Estimation of Spring Frost Effects on Walnut Trees using Remote Sensing from 2013 to 2018

نوع: Type: thesis

مقطع: Segment: masters

عنوان: Title: Estimation of Spring Frost Effects on Walnut Trees using Remote Sensing from 2013 to 2018

ارائه دهنده: Provider: Elham Gohari

اساتید راهنما: Supervisors: DR.Hosein Torabzadeh Khorasani

اساتید مشاور: Advisory Professors:

اساتید ممتحن یا داور: Examining professors or referees: DR.Morteza heidari Mozafar, DR. Safar Marofi

زمان و تاریخ ارائه: Time and date of presentation: 2022

مکان ارائه: Place of presentation: Room 2

چکیده: Abstract: One of the issues in orchards is crop loss due to sudden frosts and negative effects on yield and reduced yields. Spring frost damage is one of the items covered by the Agricultural Insurance Fund. Due to the relatively high economic value of horticultural products, more accurate methods should be used to estimate the amount of damage. Unlike crops, which are widely and uniformly cultivated, generalization of sampling methods to the whole region is very difficult and reduces the accuracy of damage estimation models. The purpose of this study is to provide a quantitative indicator for estimating the amount of damage to walnut trees based on observations of Landsat and Sentinel-2 satellites. Therefore, with the help of NDVI, EVI and GI vegetation time series, the spring frost damage index (SFDI) for walnut orchards in Tuyserkan city was calculated and evaluated over a period of nine years (2013 to 2021). The Savitzky-Golay (SG) smoothing filter is also used for vegetation indices to reduce annoying effects such as clouds, dust and noise. To produce the SFDI index, it is necessary to determine the year without frost, which was selected as the reference in 2013 based on the reports of the Agricultural Insurance Fund and the weather. By comparing the time series of each year with the reference year and calculating the area between the two curves, the SFDI index is obtained, which is related to the damage to walnut trees. Evaluation of the performance of the SFDI index, compared to the estimates of the Agricultural Insurance Fund, shows that the SFDINDVI index is able to estimate the damage with high accuracy (R2 = 0.71). Finally, according to the proposed index, a spatial distribution map of spring frost damage was produced in the study period in the region, which can be used as a basis for evaluation. Key Words: Tuyserkan, Product damage, Walnut trees, Spring frost, Remote Sensing

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