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Pregled bibliografske jedinice broj: 1204138

The relationship of environmental factors and the cropland suitability levels for soybean cultivation determined by machine learning


Radočaj, Dorijan; Vinković, Tomislav; Jurišić, Mladen; Gašparović, Mateo
The relationship of environmental factors and the cropland suitability levels for soybean cultivation determined by machine learning // Poljoprivreda (Osijek), 28 (2022), 1; 53-59 doi:10.18047/poljo.28.1.8 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1204138 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
The relationship of environmental factors and the cropland suitability levels for soybean cultivation determined by machine learning
(The relationship of environmental factors and the cropland suitability levels for soybean cultivation determined by machine learning)

Autori
Radočaj, Dorijan ; Vinković, Tomislav ; Jurišić, Mladen ; Gašparović, Mateo

Izvornik
Poljoprivreda (Osijek) (1330-7142) 28 (2022), 1; 53-59

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
land cover ; crop rotation ; soil types ; land management ; machine learning

Sažetak
The relationship between cropland suitability and the surrounding environmental factors has an important role in understanding and adjusting agricultural land management systems to natural cropland suitability. In this study, the relationship between soybean cropland suitability, determined by a novel machine learning based approach, and three major environmental factors in continental Croatia was evaluated. These constituted of two major land cover classes (forests and urban areas), utilized soybean growth seasons per agricultural parcels during a 2017– 2020 study period and soil types. The sensitivity analysis in geographic information system (GIS) using a raster overlay method, along with auxiliary spatial processing, was performed. The proximity of soybean agricultural parcels to forests showed a high correlation with suitability values, indicating a potential benefit of implementing agroforestry in land management plans. A notable amount of suitable agricultural parcels for soybean cultivation, which were previously not utilized for soybean cultivation was observed. A disregard of crop rotations was also noted, with the same soybean parcels within the study period in three and four years. This analysis showed considerable potential in understanding the effects of environmental factors on cropland suitability values, leading to more efficient land management policies and future suitability studies.

Izvorni jezik
Engleski

Znanstvena područja
Interdisciplinarne tehničke znanosti, Poljoprivreda (agronomija), Interdisciplinarne biotehničke znanosti



POVEZANOST RADA


Ustanove:
Geodetski fakultet, Zagreb,
Fakultet agrobiotehničkih znanosti Osijek

Poveznice na cjeloviti tekst rada:

doi hrcak.srce.hr

Citiraj ovu publikaciju:

Radočaj, Dorijan; Vinković, Tomislav; Jurišić, Mladen; Gašparović, Mateo
The relationship of environmental factors and the cropland suitability levels for soybean cultivation determined by machine learning // Poljoprivreda (Osijek), 28 (2022), 1; 53-59 doi:10.18047/poljo.28.1.8 (međunarodna recenzija, članak, znanstveni)
Radočaj, D., Vinković, T., Jurišić, M. & Gašparović, M. (2022) The relationship of environmental factors and the cropland suitability levels for soybean cultivation determined by machine learning. Poljoprivreda (Osijek), 28 (1), 53-59 doi:10.18047/poljo.28.1.8.
@article{article, author = {Rado\v{c}aj, Dorijan and Vinkovi\'{c}, Tomislav and Juri\v{s}i\'{c}, Mladen and Ga\v{s}parovi\'{c}, Mateo}, year = {2022}, pages = {53-59}, DOI = {10.18047/poljo.28.1.8}, keywords = {land cover, crop rotation, soil types, land management, machine learning}, journal = {Poljoprivreda (Osijek)}, doi = {10.18047/poljo.28.1.8}, volume = {28}, number = {1}, issn = {1330-7142}, title = {The relationship of environmental factors and the cropland suitability levels for soybean cultivation determined by machine learning}, keyword = {land cover, crop rotation, soil types, land management, machine learning} }
@article{article, author = {Rado\v{c}aj, Dorijan and Vinkovi\'{c}, Tomislav and Juri\v{s}i\'{c}, Mladen and Ga\v{s}parovi\'{c}, Mateo}, year = {2022}, pages = {53-59}, DOI = {10.18047/poljo.28.1.8}, keywords = {land cover, crop rotation, soil types, land management, machine learning}, journal = {Poljoprivreda (Osijek)}, doi = {10.18047/poljo.28.1.8}, volume = {28}, number = {1}, issn = {1330-7142}, title = {The relationship of environmental factors and the cropland suitability levels for soybean cultivation determined by machine learning}, keyword = {land cover, crop rotation, soil types, land management, machine learning} }

Časopis indeksira:


  • Web of Science Core Collection (WoSCC)
    • Emerging Sources Citation Index (ESCI)
  • Scopus


Citati:





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