کاربرد شاخص‌های توپوگرافی و طیفی در تعیین نواحی مدیریتی در مزارع کشت گندم دیم، قزوین

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه علوم و مهندسی خاک، دانشکده علوم کشاورزی دانشگاه گیلان، ایران

2 گروه علوم خاک، دانشکده علوم کشاورزی، دانشگاه گیلان، رشت، ایران

3 'گروه علوم و مهندسی خاک، دانشکده کشاورزی، دانشگاه بوعلی سینا-همدان، ایران

4 گروه علوم و مهندسی خاک، دانشکده کشاورزی، دانشگاه لرستان، خرم آباد، ایران

چکیده

مدیریت پایدار خاک با درک صحیح از ویژگی‌های خاک به حفظ حاصلخیزی و جلوگیری از تخریب آن کمک می‌کند. این تحقیق به منظور ارزیابی پتانسیل استفاده از مناطق مدیریت خاک (MZs) به عنوان روشی کارآمد برای بهبود بهره وری کشت گندم انجام شد. بر‌این‌اساس تعداد 140 نمونه خاک از مزارع گندم دیم برداشت شد. از ویژگی‌های خاکی به همراه ویژگی‌ها و شاخص‌های توپوگرافی و طیفی جهت تعیین MZs استفاده گردید. ویژگی‌های توپوگرافی مورد استفاده در این مطالعه با استفاده از نرم‌افزار7.8.2 SAGA و نقشه DEM منطقه مورد مطالعه استخراج گردید. تهیه نقشه ویژگی‌ها، انتخاب ویژگی-های بهینه با استفاده از آنالیز مولفه‌های اصلی (PCA)، تقسیم‌بندی مزرعه بر‌پایه ویژگی‌های منطقه‌ای و توپوگرافی بهینه با استفاده از الگوریتم‌های خوشه‌ای در ترکیب با زمین‌آمار، مراحل ایجاد MZs در این مطالعه بودند. شاخص عملکرد فازی (FPI) و آنتروپی طبقه‌بندی نرمال‌شده (NCE) جهت ارزیابی تعداد بهینه MZs بررسی گردید. تجزیه و تحلیل نیم‌تغییر‌نما، الگوی توزیع مکانی متنوع با وابستگی مکانی متوسط تا قوی را برای اکثر ویژگی‌ها در منطقه مطالعاتی نشان داد. در نهایت شش PC با مقادیر ویژه بیشتر از 1 با مجموع 3/76درصد از واریانس کل برای تجزیه و تحلیل بیشتر مورد استفاده قرار گرفتند. بر‌اساس حداقل مقدار FPI و NCE، شش ناحیه مدیریتی شناسایی شد. نتایج مقایسه میانگین‌ها نشان‌دهنده تفاوت در ویژگی‌ها در MZs است. این مطالعه نشان داد که تعیین MZs  بر اساس تغییرات مکانی ویژگی‌های توپوگرافی منطقه می‌تواند به طور موثری در شناسایی منابع اصلی تغییرپذیری عملکرد محصول و مدیریت خاک برای به حداکثر رساندن تولید محصول استفاده شود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Using topographical and spectral indices to delineate management zone in drylands wheat cultivated area, Qazvin.

نویسندگان [English]

  • Golnaz Ebrahimzadeh 1
  • Nafiseh Yaghmaeian Mahabadi 2
  • Hossein Bayat: 3
  • Hamid Reza Matinfar 4
1 Department of Soil Science, Faculty of Agricultural Sciences, University of Guilan, Rasht
2 Department of Soil Science, Faculty of Agricultural Sciences, University of Guilan, Iran
3 Department of Soil Science, Faculty of Agricultural Sciences, University of Bu-Ali Sina, Hamedan, Iran
4 Department of Soil Science, Faculty of Agricultural Sciences, Lorestan University , Khorramabad, Iran
چکیده [English]

Sustainable soil management with a correct understanding of soil properties helps to maintain soil fertility and prevent soil degradation. This research was conducted to evaluate the potentional use of soil management zones (MZs) as an efficient method to improve the productivity of wheat cultivation. According to this, 140 soil samples were taken randomly from wheat fields. Physical and chemical properties, along with topographical and spectral indices, were used to delineate MZs. Topographic attributes were extracted from digital elevation model (DEM) map preapared in SAGA GIS 7.8.2 software from the study area. Mapping the applied variables, selecting the optimal variable using principal component analysis, and delineating the study area based on soil properties, topographic attributes and spectral indices by using cluster algorithms in combination with geostatistics are major steps for delineating management zones. The fuzziness performance index (FPI) and normalized classification entropy (NCE) were investigated for the number of MZs. The semivariogram and kriging prediction maps showed different spatial distribution patterns, with spatial autocorrelation ranging varies from weak to strong for most of the applied variables. Finally, six principal components (PCs) with an eigenvalue of more than 1 and a total variance of 76.3% were chosen for further analysis. Based on the lowest values of FPI and NCE, six MZs were identified. The mean values demonstrate the difference between the applied properties in the MZs. This study showed that the delineation of MZs can be effectively used in soil management for cultivation crops to maximise crop production.

کلیدواژه‌ها [English]

  • management zones
  • Fuzzy clustering
  • geostatics

Using topographical and spectral indices to delineate management zone in drylands wheat cultivated area, Qazvin.

 

EXTENDED ABSTRACT

Introduction:

Effective and sustainable soil management practices are crucial for maintaining soil fertility and preventing soil degradation. Sustainable soil management involves adopting practices that minimize soil erosion, reduce nutrient loss, promote organic matter accumulation, and optimize water holding capacity.

Objective:

This study aims to address the critical aspect of sustainable soil management by employing a robust understanding of soil properties to ensure long-term soil fertility and prevent soil degradation. In particular, the study focuses on the cultivation of wheat and proposes the use of management zones (MZs) as an effective strategy to optimize crop yield and enhance overall productivity.

Material and method:

To carry out the study, a comprehensive sampling approach was adopted, involving the collection of 140 soil samples from various wheat fields. The samples were carefully analyzed to determine both the physical and chemical properties of the soil. Additionally, topographical and spectral indices were incorporated to gain a more holistic understanding of the study area. The next step involved the delineation of management zones based on the collected data. This process consisted of several key stages. First, the topographic properties of the study area were derived using advanced software tools like SAGA, coupled with a high-resolution Digital Elevation Model (DEM). These topographic properties played a crucial role in capturing the terrain characteristics that influence soil behavior and agricultural practices. To optimize the selection of variables for delineating the management zones, Principal Component Analysis (PCA) was employed. By reducing the dimensionality of the dataset, PCA facilitated a more efficient and insightful analysis of the data. The subsequent step involved clustering algorithms, which integrated the soil properties, topographical features, and spectral indices to define distinct management zones. This process incorporated geostatistical techniques to account for the spatial dependencies and variations within the study area. To evaluate the optimal number of management zones, two criteria, namely the Fuzziness Performance Index (FPI) and the Normalized Classification Entropy (NCE), were utilized. These criteria provided quantitative measures to assess the degree of uncertainty and classification accuracy, ensuring a robust and informed decision regarding the optimal number of management zones. The analysis of semivariograms and kriging, a geostatistical interpolation method, provided insights into the spatial distribution patterns and spatial dependency of the soil properties.

Result and Disscution:

The results indicated a range of spatial relationships, varying from weak to strong, across the different variables considered in the study. Based on a comprehensive analysis of the data, six Principal Components (PCs) were selected for further examination. These PCs, accounting for a substantial portion of the total variance (76.3%), were deemed crucial in explaining the underlying patterns and variations in the soil properties. Ultimately, based on the criteria of FPI and NCE, six distinct management zones were delineated. Each zone exhibited unique characteristics in terms of soil properties, topographical features, and spectral indices. The mean values of the soil properties within each management zone provided valuable insights into the variations and highlighted the heterogeneity across the study area. The findings of this study emphasize the effectiveness of adopting a systematic approach to delineate management zones for efficient soil management in wheat cultivation and other crop production systems. The proposed methodology allows for a targeted and site-specific approach, enabling farmers and land managers to optimize their agricultural practices, maximize crop production, and contribute to long-term soil health and sustainability.

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