Accurate forest assessment is essential to detect and tackle deforestation, especially in emerging economies. In Colombia, three different geo-spatial data sources are available for forest monitoring: the European Space Agency (ESA), the Institute for Hydrology, Meteorology and Environmental Studies (IDEAM), and the Global Forest Change Data (GFCD) from the University of Maryland. These information sources have distinct characteristics, purposes, and coverage, and their peculiarities can lead to marked differences in the results when they are used to produce forest cover maps. In this study, we determine the optimal forest threshold for GFCD and assess the accuracy of the three data sources in mapping forests, on the basis of a stratified sample of sites, with Colombian ecoregions used as strata. At each site, the classification into forest or non-forest, according to one of the sources, is compared with reference data collected through Google Earth imagery and landscape photographs. Accuracy measures are produced at both the ecoregion and national level. IDEAM and GFCD prove to be quite accurate in most cases, and each of them turns out to be the best forest map in about half of the ecoregions. GFCD’s optimal threshold is found to be equal to 90% in almost all those ecoregions for which it represents the best performing data set.

An accuracy assessment of three forest cover databases in Colombia / Rivadeneyra García, Perla; Scaccia, Luisa; Salvati, Luca. - In: ENVIRONMENTAL AND ECOLOGICAL STATISTICS. - ISSN 1352-8505. - 30(2023), pp. 443-475. [10.1007/s10651-023-00571-w]

An accuracy assessment of three forest cover databases in Colombia

Luisa Scaccia;Luca Salvati
2023

Abstract

Accurate forest assessment is essential to detect and tackle deforestation, especially in emerging economies. In Colombia, three different geo-spatial data sources are available for forest monitoring: the European Space Agency (ESA), the Institute for Hydrology, Meteorology and Environmental Studies (IDEAM), and the Global Forest Change Data (GFCD) from the University of Maryland. These information sources have distinct characteristics, purposes, and coverage, and their peculiarities can lead to marked differences in the results when they are used to produce forest cover maps. In this study, we determine the optimal forest threshold for GFCD and assess the accuracy of the three data sources in mapping forests, on the basis of a stratified sample of sites, with Colombian ecoregions used as strata. At each site, the classification into forest or non-forest, according to one of the sources, is compared with reference data collected through Google Earth imagery and landscape photographs. Accuracy measures are produced at both the ecoregion and national level. IDEAM and GFCD prove to be quite accurate in most cases, and each of them turns out to be the best forest map in about half of the ecoregions. GFCD’s optimal threshold is found to be equal to 90% in almost all those ecoregions for which it represents the best performing data set.
2023
accuracy assessment; ESA CCI land cover; global forest change; IDEAM; optimal forest threshold
01 Pubblicazione su rivista::01a Articolo in rivista
An accuracy assessment of three forest cover databases in Colombia / Rivadeneyra García, Perla; Scaccia, Luisa; Salvati, Luca. - In: ENVIRONMENTAL AND ECOLOGICAL STATISTICS. - ISSN 1352-8505. - 30(2023), pp. 443-475. [10.1007/s10651-023-00571-w]
File allegati a questo prodotto
File Dimensione Formato  
Salvati_accuracy-assessment_2023.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 3.62 MB
Formato Adobe PDF
3.62 MB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1693977
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 1
social impact