Uncertainty in Land Value Modeling of the San José Metropolitan Region, Costa Rica

 

Đã lưu trong:
Chi tiết về thư mục
Nhiều tác giả: Pérez Molina, Eduardo, Vargas Aguilar, Darío
Định dạng: artículo original
Trạng thái:Versión publicada
Ngày xuất bản:2023
Miêu tả: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).
Quốc gia:Portal de Revistas UCR
Tổ chức giáo dục:Universidad de Costa Rica
Repositorio:Portal de Revistas UCR
Ngôn ngữ:Inglés
OAI Identifier:oai:portal.ucr.ac.cr:article/56618
Truy cập trực tuyến:https://revistas.ucr.ac.cr/index.php/ingenieria/article/view/56618
Từ khóa:Extrapolation
land values
sequential Gaussian
simulation
spatial factors
uncertainty
Extrapolación
factores espaciales
incertidumbre
simulación gaussiana secuencial
valor del suelo