1990
DOI: 10.1080/10106049009354265
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Visual versus digital analysis for vegetation mapping: Some examples on central Spain

Abstract: Digital processing of Landsat images has been considered the most appropriate interpretation method for vegetation mapping. However, digital processing presents several difficulties: (i) it demands significant inversions, with respect both the images and the equipment; (ii) it presents problems to discriminate heterogeneous categories, and (iii) it requires much more training effort.Visual analysis, on the other hand, is less demanding both in economic investments and training. Therefore, it is a fruitful alte… Show more

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Cited by 9 publications
(3 citation statements)
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“…Classification accuracy assessment was carried out by calculating the overall accuracy of the classification process (Langley et al. 2001; Chuvieco and Vega 1990) and the kappa (κ) coefficient, which expresses the proportionate reduction in error generated by a classification process compared with the error of a completely random classification (Congalton 1991). The level of accuracy for the 1967 CORONA map output was 69.1%, κ= 69%.…”
Section: Methodsmentioning
confidence: 99%
“…Classification accuracy assessment was carried out by calculating the overall accuracy of the classification process (Langley et al. 2001; Chuvieco and Vega 1990) and the kappa (κ) coefficient, which expresses the proportionate reduction in error generated by a classification process compared with the error of a completely random classification (Congalton 1991). The level of accuracy for the 1967 CORONA map output was 69.1%, κ= 69%.…”
Section: Methodsmentioning
confidence: 99%
“…Mapping was performed manually, by the visual interpretation of orthoimages, to achieve the adequate discrimination of the different land types, despite their spectral proximity across the nonhomogeneous study area. This approach was selected since it allows well-trained human image interpreters, with personal experience and knowledge of the area, to clearly detect colour gradations and to integrate textural and contextual information at a small or medium scale [34,35].…”
Section: Mapping the Land Covermentioning
confidence: 99%
“…This image has only two values, usually one and zero; the 1's represent the areas that meet the stated criteria, while the 0's represent areas that do not meet the criteria (McKendy et al, 1992). Thus, by applying a masking operation, particular subtle features can be isolated from a sub-scene, and with the help of ancillary information or visual interpretation (see Chuvieco and Vega, 1990), they can be incorporated again, from a separate layer, into the generated land use/land cover map.…”
Section: Supervised Classification and Binary Maskingmentioning
confidence: 99%