2014
DOI: 10.1007/s13762-014-0728-3
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Abstract: Land use classification is often the first step in land use studies and thus forms the basis for many earth science studies. In this paper, we focus on low-cost techniques for combining Landsat images with geographic information system approaches to create a land use map. In the Golestan region of Iran, we show that traditional supervised and unsupervised methods do not result in sufficiently accurate land use maps. Therefore, we evaluated a synthetic approach combining supervised and unsupervised methods with… Show more

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Cited by 61 publications
(23 citation statements)
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References 36 publications
(57 reference statements)
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“…), the large extents of disagreement between our Combined map and Miettinen2016 on the east coast of Sumatra ( Figure 5A) are likely coconut and sago plantations misclassified as oil palm in our Combined map. Our results support previous studies that found higher accuracies using supervised methods [61][62][63].…”
Section: Discussionsupporting
confidence: 92%
“…), the large extents of disagreement between our Combined map and Miettinen2016 on the east coast of Sumatra ( Figure 5A) are likely coconut and sago plantations misclassified as oil palm in our Combined map. Our results support previous studies that found higher accuracies using supervised methods [61][62][63].…”
Section: Discussionsupporting
confidence: 92%
“…These problems can be addressed using remote sensing data that offer a supplement to local measurements, providing comprehensive coverage of large areas. Such data are reliable and regularly updated (Chen et al 2013;Mujabar and Chandrasekar 2013;Mohammady et al 2015). LULC datasets are generally generated from available satellite data such as Landsat using state of the art classification methods including supervised, unsupervised, cross-correlation analysis, object-oriented and neural networks (Yuan et al 2005;Adepoju et al 2006;El Gammal et al 2010;Rawat and Kumar 2015).…”
Section: Introductionmentioning
confidence: 99%
“…A classificação foi executada pelo modo supervisionado na abordagem pixel-a-pixel, que agrega as regiões por semelhança de pixels nas amostras coletadas e que definem as classes temáticas que podem ser reconhecidas na imagem através de princípios como cor, tonalidade, textura, forma, grupamento, tamanho e sombra (MOHAMMADY, 2015(MOHAMMADY, , p.1515REIS, 2015, p. 61).…”
Section: Materiais E Métodosunclassified