Crnojević, Vladimir

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  • Crnojević, Vladimir (2)
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Author's Bibliography

Within-field correlation between satellite-derived vegetation indices and grain yield of wheat

Blagojević, Dragana; Stojković, Stefanija; Brdar, Sanja; Crnojević, Vladimir

(BioSense Institute, Novi Sad, 2021)

TY  - CONF
AU  - Blagojević, Dragana
AU  - Stojković, Stefanija
AU  - Brdar, Sanja
AU  - Crnojević, Vladimir
PY  - 2021
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/3182
AB  - This research aimed to inspect the correlation coefficients, during the crop growth stages, between vegetation indices (VIs) derived from Sentinel-2 imagery and grain winter wheat yield derived from yield monitoring and select the most promising indices for monitoring crop growth and yield estimation. METHOD / DESIGN: The satellite images in 10m resolution were selected based on crop growth stages, from the end of tillering phase (beginning of March 2019) until the full ripening (end of June 2019). For the analysis, the BBCH-scale for cereals was used. Yield observations were performed at harvest on five fields in one season and twelve VIs were calculated across 10 growth stages. To designate their correlation and dependence, a statistical comparison of the VIs and yield was made. The Pearson’s and Spearman’s correlation coefficients were calculated, and their statistical significance was tested using p-value (at p=0.01, p=0.05). RESULTS: According to the crop growth stages, the highest correlation coefficients were detected from the early boot stage (BBCH 41) until the middle of development of the fruiting stage (BBCH 73 – early milk). In that period the correlation coefficients varied from 0.39 to 0.84 depending on the field. Based on the location, the highest correlation coefficient values for all 12 indices were recorded for the parcel named C-6 (April 15), and the lowest values for the parcel named C-10 (June 29). Most of the indices showed statistically significant dependence (at the p<0.01 and p<0.05 significant levels) on the yield in the first five growth stages except the chlorophyll vegetation index (CVI) for the parcel named C-11 (p=0.21, p=0.39). CONCLUSIONS: To conclude, the last growth stage named ripening showed the lowest values both for correlation coefficient and statistical significance which means that VIs also had low values because the reflectance is weak in this growth stage and wheat is about to be harvested. In the first five stages, VIs showed significantly high spectral reflectance values since in this period the leaf is full of chlorophyll pigments. Analyzing the correlation coefficient in different stages of wheat growth, we look at the current state of crops and have the opportunity to take appropriate measures in time to increase yields or save inputs at specific locations.
PB  - BioSense Institute, Novi Sad
C3  - International Bioscience Conference and the 8th International PSU – UNS Bioscience Conference
T1  - Within-field correlation between satellite-derived vegetation indices and grain yield of wheat
SP  - 218
DO  - 10.13140/RG.2.2.22001.20324
ER  - 
@conference{
author = "Blagojević, Dragana and Stojković, Stefanija and Brdar, Sanja and Crnojević, Vladimir",
year = "2021",
abstract = "This research aimed to inspect the correlation coefficients, during the crop growth stages, between vegetation indices (VIs) derived from Sentinel-2 imagery and grain winter wheat yield derived from yield monitoring and select the most promising indices for monitoring crop growth and yield estimation. METHOD / DESIGN: The satellite images in 10m resolution were selected based on crop growth stages, from the end of tillering phase (beginning of March 2019) until the full ripening (end of June 2019). For the analysis, the BBCH-scale for cereals was used. Yield observations were performed at harvest on five fields in one season and twelve VIs were calculated across 10 growth stages. To designate their correlation and dependence, a statistical comparison of the VIs and yield was made. The Pearson’s and Spearman’s correlation coefficients were calculated, and their statistical significance was tested using p-value (at p=0.01, p=0.05). RESULTS: According to the crop growth stages, the highest correlation coefficients were detected from the early boot stage (BBCH 41) until the middle of development of the fruiting stage (BBCH 73 – early milk). In that period the correlation coefficients varied from 0.39 to 0.84 depending on the field. Based on the location, the highest correlation coefficient values for all 12 indices were recorded for the parcel named C-6 (April 15), and the lowest values for the parcel named C-10 (June 29). Most of the indices showed statistically significant dependence (at the p<0.01 and p<0.05 significant levels) on the yield in the first five growth stages except the chlorophyll vegetation index (CVI) for the parcel named C-11 (p=0.21, p=0.39). CONCLUSIONS: To conclude, the last growth stage named ripening showed the lowest values both for correlation coefficient and statistical significance which means that VIs also had low values because the reflectance is weak in this growth stage and wheat is about to be harvested. In the first five stages, VIs showed significantly high spectral reflectance values since in this period the leaf is full of chlorophyll pigments. Analyzing the correlation coefficient in different stages of wheat growth, we look at the current state of crops and have the opportunity to take appropriate measures in time to increase yields or save inputs at specific locations.",
publisher = "BioSense Institute, Novi Sad",
journal = "International Bioscience Conference and the 8th International PSU – UNS Bioscience Conference",
title = "Within-field correlation between satellite-derived vegetation indices and grain yield of wheat",
pages = "218",
doi = "10.13140/RG.2.2.22001.20324"
}
Blagojević, D., Stojković, S., Brdar, S.,& Crnojević, V.. (2021). Within-field correlation between satellite-derived vegetation indices and grain yield of wheat. in International Bioscience Conference and the 8th International PSU – UNS Bioscience Conference
BioSense Institute, Novi Sad., 218.
https://doi.org/10.13140/RG.2.2.22001.20324
Blagojević D, Stojković S, Brdar S, Crnojević V. Within-field correlation between satellite-derived vegetation indices and grain yield of wheat. in International Bioscience Conference and the 8th International PSU – UNS Bioscience Conference. 2021;:218.
doi:10.13140/RG.2.2.22001.20324 .
Blagojević, Dragana, Stojković, Stefanija, Brdar, Sanja, Crnojević, Vladimir, "Within-field correlation between satellite-derived vegetation indices and grain yield of wheat" in International Bioscience Conference and the 8th International PSU – UNS Bioscience Conference (2021):218,
https://doi.org/10.13140/RG.2.2.22001.20324 . .

Reviewing the potential of Sentinel-2 in assessing the drought

Varghese, Dani; Radulović, Mirjana; Stojković, Stefanija; Crnojević, Vladimir

(MDPI, 2021)

TY  - JOUR
AU  - Varghese, Dani
AU  - Radulović, Mirjana
AU  - Stojković, Stefanija
AU  - Crnojević, Vladimir
PY  - 2021
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/3168
AB  - This paper systematically reviews the potential of the Sentinel-2 (A and B) in assessing drought. Research findings, including the IPCC reports, highlighted the increasing trend in drought over the decades and the need for a better understanding and assessment of this phenomenon. Continuous monitoring of the Earth’s surface is an efficient method for predicting and identifying the early warnings of drought, which enables us to prepare and plan the mitigation procedures. Considering the spatial, temporal, and spectral characteristics, the freely available Sentinel-2 data products are a promising option in this area of research, compared to Landsat and MODIS. This paper evaluates the recent developments in this field induced by the launch of Sentinel-2, as well as the comparison with other existing data products. The objective of this paper is to evaluate the potential of Sentinel-2 in assessing drought through vegetation characteristics, soil moisture, evapotranspiration, surface water including wetland, and land use and land cover analysis. Furthermore, this review also addresses and compares various data fusion methods and downscaling methods applied to Sentinel-2 for retrieving the major bio-geophysical variables used in the analysis of drought. Additionally, the limitations of Sentinel-2 in its direct applicability to drought studies are also evaluated.
PB  - MDPI
T1  - Reviewing the potential of Sentinel-2 in assessing the drought
VL  - 13: 3355
DO  - 10.3390/rs13173355
ER  - 
@article{
author = "Varghese, Dani and Radulović, Mirjana and Stojković, Stefanija and Crnojević, Vladimir",
year = "2021",
abstract = "This paper systematically reviews the potential of the Sentinel-2 (A and B) in assessing drought. Research findings, including the IPCC reports, highlighted the increasing trend in drought over the decades and the need for a better understanding and assessment of this phenomenon. Continuous monitoring of the Earth’s surface is an efficient method for predicting and identifying the early warnings of drought, which enables us to prepare and plan the mitigation procedures. Considering the spatial, temporal, and spectral characteristics, the freely available Sentinel-2 data products are a promising option in this area of research, compared to Landsat and MODIS. This paper evaluates the recent developments in this field induced by the launch of Sentinel-2, as well as the comparison with other existing data products. The objective of this paper is to evaluate the potential of Sentinel-2 in assessing drought through vegetation characteristics, soil moisture, evapotranspiration, surface water including wetland, and land use and land cover analysis. Furthermore, this review also addresses and compares various data fusion methods and downscaling methods applied to Sentinel-2 for retrieving the major bio-geophysical variables used in the analysis of drought. Additionally, the limitations of Sentinel-2 in its direct applicability to drought studies are also evaluated.",
publisher = "MDPI",
title = "Reviewing the potential of Sentinel-2 in assessing the drought",
volume = "13: 3355",
doi = "10.3390/rs13173355"
}
Varghese, D., Radulović, M., Stojković, S.,& Crnojević, V.. (2021). Reviewing the potential of Sentinel-2 in assessing the drought. 
MDPI., 13: 3355.
https://doi.org/10.3390/rs13173355
Varghese D, Radulović M, Stojković S, Crnojević V. Reviewing the potential of Sentinel-2 in assessing the drought. 2021;13: 3355.
doi:10.3390/rs13173355 .
Varghese, Dani, Radulović, Mirjana, Stojković, Stefanija, Crnojević, Vladimir, "Reviewing the potential of Sentinel-2 in assessing the drought", 13: 3355 (2021),
https://doi.org/10.3390/rs13173355 . .
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