ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume V-3-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 117–124, 2020
https://doi.org/10.5194/isprs-annals-V-3-2020-117-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 117–124, 2020
https://doi.org/10.5194/isprs-annals-V-3-2020-117-2020

  03 Aug 2020

03 Aug 2020

A CASE STUDY OF MONITORING MAIZE DYNAMICS IN SERBIA BY UTILIZING SENTINEL-1 DATA AND GROWING DEGREE DAYS

M. Pandžić1, N. Ljubičić1, G. Mimić1, J. Pandžić2, B. Pejak1, and V. Crnojević1 M. Pandžić et al.
  • 1University of Novi Sad, BioSense Institute, 21 000 Novi Sad, Serbia
  • 2University College of Professional Studies for Civil Engineering and Geodesy, 11 000 Belgrade, Serbia

Keywords: Sentinel-1, Growing Degree Days, Growth Stages, Backscatter, Maize

Abstract. Due to great significance of maize for Serbian agricultural production, maize growth monitoring during the season is highly important. Some of the growth stages have particular influence on the final yield and without optimal conditions at that point, yield losses may be substantial. Hence, it is crucial to be familiar with transition periods between the stages. Sentinel-1 Synthetic Aperture Radar (SAR) data is a reliable source of information for monitoring various crops in all climatic conditions. Dense time series of radar images offer a unique insight into vegetation dynamics during the season. By combining these with the Growing Degree Days (GDD) method that exploits temperature information in order to position different growth stages in time, more precise estimates of crucial periods in maize development can be made. An experiment was conducted for several maize fields in Serbia for 2017 and 2018 season. GDD estimates were constructed based on literature search and temperature information acquired from the Copernicus Climate Change Service. Despite seasonal weather differences, similar trends in radar backscatter were noticeable and existence of certain growth stages (such as emergence, tasselling, silking and physiological maturity) could be estimated. However, these estimates came up with an uncertainty caused most likely by rain and uneven development of maize that influence radar backscatter. The results were compared with estimates made by an agronomy expert that were not based on field inspection but solely on professional experience due to post-seasonal experiment design. The procedure proved to be practical and applicable all over the world.