Description

• Title:
  Application of landscape metrics and object-oriented remote sensing to detect the spatial arrangement of agricultural land
• Creator:
  Safdary, Rezvan;
  Soffianian, Alireza;
  Pourmanafi, Saeid
• Description:
  This study aims to investigate crop selection and spatial patterns of agricultural fields in a drought-affected region in Isfahan Province, central Iran. Based on field surveys portraying growth stages of the main crops including wheat, alfalfa, vegetables and fruit trees, three Landsat 8 operational land imager (OLI) images were acquired on March 15 (L1), June 27 (L2) and October 1 (L3), 2015. After performing radiometric and atmospheric corrections, Normalized Difference Vegetation Index (NDVI) maps of the images were produced and introduced to the Multi-Resolution Segmentation algorithm to delineate agricultural fields. An NDVI-based decision algorithm was then developed to identify crops devoted to each field. Finally, a set of landscape metrics including Number of Patches (NP), mean patch size (MPS), mean shape index (MSI), perimeter-to-area ratio (PARA) and Euclidian Nearest Neighborhood Distance (ENN) was utilized to evaluate their respective spatial formation. The results showed that nearly 46% of fields are devoted to wheat indicating that the landscape has been dramatically shifted towards wheat monoculture farming. Moreover, the farmers’ inclination to grow crops in large fields (approximate area of 1 ha) with more regular geometric shapes are considered as an effective way of optimising water use efficiency in areas experiencing significant water shortage.
• Object availability:
  free access
• Rights:
  Prawa autorskie (c) 2022 Rezvan Safdary, Alireza Soffianian, Saeid Pourmanafi
• Date:
  2022.03.31
• Type:
  info:eu-repo/semantics/article;
  info:eu-repo/semantics/publishedVersion;
  Recenzowany artykuł
• Language:
  English;
  eng
• Source:
  Quaestiones Geographicae; Vol. 41 No. 1 (2022); 25-35;
  Quaestiones Geographicae; Tom 41 Nr 1 (2022); 25-35;
  2081-6383;
  0137-477X
• Format:
  application/pdf
• Publisher:
  Adam Mickiewicz University Poznan
• Relation: http://pressto.amu.edu.pl/index.php/qg/article/view/33916/29415
• Subject:
  crop type;
  segmentation;
  landscape metrics;
  Iran
• Identifier: http://pressto.amu.edu.pl/index.php/qg/article/view/33916
• Data provider:
  Platforma Otwartych Czasopism Naukowych UAM
• Can I use it?:
  seek permission
• Type:
  other