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Pregled bibliografske jedinice broj: 988848

Automatic cost-effective method for land cover classification (ALCC)


Gašparović, Mateo; Zrinjski, Mladen; Gudelj, Marina
Automatic cost-effective method for land cover classification (ALCC) // Computers environment and urban systems, 76 (2019), 4; 1-10 doi:10.1016/j.compenvurbsys.2019.03.001 (međunarodna recenzija, članak, znanstveni)


Naslov
Automatic cost-effective method for land cover classification (ALCC)

Autori
Gašparović, Mateo ; Zrinjski, Mladen ; Gudelj, Marina

Izvornik
Computers environment and urban systems (0198-9715) 76 (2019), 4; 1-10

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

Ključne riječi
Landsat-8 ; Unsupervised classification ; k-means ; Spectral indices

Sažetak
The need for the detection and monitoring of changes in the environment is greater today than ever before. Through classification we can obtain insights into the state of the land surface. No known classification methods are fully automated, and their implementation requires preprocessing and postprocessing. This research provides a novel, fully automatic and cost-effective land cover classification method (ALCC). This novel automatic method does not require prior knowledge of the terrain or the assignment of training samples. The ALCC method is based on unsupervised classification methods, which is performed over the spectral indices rasters and six Landsat-8 30 m spatial resolution bands. The method was tested in three different study areas. Furthermore, all three study areas were classified by common supervised classification methods, namely, the Maximum Likelihood Classification (MLC) and the Random Forests (RF) method. For comparison accuracy, assessment of the three applied classification methods, namely, the figure of merit, overall agreement, omission and commission, were used. The results show that the overall agreement of the new automatic classification method for the Rijeka, Zagreb and Sarajevo study areas is 90.0%, 89.5% and 89.9%, respectively, and the overall agreement always falls between the overall agreement of the MLC method (88.1%, 88.9% and 86.7%, respectively) and the overall agreement of the RF method of classification (91.7%, 90.4% and 90.2%, respectively). These results confirm that this new automatic, cost-effective and accurate land cover classification method can be easily applied for numerous remote sensing applications.

Izvorni jezik
Engleski

Znanstvena područja
Geodezija



POVEZANOST RADA


Ustanove
Geodetski fakultet, Zagreb

Profili:

Avatar Url Mateo Gašparović (autor)

Avatar Url Mladen Zrinjski (autor)

Avatar Url Marina Gudelj (autor)

Citiraj ovu publikaciju

Gašparović, Mateo; Zrinjski, Mladen; Gudelj, Marina
Automatic cost-effective method for land cover classification (ALCC) // Computers environment and urban systems, 76 (2019), 4; 1-10 doi:10.1016/j.compenvurbsys.2019.03.001 (međunarodna recenzija, članak, znanstveni)
Gašparović, M., Zrinjski, M. & Gudelj, M. (2019) Automatic cost-effective method for land cover classification (ALCC). Computers environment and urban systems, 76 (4), 1-10 doi:10.1016/j.compenvurbsys.2019.03.001.
@article{article, year = {2019}, pages = {1-10}, DOI = {10.1016/j.compenvurbsys.2019.03.001}, keywords = {Landsat-8, Unsupervised classification, k-means, Spectral indices}, journal = {Computers environment and urban systems}, doi = {10.1016/j.compenvurbsys.2019.03.001}, volume = {76}, number = {4}, issn = {0198-9715}, title = {Automatic cost-effective method for land cover classification (ALCC)}, keyword = {Landsat-8, Unsupervised classification, k-means, Spectral indices} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Social Science Citation Index (SSCI)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


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