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

Radosław Gurdak
Radosław Gurdak
 y 
Maciej Bartold
Maciej Bartold
   | 26 sept 2021
Miscellanea Geographica's Cover Image
Miscellanea Geographica
Volumen 25 (2021): Edición 4 (October 2021)
Thematic Issue: “Innovation in geospatial and 3D data” focuses on the newest achievements in the field of Geodata, which are used in Geosciences and for various applications such as urban planning, territorial management, damage assessment, environmental monitoring, 3D city modelling, renewable energy assessment, land registry, heritage documentation.
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Publicado en línea: 26 sept 2021
Páginas: 226 - 237
Recibido: 28 abr 2020
Aceptado: 13 ago 2020
DOI: https://doi.org/10.2478/mgrsd-2020-0029
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© 2021 Radosław Gurdak et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1

JECAM cropland site 25 km × 25 km, highlighted in yellow, with field sites where chlorophyll fluorescence were measuredSource: own elaboration
JECAM cropland site 25 km × 25 km, highlighted in yellow, with field sites where chlorophyll fluorescence were measuredSource: own elaboration

Figure 2

Scheme of workSource: own elaboration
Scheme of workSource: own elaboration

Figure 3

Chlorophyll fluorescence measurements on sugar beets with OS5p+ Pulse Modulated Chlorophyll FluorometerSource: photo by Maciej Bartold
Chlorophyll fluorescence measurements on sugar beets with OS5p+ Pulse Modulated Chlorophyll FluorometerSource: photo by Maciej Bartold

Figure 4

Time series of vegetation indices for maize and sugar beets during 2018–2019Source: own elaboration
Time series of vegetation indices for maize and sugar beets during 2018–2019Source: own elaboration

Figure 5

Sentinel-3 based land surface temperatures of maize and sugar beets during 2018–2019. The red crosses indicate mean, thin black lines median, green boxes 25%–75% ranges, black dots are outliersSource: own elaboration
Sentinel-3 based land surface temperatures of maize and sugar beets during 2018–2019. The red crosses indicate mean, thin black lines median, green boxes 25%–75% ranges, black dots are outliersSource: own elaboration

Figure 6

Maximum and mean temperatures, as well as total precipitation, noted in 2018 at the meteorological station in the town of KornikSource: own elaboration
Maximum and mean temperatures, as well as total precipitation, noted in 2018 at the meteorological station in the town of KornikSource: own elaboration

Figure 7

Maximum and mean temperature, as well as total precipitation, noted in 2019 at the meteorological station in the town of KornikSource: own elaboration
Maximum and mean temperature, as well as total precipitation, noted in 2019 at the meteorological station in the town of KornikSource: own elaboration

Vegetation indices calculated from Sentinel-2 satellite imagery

1 2 3 4 5
Application Index Description Equation Reference
Assessment of the general condition of vegetation CTVI Corrected Transformed Vegetation Index CTVI=(NDVI+0.5)|NDVI+0.5|*NDVI+0.5 {\rm{CTVI}} = {{\left( {{\rm{NDVI}} + 0.5} \right)} \over {\left| {{\rm{NDVI}} + 0.5} \right|}}*\sqrt {{\rm{NDVI}} + 0.5} Perry, 1984
DVI Difference Vegetation Index DVI= aRNIR-Rred Richardson, 1977
EVI Enhanced Vegetation Index EVI=RNIR−RredRNIR+C1*Rred−C2*Rblue+L {\rm{EVI}} = {{{R_{NIR}} - {R_{red}}} \over {{R_{NIR}} + {C_1}*{R_{red}} - {C_2}*{R_{blue}} + L}} Huete, 1999
GEMI Global Environmental Monitoring Index GEMI=n(1−0.25n)−Rred−0.1251−Rred {\rm{GEMI}} = {\rm{n}}\left( {1 - 0.25{\rm{n}}} \right) - {{{R_{red}} - 0.125} \over {1 - {R_{red}}}} Pinty, 1992
GNDVI Green Normalized Difference Vegetation Index GNDVI=RNIR−RgreenRNIR+Rgreen {\rm{GNDVI}} = {{{R_{NIR}} - {R_{green}}} \over {{R_{NIR}} + {R_{green}}}} Gitelson, 1998
IRECI Inverted Red Edge Chlorophyll Index IRECI=(RNIR−Rred)Rrededge1/Rrededge2 {\rm{IRECI}} = {{\left( {{R_{NIR}} - {R_{red}}} \right)} \over {{R_{rededge1}}/{R_{rededge2}}}} Frampton et al., 2013
MSAVI Modified Soil Adjusted Vegetation Index MSAVI=RNIR−RredRNIR+Rred+L*(1+L) {\rm{MSAVI}} = {{{R_{NIR}} - {R_{red}}} \over {{R_{NIR}} + {R_{red}} + L}}*\left( {1 + L} \right) Qi et al., 1994
MSAVI2 Modified Soil Adjusted Vegetation Index 2 MSAVI2=12[2*R800+1−(2*R800+1)−8*(R800−R670)] {\rm{MSAVI}}2 = {1 \over 2}\left[ {2*{R_{800}} + 1 - \sqrt {\left( {2*{R_{800}} + 1} \right) - 8*\left( {{R_{800}} - {R_{670}}} \right)} } \right] Qi et al., 1994
NDREI1 Normalized Difference Red Edge Index 1 NDREI1=R790−R720R790+R720 {\rm{NDREI}}1 = {{{R_{790}} - {R_{720}}} \over {{R_{790}} + {R_{720}}}} Gitelson And Merzlyak, 1994
NDREI2 Normalized Difference Red Edge Index 2 NDREI2=R750−R705R750+R705*R445 {\rm{NDREI}}2 = {{{R_{750}} - {R_{705}}} \over {{R_{750}} + {R_{705}}*{R_{445}}}} Barnes, 2000
NDVI Normalized Difference Vegetation Index NDVI=RNIR−RredRNIR+Rred {\rm{NDVI}} = {{{R_{NIR}} - {R_{red}}} \over {{R_{NIR}} + {R_{red}}}} Rouse, 1974
NRVI Normalized Ratio Vegetation Index NRVI=RredRNIR−1RredRNIR+1 {\rm{NRVI}} = {{{{{R_{red}}} \over {{R_{NIR}}}} - 1} \over {{{{R_{red}}} \over {{R_{NIR}}}} + 1}} Baret, 1991
REIP Red Edge Inflection Point REIP=700+40((R670+R7802)−R700R740−R700) {\rm{REIP}} = 700 + 40\left( {{{\left( {{{{R_{670}} + {R_{780}}} \over 2}} \right) - {R_{700}}} \over {{R_{740}} - {R_{700}}}}} \right) Guyot And Barnet, 1988
RVI Ratio Vegetation Index RVI=RredRNIR {\rm{RVI}} = {{{R_{red}}} \over {{R_{NIR}}}} Bannari et al., 1995
SATVI Soil Adjusted Total Vegetation Index SATVI=RNIR−RredRNIR+Rred+L*(1+L)−RSWIR2 {\rm{SATVI}} = {{{R_{NIR}} - {R_{red}}} \over {{R_{NIR}} + {R_{red}} + L}}*\left( {1 + L} \right) - {{{R_{SWIR}}} \over 2} Marsett, 2006
SAVI Soil Adjusted Vegetation Index SAVI=(1+L)(RNIR−Rred)RNIR+Rred+L {\rm{SAVI}} = {{\left( {1 + L} \right)\left( {{R_{NIR}} - {R_{red}}} \right)} \over {{R_{NIR}} + {R_{red}} + L}} Huete, 1988
SLAVI Specific Leaf Area Vegetation Index SLAVI=RNIRRred+RSWIR {\rm{SLAVI}} = {{{R_{NIR}}} \over {{R_{red}} + {R_{SWIR}}}} Lymburger et al., 2000
SR Simple Ratio Vegetation Index SR=RNIRRred {\rm{SR}} = {{{R_{NIR}}} \over {{R_{red}}}} Birth, 1968
TTVI Thiam's Transformed Vegetation Index TTVI=|NDVI+0.5| {\rm{TTVI}} = \sqrt {\left| {{\rm{NDVI}} + 0.5} \right|} Thiam, 1997
TVI Transformed Vegetation Index MSAVI2=12[120*(R750−R550)−200*(R670−R550)] {\rm{MSAVI}}2 = {1 \over 2}\left[ {120*\left( {{R_{750}} - {R_{550}}} \right) - 200*\left( {{R_{670}} - {R_{550}}} \right)} \right] Deering, 1975
WDVI Weighted Difference Vegetation Index WDVI=RNIR-a*Rred Richardson, 1977
Assessment of photosynthetically active pigment CLG Chlorophyll Index Green CLG=RNIRRgreen−1 {\rm{CLG}} = {{{R_{NIR}}} \over {{R_{green}}}} - 1 Gitelson, 2003
CLRE Red-edge-band Chlorophyll Index CLRE=R750R710−1 {\rm{CLRE}} = {{{R_{750}}} \over {{R_{710}}}} - 1 Gitelson, 2003
MCARI Modified Chlorophyll Absorption Ratio Index MCARI=[(R700−R670)−0.2*(R700−R550)]*(R700/R670) {\rm{MCARI}} = \left[ {\left( {{R_{700}} - {R_{670}}} \right) - 0.2*\left( {{R_{700}} - {R_{550}}} \right)} \right]*\left( {{R_{700}}/{R_{670}}} \right) Daughtery, 2000
MTCI MERIS Terrestrial Chlorophyll Index MTCI=R754−R709R709−R681 {\rm{MTCI}} = {{{R_{754}} - {R_{709}}} \over {{R_{709}} - {R_{681}}}} Dash And Curran, 2004
S2REP Sentinel-2 Red-Edge Position Index S2REP=705+35*((RNIR+Rred)/2)−R705(R740−R705) {\rm{S}}2{\rm{REP}} = 705 + 35*{{\left( {\left( {{R_{NIR}} + {R_{red}}} \right)/2} \right) - {R_{705}}} \over {\left( {{R_{740}} - {R_{705}}} \right)}} Frampton et al., 2013
Assessment of the amount of light used in photosynthesis SIPI Structure Insensitive Pigment Index SIPI=R800−R450R800+R650 {\rm{SIPI}} = {{{R_{800}} - {R_{450}}} \over {{R_{800}} + {R_{650}}}} Peñuelas et al., 1995
ZMI Zarco-Tejada & Miller Index ZMI=R750R710 {\rm{ZMI}} = {{{R_{750}}} \over {{R_{710}}}} Zarco-Tejada et al., 2001
Assessment of water content DSWI Disease Water Stress Index DSWI=R802+R547R1657+R682 {\rm{DSWI}} = {{{R_{802}} + {R_{547}}} \over {{R_{1657}} + {R_{682}}}} Galvão et al., 2005
MNDWI Modified Normalized Difference Water Index MNDWI=Rgreen−RMIRRgreen+RMIR {\rm{MNDWI}} = {{{R_{green}} - {R_{MIR}}} \over {{R_{green}} + {R_{MIR}}}} Xu, 2006
NDWI Normalized Difference Water Index NDWI=Rgreen−RNIRRgreen+RNIR {\rm{NDWI}} = {{{R_{green}} - {R_{NIR}}} \over {{R_{green}} + {R_{NIR}}}} McFeeters, 1996
NDWI2 Normalized Difference Water 2 Index NDWI2=R857−R1241R587+R1241 {\rm{NDWI2}} = {{{R_{857}} - {R_{1241}}} \over {{R_{587}} + {R_{1241}}}} Gao, 1996
NDII Normalized Difference Infrared Index NDII=R850−R1650R580+R1650 {\rm{NDII}} = {{{R_{850}} - {R_{1650}}} \over {{R_{580}} + {R_{1650}}}} Hardisky et al., 1993

Linear regression equations for estimating ChlF (FV/FM)

CROP TYPE INDEX FORMULA
MAIZE NDII FV/FM = 0.68053 + 0.25102 * NDII
SIPI FV/FM = 1.1527 − 0.3640 * SIPI
SUGAR BEETS EVI FV/FM = 0.60230 + 0.07402 * EVI
S2REP FV/FM = −8.753 + 0.01317 * S2REP

Sentinel-3 cloud-free satellite images of croplands in Wielkopolska. Actual state on 10. September 2019.

Year 2018 2019
Month July August July August
Day 5 9 21 28 1 5 13 17 4 15 25 26 1 8 12 13 15 22 23 24 26 28 29 30 31

Results of correlation analysis of ground measured ChlF and Vis (red color – results with the highest correlation coefficient)

Assessment Vegetation Index Maize Sugar beets
R coefficient MAE RMSE p-value R coefficient MAE RMSE p-value
Assessment of the general condition of vegetation CTVI 0.19 0.08 0.07 0.445 0.36 0.08 0.07 0.204
DVI 0.24 0.07 0.07 0.315 0.29 0.08 0.08 0.320
EVI 0.61 0.03 0.03 0.005 0.45 0.05 0.04 0.106
GEMI −0.26 0.07 0.07 0.275 −0.25 0.08 0.08 0.394
GNDVI 0.07 0.10 0.09 0.767 0.35 0.09 0.09 0.226
IRECI 0.64 0.02 0.02 0.003 0.22 0.08 0.08 0.447
MSAVI 0.17 0.08 0.07 0.478 0.37 0.07 0.06 0.188
MSAVI2 0.17 0.08 0.07 0.478 0.37 0.07 0.06 0.188
NDREI1 0.14 0.08 0.07 0.579 0.35 0.07 0.07 0.213
NDREI2 0.06 0.10 0.09 0.815 0.35 0.07 0.07 0.223
NDVI 0.19 0.08 0.08 0.429 0.35 0.07 0.07 0.214
NRVI −0.19 0.08 0.08 0.429 −0.35 0.07 0.07 0.214
REIP 0.15 0.08 0.07 0.538 0.31 0.08 0.07 0.284
RVI −0.17 0.08 0.07 0.478 −0.37 0.07 0.07 0.188
SATVI 0.22 0.07 0.07 0.362 0.40 0.05 0.05 0.152
SAVI 0.56 0.04 0.03 0.012 0.32 0.08 0.07 0.269
SLAVI 0.37 0.06 0.06 0.124 0.26 0.08 0.07 0.374
SR 0.29 0.07 0.06 0.233 0.21 0.08 0.08 0.479
TTVI 0.19 0.08 0.07 0.445 0.36 0.07 0.07 0.478
TVI 0.55 0.04 0.04 0.015 0.21 0.08 0.08 0.478
WDVI 0.24 0.07 0.06 0.315 0.29 0.08 0.07 0.320
Assessment of photosynthetically active pigment CLG 0.06 0.10 0.10 0.805 0.24 0.07 0.07 0.401
CLRE 0.09 0.10 0.09 0.708 0.28 0.08 0.07 0.335
MCARI 0.35 0.06 0.06 0.141 0.26 0.07 0.06 0.377
MTCI −0.01 0.11 0.10 0.980 0.38 0.06 0.06 0.186
S2REP 0.46 0.06 0.05 0.046 0.43 0.05 0.04 0.125
Assessment of the amount of light used in photosynthesis SIPI −0.68 0.02 0.02 0.001 0.24 0.07 0.07 0.401
ZMI 0.54 0.04 0.04 0.017 −0.13 0.09 0.08 0.665
Assessment of water content DSWI 0.64 0.03 0.03 0.003 0.22 0.07 0.06 0.460
MNDWI 0.54 0.04 0.04 0.017 0.09 0.09 0.09 0.751
NDWI −0.07 0.10 0.09 0.767 −0.35 0.06 0.06 0.226
NDWI2 0.37 0.06 0.06 0.120 0.33 0.07 0.06 0.251
NDII 0.65 0.03 0.03 0.002 0.31 0.07 0.07 0.279
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