La incertidumbre en la modelación de valores del suelo de la Gran Área Metropolitana, Costa Rica

Land value patterns show very distinct spatial associations with accessibility to urban centralities and physical factors in a territory. However, predictions based on models of this structure can be highly uncertain, as the underlying data also may show clustering (thus allowing for better predicti...

Celý popis

Uloženo v:
Podrobná bibliografie
Hlavní autoři: Pérez Molina, Eduardo, Vargas Aguilar, Darío
Médium: Online
Jazyk:eng
Vydáno: Universidad de Costa Rica 2023
Témata:
On-line přístup:https://revistas.ucr.ac.cr/index.php/ingenieria/article/view/56618
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Land value patterns show very distinct spatial associations with accessibility to urban centralities and physical factors in a territory. However, predictions based on models of this structure can be highly uncertain, as the underlying data also may show clustering (thus allowing for better predictions in more densely sampled areas). An assessment of this uncertainty for land value extrapolations in the the San José Metropolitan Region of Costa Rica is presented, via conditional Gaussian simulation, and the determinants of this uncertainty were explored, to find spatial strengths and weaknesses in the modeling efforts. The E-Type prediction from the conditional Gaussian simulation was found to marginally improve on ordinary kriging methods and it also provided explicit uncertainty patterns, which are the inverse of the land value prediction. The estimated uncertainty was found to decrease with characteristics that identify suitability for urban land use (and thus higher land values).