Satellite-Based Frost Damage Detection in Support of Winter Cover Crops Management: A Case Study on White Mustard

Abstract

Cover crops are grown in order to provide agro-ecological services and must be terminated before planting the subsequent cash crop. Winterkill termination (by frost damage) depends on the interaction between crop frost hardiness, temperatures and the development stage reached at the time of sub-zero temperature exposure. Remotely sensing intensity, timing and spatial variation of cover crop frost damage can be useful for modeling and planning purposes. Therefore, in this study Sentinel-2 vegetation indices were employed in order to detect frost damage in four white mustard (Sinapis alba L.) fields located in Northern Italy. We estimated the starting date of frost events by means of vegetation indices (EVI, NDRE, NDVI, MMSR, and CCCI); we quantified and mapped frost damage at the sub-field level, using ground-based frost damage measurements carried out during the 2021/2022 season. As to frost damage quantification, MMSR outperformed the other VIs followed by CCCI and EVI (R2 > 0.55). The adopted procedure to detect starting dates of frost events was successful in most cases, with a one-day and a four-day delay in the two best cases (NDRE). Finally, maps of frost damage were consistent with its observed spatial variation. We demonstrated that it is possible to employ vegetation indices in order to detect cover crop frost damage and thus assessing cover crop winterkill termination efficiency in the field. Further research is needed, involving additional field monitoring of white mustard in more diverse conditions, and extension of the calibration, as well as validation.

Analysis of the Potential of Remote Piloted Aircraft in the Detection of Damage by Frost in Coffee Plants

“…Gabrielli et al [29], evaluating frost damage in White Mustard from vegetation indices obtained from Sentinel-2 images, found different results from this study. The NDRE index presented the highest value of R 2 (0.46) compared to the NDVI (0.21).…”

“…Although the MPRI, an indice that uses only the reflectance in the visible bands, showed the most significant variation, a greater variation was expected for the NDVI, GNDVI and NDRE indices, indices that use the combination of the near-infrared with the visible bands, because as shown in Figure 3, the variation in near-infrared reflectance at different levels of frost damage to plants is more pronounced when compared to reflectance in the visible bands. This relationship can be observed in Gabrielli et al [29]. The authors demonstrate that the VIs calculated from the reflectance values in the red and red-edge regions were the most correlated with frost damage in White Mustard.…”

“…XXX [23] demonstrated that the NDVI values in coffee plantations vary soon after the frost, allowing us to visualize the extension of the affected area. Gabrielli et al [29] observed that vegetation indices decrease as the frost index in White Mustard increases.…”

Vegetation and Dormancy States Identification in Coniferous Plants Based on Hyperspectral Imaging Data

“…Additionally, it is crucial to promptly evaluate the level of frost tolerance of conifers during specific time periods. Currently, multispectral and hyperspectral data are used to determine the degree of damage to plants caused by negative temperatures [83,84] but not their frost tolerance-their ability to tolerate certain negative temperatures. The ability to solve this issue depends on the correlation between negative temperatures and the values of PRI and CCI.…”

Estimating the frost damage index in lettuce using UAV-based RGB and multispectral images

“…Remote sensing based on Unmanned Aerial Vehicle (UAV), a newly developed technique for high-throughput crop growth information acquisition, has been widely used in crop monitoring under growth ( Jiang et al., 2022 )and various stresses such as pests, diseases, water deficit, salt-stressed( Johansen et al., 2019 ) and frost( Wójtowicz et al., 2016 ; Perry et al., 2017a ; Chen et al., 2019 ; Choudhury et al., 2019 ; Goswami et al., 2019 ; Jełowicki et al., 2020 ; Millan et al., 2020 ; Marin et al., 2021 ). Although satellite remote sensing technology was also used in frost damage monitoring( Feng et al., 2009 ; Romanov, 2009 ; Romani et al., 2011 ; Rudorff et al., 2012 ; She et al., 2015 ; She et al., 2017 ; Li et al., 2021 ; Gabbrielli et al., 2022a ; Gabbrielli et al., 2022b ), the UAV-based remote sensing is more accurate in the breeding field due to its high spatial resolution. UAVs, including DJI, 3D Robotics solo and Ebee, were equipped with spectral cameras to detect frost damage of crops such as wheat( Guo et al., 2014 ; Wang et al., 2014 ; Murphy et al., 2020 ), maize( Choudhury et al., 2019 ; Goswami et al., 2019 ; Shu et al., 2022 ), oat( Macedo-Cruz et al., 2011 ), oilseed rape( She et al., 2015 ), and coffee plants( Marin et al., 2021 ; Marin et al., 2022 ).…”