Textural ordination based on Fourier spectral decomposition: a method to analyze and compare landscape patterns
We propose an approach to texture characterization and comparison that directly uses the information of digital images of the earth surface without requesting a prior distinction of structural 'patches'. Digital images are partitioned into square 'windows' that define the scale of the analysis and which are submitted to the two-dimensional Fourier transform for extraction of a simplified textural characterization (in terms of coarseness) via the computation of a 'radial' power spectrum. Spectra computed from many images of the same size are systematically compared by means of a principal component analysis (PCA), which provides an ordination along a limited number of coarseness vs. fineness gradients. As an illustration, we applied this approach to digitized panchromatic air photos depicting various types of land cover in a semiarid landscape of northern Cameroon. We performed 'textural ordinations' at several scales by using square windows with sides ranging from 120 m to 1 km. At all scales, we found two coarseness gradients (PCA axes) based on the relative importance in the spectrum of large (> 50 km [exponent) -1), intermediate (30-50 km [exponent)-1), small (10-25 km [exponent) -1) and very small (<10 km [exponent) -1) spatial frequencies. Textural ordination based on Fourier spectra provides a powerful and consistent framework to identifying prominent scales of landscape patterns and to compare scaling properties across landscapes.
| Main Authors: | , , |
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| Format: | article biblioteca |
| Language: | eng |
| Subjects: | U30 - Méthodes de recherche, U10 - Informatique, mathématiques et statistiques, P31 - Levés et cartographie des sols, modèle mathématique, télédétection, cartographie, analyse d'image, paysage, http://aims.fao.org/aos/agrovoc/c_24199, http://aims.fao.org/aos/agrovoc/c_6498, http://aims.fao.org/aos/agrovoc/c_1344, http://aims.fao.org/aos/agrovoc/c_36762, http://aims.fao.org/aos/agrovoc/c_4185, http://aims.fao.org/aos/agrovoc/c_6734, http://aims.fao.org/aos/agrovoc/c_1229, |
| Online Access: | http://agritrop.cirad.fr/560148/ http://agritrop.cirad.fr/560148/1/document_560148.pdf |
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| Summary: | We propose an approach to texture characterization and comparison that directly uses the information of digital images of the earth surface without requesting a prior distinction of structural 'patches'. Digital images are partitioned into square 'windows' that define the scale of the analysis and which are submitted to the two-dimensional Fourier transform for extraction of a simplified textural characterization (in terms of coarseness) via the computation of a 'radial' power spectrum. Spectra computed from many images of the same size are systematically compared by means of a principal component analysis (PCA), which provides an ordination along a limited number of coarseness vs. fineness gradients. As an illustration, we applied this approach to digitized panchromatic air photos depicting various types of land cover in a semiarid landscape of northern Cameroon. We performed 'textural ordinations' at several scales by using square windows with sides ranging from 120 m to 1 km. At all scales, we found two coarseness gradients (PCA axes) based on the relative importance in the spectrum of large (> 50 km [exponent) -1), intermediate (30-50 km [exponent)-1), small (10-25 km [exponent) -1) and very small (<10 km [exponent) -1) spatial frequencies. Textural ordination based on Fourier spectra provides a powerful and consistent framework to identifying prominent scales of landscape patterns and to compare scaling properties across landscapes. |
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