Inferring fine scale wild species distribution from spatially aggregated data - Archive ouverte HAL Access content directly
Preprints, Working Papers, ... Year :

Inferring fine scale wild species distribution from spatially aggregated data

(1) , (2) , (1) , (1) , (1) , (3)
1
2
3

Abstract

In spatial ecology, huge amount of aggregated and non-aggregated spatial data offer possibilities to map wild species distribution. However, this requires to properly handle the difference in spatial resolution between the different data sources. Such issue is often referred as the change of support (COS) problem. In this paper, we develop a hierarchical approach that allows (1) to handle COS for a mixture of zero-inflated positive continuous data and (2) to combine fine scale data and aggregated data. We assess the framework through simulations and apply it on real data for the common sole of the Bay of Biscay.
Fichier principal
Vignette du fichier
JRSSC-Jan-2023-0009_Proof_hi.pdf (2.46 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03878990 , version 1 (30-11-2022)
hal-03878990 , version 2 (09-01-2023)

Identifiers

  • HAL Id : hal-03878990 , version 2

Cite

Baptiste Alglave, Kasper Kristensen, Etienne Rivot, Mathieu Woillez, Youen Vermard, et al.. Inferring fine scale wild species distribution from spatially aggregated data. 2023. ⟨hal-03878990v2⟩
0 View
0 Download

Share

Gmail Facebook Twitter LinkedIn More