Document Type : Research Article
Authors
1 Department of Civil Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran
2 Bu Ali Sina University
3 Department of Plant Protection, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran
Abstract
Introduction
Walnut is one of the most important economic products of Iran and the world. Among the climatic factors effective in choosing the right place for planting walnut trees, we can mention the spring cold. Most of the walnut planting areas in Iran are mostly in the areas that have damaging colds in spring. The largest area under walnut cultivation in Iran is concentrated in the mountain hills and heights of the Zagros and Alborz mountain ranges. Every year, walnut production is limited by spring frosts, which, in addition to reducing production, can also damage sensitive plant tissues. Frost damage is one of the cases that are subject to compensation from the Agricultural Insurance Fund. Due to the high economic value of this product, an accurate, fast and low-cost estimation is necessary to evaluate the damages caused by this phenomenon on the walnut product. In this regard, in order to plan for the accurate calculation of the amount of compensation to the insurer, the insurer needs comprehensive information, so that it can estimate the performance losses caused by various factors. Remote sensing methods for frost monitoring using vegetation indicators are very efficient and effective. Therefore, this research examines spring frost damage by providing a quantitative index.
Materials and methods
In this research, frost damage of the Agricultural Insurance Fund was used for walnut trees. The damage assessment was presented over a period of nine years.Vegetation index values extracted from OLI, ETM+, MSI sensors have been used to overcome adverse weather conditions. Each of the vegetation indicators has different noises such as light changes during the day, wind speed, temperature, sun angle, etc. . In order to smooth the indices, SG filter was used. This filter was calculated with window size 11 and degree 2. In this filter, choosing the window size and degree is very important, because the small window size and degree cause noise to remain in the data, and if the window size and degree are chosen large, they lead to the loss of information related to vegetation indices. Meanwhile, choosing the reference year for comparison with other years was of particular importance. According to the consistency of the filtered indicators and the damages reported by the Agricultural Insurance Fund, the reference year was determined. The SFDI index was presented in each year using the filtered values of the relevant vegetation indices, between the reference year and other years. In general, the enclosed area of the two curves between the intersection points at the beginning and the end has indicated the values of the SFDI index in each year.
Results and Discussion
The relationship between SFDI index and damages was done through 2nd degree polynomial model and linear regression. The status of the SFDI index compared to the estimates of the agricultural insurance fund for all villages was investigated through two polynomial models of the 2nd degree and linear regression. The accuracy of the regression model was evaluated with criteria such as: r, RMSE, P-value. The value of r indicates how well a model can predict the value of the dependent variable in percentage terms. The higher the value of r, the better the model. RMSE values indicate how well a regression model can predict the value of the variable. The quantity P-value shows the significance of two independent and dependent variables, and values less than 5% indicate the existence of a relationship between two variables at a significant level of 95%. It is useful to calculate all three quantities for a given model, as each measure provides useful information. Spring frost damage index based on NDVI vegetation index with correlation coefficients of r = 0.927 and r = 0.823 were able to estimate the damage. Finally, the maps of spatial distribution and spring frost damage showed a good fit with the damage reported by the Agricultural Insurance Fund.
Conclusion
The SFDI index has provided a positive effect in the assessment of frost damage. Also, the results of the spatial distribution of the SFDI index have shown the effectiveness of this index, in such a way that with the increase of this index, the frost damage percentage of the agricultural insurance fund has also increased. The results showed that this index evaluated the effects of spring frost effectively and quickly and showed a good correlation with the decrease in crop yield.
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