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Weighting function alternatives for a subpixel allocation model / Y. Makido in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 11 (November 2007)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 73 n° 11 (November 2007) . - pp 1233 - 1240 Titre : Weighting function alternatives for a subpixel allocation model Type de document : Article/Communication Auteurs : Y. Makido, Auteur ; A. Shortridge, Auteur Année de publication : 2007 Article en page(s) : pp 1233 - 1240 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] allocation [Termes IGN] analyse infrapixellaire [Termes IGN] autocorrélation spatiale [Termes IGN] classification barycentrique [Termes IGN] image Ikonos [Termes IGN] interpolation inversement proportionnelle à la distance [Termes IGN] optimisation (mathématiques) [Termes IGN] précision de la classification Résumé : (Auteur) This study investigates the “pixel-swapping” optimization algorithm proposed by Atkinson for predicting subpixel land- cover distribution. Two limitations of this method are assessed: the arbitrary spatial range value and the arbitrary exponential model for characterizing spatial autocorrelation. Various alternative weighting functions are evaluated. For this assessment, two different simulation models are employed to develop spatially autocorrelated binary class raster maps. These rasters are then resampled to generate sets of representative medium-resolution class maps. Prior to conducting the subpixel allocation, the relationship between cell resolution and spatial autocorrelation, as measured by Moran’s I, is evaluated. It is discovered that the form of this relationship depends upon the simulation model. For all tested weighting functions (Nearest Neighbor, Gaussian, Exponential, and IDW), the pixel swapping method increased classification accuracy compared with the initial random allocation of subpixels. Nearest Neighbor allocation performs as well as the more complex models of spatial structure. Copyright ASPRS Numéro de notice : A2007-514 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.73.11.1233 En ligne : http://dx.doi.org/10.14358/PERS.73.11.1233 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28877 [article]

Assessing alternatives for modelling the spatial distribution of multiple land-cover classes at sub-pixel scales / Y. Makido in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 8 (August 2007)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 73 n° 8 (August 2007) . - pp 935 - 943 Titre : Assessing alternatives for modelling the spatial distribution of multiple land-cover classes at sub-pixel scales Type de document : Article/Communication Auteurs : Y. Makido, Auteur ; A. Shortridge, Auteur ; P. Messina, Auteur Année de publication : 2007 Article en page(s) : pp 935 - 943 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse comparative [Termes IGN] analyse infrapixellaire [Termes IGN] autocorrélation spatiale [Termes IGN] distribution spatiale [Termes IGN] image Landsat-ETM+ Résumé : (Auteur) We introduce and evaluate three methods for modeling the spatial distribution of multiple land-cover classes at subpixel scales: (a) sequential categorical swapping, (b) simultaneous categorical swapping, and (c) simulated annealing. Method 1, a modification of a binary pixel-swapping algorithm, allocates each class in turn to maximize internal spatial autocorrelation. Method 2 simultaneously examines all pairs of cell-class combinations within a pixel to determine the most appropriate pairs of sub-pixels to swap. Method 3 employs simulated annealing to swap cells. While convergence is relatively slow, Method 3 offers increased flexibility. Each method is applied to a classified Landsat-7 ETM dataset that has been resampled to a spatial resolution of 210 m, and evaluated for accuracy performance and computational efficiency. Numéro de notice : A2007-371 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.73.8.935 En ligne : http://dx.doi.org/10.14358/PERS.73.8.935 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28734 [article]