- Tytuł:
- Application of landscape metrics and object-oriented remote sensing to detect the spatial arrangement of agricultural land
- Autorzy:
-
Safdary, Rezvan
Soffianian, Alireza
Pourmanafi, Saeid - Powiązania:
- https://bibliotekanauki.pl/articles/2054571.pdf
- Data publikacji:
- 2022-03-31
- Wydawca:
- Uniwersytet im. Adama Mickiewicza w Poznaniu
- Tematy:
-
crop type
segmentation
landscape metrics
Iran - Opis:
- 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.
- Źródło:
-
Quaestiones Geographicae; 2022, 41, 1; 25-35
0137-477X
2081-6383 - Pojawia się w:
- Quaestiones Geographicae
- Dostawca treści:
- Biblioteka Nauki
Artykuł