Exploring land use prediction errors from area frame survey data

Exploration des erreurs de prédiction de l'occupation des sols à partir de données d'enquêtes parcellaires

Raja Chakir (), Thibault Laurent (), Anne Ruiz-Gazen (), Christine Thomas-Agnan () and Céline Vignes
Additional contact information
Raja Chakir: ECO-PUB - Economie Publique - INRA - Institut National de la Recherche Agronomique - AgroParisTech
Thibault Laurent: TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement
Anne Ruiz-Gazen: TSE-R - TSE-R Toulouse School of Economics – Recherche - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement
Christine Thomas-Agnan: TSE-R - TSE-R Toulouse School of Economics – Recherche - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement
Céline Vignes: TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement

Post-Print from HAL

Abstract: We consider the problem of areal level land use classification from the information provided by point level databases such as the area frame surveys (American NRI survey, EUROSTAT Lucas survey, French Teruti-Lucas survey) and easily accessible covariates. An exploratory analysis emphasizes the link between the areal level prediction error and a measure of difficulty of prediction given by the Gini-Simpson impurity index. We provide a methodology and an R code for allowing to explore the quality of an areal frame survey by generating synthetic data.

Keywords: American NRI survey; Gini-Simpson impurity index; Cover model; Teruti-Lucas survey (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

Published in Case Studies in Business, Industry and Government Statistics, 2018, 7 (1), pp.33-48

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05135972

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().