Agro Climatic Zoning of Saffron Culture in Miyaneh City by Using WLC Method and Remote Sensing Data

Abstract

Recent continuous droughts and decreasing ground water tables have prompted efforts to improve irrigation schedules and introduce crops that need less water. A study was recently conducted to determine suitable zones for saffron in Miyaneh using Landsat-8 images and the weighted linear combination (WLC) method. Climatic and geographical indices for saffron cultivation in the region were for soil type, slope, soil moisture, and soil salinity. Parameters such as 30 years of data on climate, soil, and water conditions were collected from synoptic and climatologic stations such as Tabriz. Then, parameters were weighted using WLC for importance in each region. The data were transferred to expert choice and clustered, rated, and integrated to produce the last layer. The results showed that the southeastern and northwestern regions of Miyaneh, especially the banks of rivers and catchments, were identified as suitable places for saffron cultivation and that 28% of the area is in the suitable class, 36% in the relatively moderately suitable class, 20% in the critical suitability class, and the rest of the area, which covers about 16% of the area, is in the non-suitable class. Therefore, if it is possible to identify favorable areas for saffron cultivation according to the climatic requirements and it is possible in practice to achieve higher performance per unit area, that in itself will contribute to improved economic conditions and levels of income for farmers. Due to the special characteristics of saffron, substituting it for the cultivation of crops with high water requirements, such as onions, potatoes, tomatoes, etc., will help reduce water consumption.

Design and validation of a multi-objective waypoint planning algorithm for UAV spraying in orchards based on improved ant colony algorithm

“…The method based on manual extraction of coordinate points of fruit trees is cumbersome and not suitable for batch extraction of coordinates of citrus trees. The development of remote sensing images in recent years has make it possible to identify targets or large-scale target research in inaccessible environments ( Hu et al., 2021 ; Ghaderizadeh et al., 2022 ; Jalayer et al., 2022 ; Zamani et al., 2022 ). For example, using satellite remote sensing images to detect the impact of climate change on planting patterns ( Tariq et al., 2022a ), drawing and detecting the distribution map of farmland and crop types ( Tariq et al., 2022b ), and large-scale extraction of farmland ( Sharifi et al., 2022 ).…”

Landslide susceptibility mapping (LSM) of Swat District, Hindu Kush Himalayan region of Pakistan, using GIS-based bivariate modeling

“…Topographically, the study area is part of the Hindu Kush Himalayan range (Qasim and Hubacek, 2013), and the tourism hub of KPK has an area of 5,337 km 2 . The study area is divided into semiarid, sub-humid, and humid climate regions (Bahadar et al, 2015;Sharifi et al, 2022;Zamani et al, 2022). Geologically the research area is engraved in a Suture Zone (SZ) between the Indian Plate and Kohistan Island Arc (KIA).…”

Prediction of flash flood susceptibility using integrating analytic hierarchy process (AHP) and frequency ratio (FR) algorithms

“…Also, the outcomes of GIS-based statistical calculations showed more accuracy than using spatial data alone. In flood susceptibility studies the use of logistic regression, decision tree, Shannon's entropy model, ANN, FRM, fuzzy logic, and AHP models have frequently been used (Sharifi et al, 2022b;Felegari et al, 2022;Zamani et al, 2022). AHP is the most widely used model and is a more efficient and easily understandable model.…”