Remote sensing techniques to assess chlorophyll fluorescence in support of crop monitoring in Poland

Gurdak Radosław () and Bartold Maciej ()
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Gurdak Radosław: Department of Geoinformatics, Cartography and Remote Sensing, Faculty of Geography and Regional Studies, University of Warsaw, Warsaw, Poland
Bartold Maciej: Remote Sensing Centre, Institute of Geodesy and Cartography, Warsaw, Poland

Miscellanea Geographica. Regional Studies on Development, 2021, vol. 25, issue 4, 226-237

Abstract: The increase in demand for food and the need to predict the impact of a warming climate on vegetation makes it critical that the best tools for assessing crop production are found. Chlorophyll fluorescence (ChlF) has been proposed as a direct indicator of photosynthesis and plant condition. The aim of this paper is to study the feasibility of estimating ChlF from spectral vegetation indices derived from Sentinel-2, in order to monitor crop stress and investigate ChlF changes in response to surface temperatures and meteorological observations. The regressions between thirty three Sentinel-2-derived VIs, and ChlF measured on the ground were evaluated in order to estimate the best predictors of ChlF. The r-Pearson correlation and polynomial linear regression were used. For maize, the highest correlation between ChlF and VIs were found for NDII (r=0.65) and for SIPI (r=−0.68). The weakest relationship between VIs and ChlF were found for sugar beets. Despite this, it should be noted that the highest correlation for sugar beets appeared for EVI (r=0.45) and S2REP (r=0.43). The results of this study indicate the need for a synergy of low and high resolution satellite data that will enable a more detailed analysis for estimating fluorescence and its relation to climatic conditions, environmental aspects, and VIs derived from satellite images.

Keywords: Spectral vegetation indices; land surface temperature; JECAM; Sentinel satellites (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:mgrsod:v:25:y:2021:i:4:p:226-237:n:2

DOI: 10.2478/mgrsd-2020-0029

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