Deriving crop productivity indicators from satellite synthetic aperture radar to assess wheat production at field-scale.

Richter, G. M. Industrial supervisor ( Rothamsted Research) Burgess, Paul J. and Meersmans, Jeroen Associate supervisorsThe deployment of high-revisit satellite-based radar sensors raises the question of whether the data collected can provide quantitative information to improve agricultural productivity. This thesis aims to develop and test mathematical algorithms to describe the dynamic backscatter of high-resolution Synthetic Aperture Radar (Sentinel-1) in order to describe the development and productivity of wheat at field-scale. A time series of the backscatter ratio (VH/VV), collected over a cropping season, could be characterised by a growth and a senescence logistic curve and related to critical phases of crop development. The curve parameters, referred to as Crop Productivity Indicators (CPIs), compared well with the crop production for three years at the Rothamsted experimental farm. The combination of different parameters (e.g. midpoints of the two curves) helped to define CPIs, such as duration, that significantly (r = 0.61, p = 0.05) correlated with measured yields. Field observations were used to understand the wheat evolution by sampling canopy characteristics across the seasons. The correlation between the samples and the CPIs showed that structural changes, like biomass increase, influence the CPIs during the growth phase, and that declining plant water content was correlated with VH/VV values during maturation. The methodology was upscaled to other farms in Hertfordshire and Norfolk. The ANOVA identified significant effects (p<0.001) of farm management, year (weather conditions) and the interaction between soil type and year on the selected CPIs. Multilinear regression models between yields and selected CPIs displayed promising predictive power (R²= 0.5) across different farms in the same year. However, these models could not explain yield differences within high-yielding farms across seasons because of the dominant effect of weather patterns on the CPIs in each year. The potential impact of the research includes estimation of yield across the landscape, phenology monitoring and indication biophysical parameters. Future work on SAR-derived CPIs should focus on improving the correlations with biophysical properties, applying of the methodology in other crops, with different soils and climates.PhD in Environment and Agrifoo

Deriving wheat crop productivity indicators using Sentinel-1 time series

High-frequency Earth observation (EO) data have been shown to be effective in identifying crops and monitoring their development. The purpose of this paper is to derive quantitative indicators of crop productivity using synthetic aperture radar (SAR). This study shows that the field-specific SAR time series can be used to characterise growth and maturation periods and to estimate the performance of cereals. Winter wheat fields on the Rothamsted Research farm in Harpenden (UK) were selected for the analysis during three cropping seasons (2017 to 2019). Average SAR backscatter from Sentinel-1 satellites was extracted for each field and temporal analysis was applied to the backscatter cross-polarisation ratio (VH/VV). The calculation of the different curve parameters during the growing period involves (i) fitting of two logistic curves to the dynamics of the SAR time series, which describe timing and intensity of growth and maturation, respectively; (ii) plotting the associated first and second derivative in order to assist the determination of key stages in the crop development; and (iii) exploring the correlation matrix for the derived indicators and their predictive power for yield. The results show that the day of the year of the maximum VH/VV value was negatively correlated with yield (r = −0.56), and the duration of “full” vegetation was positively correlated with yield (r = 0.61). Significant seasonal variation in the timing of peak vegetation (p = 0.042), the midpoint of growth (p = 0.037), the duration of the growing season (p = 0.039) and yield (p = 0.016) were observed and were consistent with observations of crop phenology. Further research is required to obtain a more detailed picture of the uncertainty of the presented novel methodology, as well as its validity across a wider range of agroecosystem

Επίδραση της προσθήκης compost στην δομή του εδάφους και στα χημικά χαρακτηριστικά του - περίπτωση της Μηλιάς Χανίων

Μη διαθέσιμη περίληψηNot available summarizatio