Spatio-temporal variability of biophysical parameters of irrigated maize using orbital remote sensing

被引:1
|
作者
Costa, Taiara Souza [1 ]
dos Santos, Robson Argolo [2 ]
Santos, Rosangela Leal [3 ]
Filgueiras, Roberto [4 ]
da Cunha, Fernando Franca [4 ]
Pereira, Anderson de Jesus [5 ]
de Salles, Rodrigo Amaro [6 ]
机构
[1] Univ Fed Vicosa, Grad Program Agr Engn, UFV, Vicosa, MG, Brazil
[2] Univ Fed Vicosa, Grad Program Agr Engn, Vicosa, MG, Brazil
[3] Univ Estadual Feira de Santana, Technol Dept, UEFS, Feira De Santana, BA, Brazil
[4] Univ Fed Vicosa, Dept Agron Engn, Vicosa, MG, Brazil
[5] Univ Estadual Paulista, UNESP, Sao Paulo, SP, Brazil
[6] Univ Fed Vicosa, Vicosa, MG, Brazil
来源
SEMINA-CIENCIAS AGRARIAS | 2021年 / 42卷 / 04期
关键词
Agrometeorological models; Irrigation management; Phenological cycle; WATER PRODUCTIVITY; RIVER-BASIN; VEGETATION; IMAGES; YIELD;
D O I
10.5433/1679-0359.2021v42n4p2181
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
This study proposes to estimate the actual crop evapotranspiration, using the SAFER model, as well as calculate the crop coefficient (Kc) as a function of the normalized difference vegetation index (NDVI) and determine the biomass of an irrigated maize crop using images from the Operational Land Imager (OLI) and Thermal Infrared (TIRS) sensors of the Landsat-8 satellite. Pivots 21 to 26 of a commercial farm located in the municipalities of Bom Jesus da Lapa and Serra do Ramalho, west of Bahia State, Brazil, were selected. Sowing dates for each pivot were arranged as North and South or East and West, with cultivation starting firstly in one of the orientations and subsequently in the other. The relationship between NDVI and the Kc values obtained in the FAO-56 report (Kc(FAO)) revealed a high coefficient of determination (R-2 = 0.7921), showing that the variance of Kc(FAO) can be explained by NDVI in the maize crop. Considering the center pivots with different planting dates, the crop evapotranspiration (ETc) pixel values ranged from 0.0 to 6.0 mm d(-1) during the phenological cycle. The highest values were found at 199 days of the year (DOY), corresponding to around 100 days after sowing (DAS). The lowest BIO values occur at 135 DOY, at around 20 DAS. There is a relationship between ETc and BIO, where the DOY with the highest BIO are equivalent to the days with the highest ETc values. In addition to this relationship, BIO is strongly influenced by soil water availability.
引用
收藏
页码:2181 / 2201
页数:21
相关论文
共 50 条
  • [1] Spatio-temporal signature of surface biophysical parameters in response to extreme IOD events using remote sensing
    Jena, Amit Kumar
    Mohanty, Sachiko
    Mitra, Debashis
    [J]. REGIONAL STUDIES IN MARINE SCIENCE, 2022, 56
  • [2] Spatio-Temporal Assessment of Surface Moisture and Evapotranspiration Variability Using Remote Sensing Techniques
    Le, Mai Son
    Liou, Yuei-An
    [J]. REMOTE SENSING, 2021, 13 (09)
  • [3] SPATIO-TEMPORAL DISTRIBUTIONS AND TRENDS OF AEROSOL PARAMETERS OVER PAKISTAN USING REMOTE SENSING
    Tariq, S.
    Ul-Haq, Z.
    Mahmood, K.
    Rana, A. D.
    [J]. APPLIED ECOLOGY AND ENVIRONMENTAL RESEARCH, 2018, 16 (03): : 2615 - 2637
  • [4] Spatio-temporal variability of coastal upwelling using high resolution remote sensing observations in the Bay of Bengal
    Dey, Shouvik
    Sil, Sourav
    [J]. ESTUARINE COASTAL AND SHELF SCIENCE, 2023, 282
  • [5] SPATIO-TEMPORAL MONITORING OF PERMAFROST REGION USING SAR REMOTE SENSING
    Park, Sang-Eun
    Yamaguchi, Yoshio
    Singh, Gulab
    Bartsch, Annett
    [J]. NETWORKING THE WORLD WITH REMOTE SENSING, 2010, 38 : 142 - 145
  • [6] Spatio-temporal analyses of cropland degradation in the irrigated lowlands of Uzbekistan using remote-sensing and logistic regression modeling
    Olena Dubovyk
    Gunter Menz
    Christopher Conrad
    Elena Kan
    Miriam Machwitz
    Asia Khamzina
    [J]. Environmental Monitoring and Assessment, 2013, 185 : 4775 - 4790
  • [7] Spatio-temporal analyses of cropland degradation in the irrigated lowlands of Uzbekistan using remote-sensing and logistic regression modeling
    Dubovyk, Olena
    Menz, Gunter
    Conrad, Christopher
    Kan, Elena
    Machwitz, Miriam
    Khamzina, Asia
    [J]. ENVIRONMENTAL MONITORING AND ASSESSMENT, 2013, 185 (06) : 4775 - 4790
  • [8] Dynamics of land cover and land use in Pernambuco (Brazil): Spatio-temporal variability and temporal trends of biophysical parameters
    Cezar Bezerra, Alan
    Bezerra da Silva, Jhon Lennon
    de Albuquerque Moura, Geber Barbosa
    Oliveira Lopes, Pabricio Marcos
    Nascimento, Cristina Rodrigues
    Ribeiro, Eberson Pessoa
    Galvincio, Josicleda Domiciano
    da Silva, Marcos Vinicius
    [J]. REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT, 2022, 25
  • [9] Effective spatio-temporal analysis of remote sensing data
    Zhang, Zhongnan
    Wu, Weili
    Huang, Yaochun
    [J]. PROGRESS IN WWW RESEARCH AND DEVELOPMENT, PROCEEDINGS, 2008, 4976 : 584 - 589
  • [10] Satellite Remote Sensing For Spatio-Temporal Changes Analysis Of Urban Surface Biogeophysical Parameters
    Zoran, Maria
    [J]. 7TH INTERNATIONAL CONFERENCE OF THE BALKAN PHYSICAL UNION VOLS 1 AND 2, 2009, 1203 : 1125 - 1130