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Landscape metrics regularly outperform other traditionally-used ancillary datasets in dasymetric mapping of population / Heng Wan in Computers, Environment and Urban Systems, vol 99 (January 2023)  

Public [article]  inComputers, Environment and Urban Systems > vol 99 (January 2023) . - n° 101899 Titre : Landscape metrics regularly outperform other traditionally-used ancillary datasets in dasymetric mapping of population Type de document : Article/Communication Auteurs : Heng Wan, Auteur ; Jim Yoon, Auteur ; Vivek Srikrishnan, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 101899 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] carte thématique [Termes IGN] densité de population [Termes IGN] distribution spatiale [Termes IGN] Etats-Unis [Termes IGN] indicateur paysager [Termes IGN] interpolation [Termes IGN] occupation du sol [Termes IGN] paysage [Termes IGN] planification urbaine [Termes IGN] réduction d'échelle Résumé : (auteur) Population downscaling and interpolation methods are required to produce data which correspond to spatial units used in urban planning, demography, and environmental modeling. Population data are typically aggregated at census enumeration units, which can have arbitrary, temporally-evolving boundaries. Previous approaches to imperviousness-based dasymetric mapping ignore cell-level patterning of imperviousness within a spatial unit of prediction, which potentially serve as a strong indicator of population. Landscape metrics derived from imperviousness data offer a promising approach to capture these patterns. In this study, we incorporate landscape metrics derived from impervious cover percentage maps into intelligent dasymetric mapping to downscale population from census tracts to block groups in four states with varying population densities: Connecticut, South Carolina, West Virginia, and New Mexico. We compare the performance of the landscape metrics-based models against two baseline models in all four states across three different time periods. The results show that intelligent dasymetric mapping using landscape metrics generally outperforms the two baseline models. We further compare the performance of landscape metrics as an ancillary source of information for dasymetric mapping against other traditionally-used datasets (e.g., land use, roads, nighttime lights data) in three states (Connecticut, South Carolina, and New Mexico) in 2000. We find that class area, landscape shape index, and number of patches consistently achieve lower error rates than other ancillary datasets in all the three states. Numéro de notice : A2023-013 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101899 Date de publication en ligne : 02/11/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101899 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102130 [article]

Landscape metrics for characterization of forest landscapes in a sustainable management framework: Potential application and prevention of misuse / Emilio R. Diaz-Varela in Annals of Forest Science, Vol 66 n° 3 (April - May 2009)  

Public [article]  inAnnals of Forest Science > Vol 66 n° 3 (April - May 2009) . - n° 301 Titre : Landscape metrics for characterization of forest landscapes in a sustainable management framework: Potential application and prevention of misuse Titre original : Indices quantitatifs de paysage pour une caractérisation des paysages forestiers dans le cadre d'une gestion durable: application potentielle et prévention de mauvaise utilisation Type de document : Article/Communication Auteurs : Emilio R. Diaz-Varela, Auteur ; Manuel F. Marey-Pérez, Auteur ; Antonio Rigueiro-Rodriguez, Auteur ; Pedro Álvarez-Álvarez, Auteur Année de publication : 2009 Article en page(s) : n° 301 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] forêt [Termes IGN] gestion durable [Termes IGN] indicateur paysager [Termes IGN] modèle mathématique [Termes IGN] statistique mathématique [Vedettes matières IGN] Ecologie forestière Résumé : (auteur) The use of landscape indices in the analysis of forest landscapes offers great potential for integration of spatial pattern information in management processes, but requires understanding of the limitations and correct interpretation of results. In this sense, awareness of scale effects on landscape indices is essential, especially when the data available is restricted to low-resolution maps. In this study, developed within the framework of the FORSEE project, the objective was to define accurately the potential usefulness of applying landscape indices to low-resolution maps commonly used in forestry studies. Landscape indices were applied to two maps differing in spatial resolution, and subsets were defined for three spatial extensions. Correlation analysis and comparison of the results were carried out to enable identification of the most suitable indices for use with low resolution data. The analysis enabled identification of the least scale-dependent indices, which are thus more useful for extrapolating results from low-resolution data. In general terms, diversity and edge indices provided the best results. We conclude that some (but not all) of the landscape indices can be used to analyse low-resolution maps with acceptable results. Additional advice is made to prevent misuse of the application of landscape indices. Numéro de notice : A2009-704 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1051/forest/2009004 Date de publication en ligne : 10/03/2009 En ligne : https://www.afs-journal.org/articles/forest/full_html/2009/03/f07184/f07184.html Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=72056 [article]