Hangzhou, Zhejiang, Peoples R China
[3] Hangzhou Normal Univ Hangzhou, Inst Remote Sensing & Earth Sci, Hangzhou, Zhejiang, Peoples R China
[4] Coll Environm & Resource Sci, Minist Educ, Key Lab Environm Remediat & Ecol Hlth, Hangzhou, Zhejiang, Peoples R China
[5] Zhejiang Univ, Sch Publ Affairs, Dept Land Management, Hangzhou, Zhejiang, Peoples R China
关键词
waterlogging; remote sensing; winter wheat; EMPIRICAL LINE METHOD; REMOTE-SENSING DATA; METEOROLOGICAL DROUGHT; REFLECTANCE; MULTISENSOR; RETRIEVAL; INDEXES; BARLEY; YIELD;
D O I
暂无
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
Waterlogging, including flooding, is one of the serious agricultural disasters for winter wheat in the middle and lower reaches of the Yangtze River region, especially during the spring. It's of great practical value to discriminating the impact of waterlogging and flooding on winter wheat efficiently in the field. In this study, we combined the field campaign and satellite remote sensing data to discriminate the impact of waterlogging and flooding on winter wheat during the growing stages in the spring. The field experiment was carried out with three treatments, i.e., waterlogging (WL), flooding (FL)(waterlogging with 3 cm water layer above the ground) and contrast (CK), and two varieties, i.e., YM14 and YM18. The phenological stages includes seeding and tillering (ST) from 7 to 27 January and jointing and booting (JB) from 12 March to 1 April, respectively. For each treatment, three samples with an area of 0.25 m(2) were randomly determined and collected. High resolution satellite data, i.e., WorldView2, Pleiades and SPOT were also obtained. We proposed a method to calibrate the collection of high resolution remote sensing data. We used a measurement, namely the M, to differentiate the different waterlogging treatments. The results showed that the yield of winter wheat under different treatments for both varieties in ST and JB had significant differences. It showed that the flooding treatment could be discriminated from its CK and waterlogging treatment for YM14, and the waterlogging treatment of YM18 could be discriminated from its CK 16 days after ST treatment. The treatment in ST showed more lasting impacts on both YM14 and YM18. Compared with ST, the treatments in JB had more severe impacts on winter wheat growth. The flooding treatment of YM14 was differentiable from its CK and waterlogging treatment before the end of JB treatment, earlier than YM18. We concluded that both of the treatments in ST and JB periods had adverse impacts on YM14 and YM18, especially during ST period.
引用
下载
收藏
页码:197 / 201
页数:5
相关论文
共 50 条
  • [31] Monitoring the change of urban wetland using high spatial resolution remote sensing data
    Zhou, Huiping
    Jiang, Hong
    Zhou, Guomo
    Song, Xiaodong
    Yu, Shuquan
    Chang, Jie
    Liu, Shirong
    Jiang, Zishan
    Jiang, Bo
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2010, 31 (07) : 1717 - 1731
  • [32] Monitoring tropical deforestation processing high frequency and high resolution satellite data
    Begue, A
    Zanardo, C
    Imbernon, J
    Deshayes, M
    EARTH SURFACE REMOTE SENSING, 1997, 3222 : 261 - 272
  • [33] Mapping and Monitoring Urban Ecosystem Services Using Multitemporal High-Resolution Satellite Data
    Haas, Jan
    Ban, Yifang
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2017, 10 (02) : 669 - 680
  • [34] Monitoring of Fallow Land in Southern Palatinate Forest Using High Resolution Satellite and LIDAR Data
    Bachofer, Felix
    Hochschild, Volker
    Schuler, Helmut
    PHOTOGRAMMETRIE FERNERKUNDUNG GEOINFORMATION, 2010, (05): : 355 - 361
  • [35] Long term monitoring and assessment of desertification processes using medium & high resolution satellite data
    Christian, Binal A.
    Dhinwa, P. S.
    Ajai
    APPLIED GEOGRAPHY, 2018, 97 : 10 - 24
  • [36] MONITORING OF GREEN AREAS IN THE CENTRAL PART OF PLOVDIV CITY USING HIGH RESOLUTION SATELLITE DATA
    Nedkov, Rumen
    Roumenina, Eugenia
    Jelev, Georgi
    AEROSPACE RESEARCH IN BULGARIA, 2005, 19 : 91 - 94
  • [37] Monitoring quality of winter wheat based on the HJ satellite images
    Wang Yan
    Li Cunjun
    Guo Wenshan
    Tan Changwei
    Jin Xiuliang
    Cui Bei
    Tong Lu
    2012 FIRST INTERNATIONAL CONFERENCE ON AGRO-GEOINFORMATICS (AGRO-GEOINFORMATICS), 2012, : 244 - 248
  • [38] Validating the geometric accuracy of high spatial resolution multispectral satellite data
    Unger, Daniel R.
    Kulhavy, David L.
    Hung, I-Kuai
    GISCIENCE & REMOTE SENSING, 2013, 50 (03) : 271 - 280
  • [39] ADVANCED EXTRACTION OF SPATIAL INFORMATION FROM HIGH RESOLUTION SATELLITE DATA
    Pour, T.
    Burian, J.
    Mirijovsky, J.
    XXIII ISPRS CONGRESS, COMMISSION III, 2016, 41 (B3): : 905 - 907
  • [40] The fusion of satellite and UAV data: simulation of high spatial resolution band
    Jenerowicz, Agnieszka
    Siok, Katarzyna
    Woroszkiewicz, Malgorzata
    Orych, Agata
    REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY XIX, 2017, 10421