Cropland expansion in Ecuador between 2000 and 2016.
Journal
PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081
Informations de publication
Date de publication:
2023
2023
Historique:
received:
17
08
2022
accepted:
05
09
2023
medline:
21
9
2023
pubmed:
19
9
2023
entrez:
19
9
2023
Statut:
epublish
Résumé
We describe changes in the cropland distribution for physiographic and bioregions of continental Ecuador between 2000 and 2016 using Landsat satellite data and government statistics. The cloudy conditions in Ecuador are a major constraint to satellite data analysis. We developed a two-stage cloud filtering algorithm to create cloud-free multi-temporal Landsat composites that were used in a Random Forest model to identify cropland. The overall accuracy of the model was 78% for the Coast region, 86% for the Andes, and 98% for the Amazon region. Cropland density was highest in the coastal lowlands and in the Andes between 2500 and 4400 m. During this period, cropland expansion was most pronounced in the Páramo, Chocó Tropical Rainforests, and Western Montane bioregions. There was no cropland expansion detected in the Eastern Foothill forests bioregion. The satellite data analysis further showed a small contraction of cropland (4%) in the Coast physiographic region, and cropland expansion in the Andes region (15%), especially above 3500m, and in the Amazon region (57%) between 2000 and 2016. The government data showed a similar contraction for the Coast (7%) but, in contrast with the satellite data, they showed a large agricultural contraction in the Andes (39%) and Amazon (50%). While the satellite data may be better at estimating relative change (trends), the government data may provide more accurate absolute numbers in some regions, especially the Amazon because separating pasture and tree crops from forest with satellite data is challenging. These discrepancies illustrate the need for careful evaluation and comparison of data from different sources when analyzing land use change.
Identifiants
pubmed: 37725616
doi: 10.1371/journal.pone.0291753
pii: PONE-D-22-23079
pmc: PMC10508625
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e0291753Informations de copyright
Copyright: © 2023 Ochoa-Brito et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
Références
Sensors (Basel). 2019 Mar 06;19(5):
pubmed: 30845748
Remote Sens Environ. 2016 Apr 28;Volume 185(Iss 2):46-56
pubmed: 32020955
Nat Food. 2022 Jan;3(1):19-28
pubmed: 37118483
PLoS One. 2019 Feb 1;14(2):e0211324
pubmed: 30707720
Land use policy. 2014 Jan 1;36:
pubmed: 24187416
PLoS One. 2020 Feb 12;15(2):e0228305
pubmed: 32049959
Philos Trans R Soc Lond B Biol Sci. 2010 Sep 27;365(1554):2779-91
pubmed: 20713384
Fam Med. 2005 May;37(5):360-3
pubmed: 15883903
Nat Commun. 2019 Jun 28;10(1):2844
pubmed: 31253787
Nat Ecol Evol. 2017 Aug;1(8):1129-1135
pubmed: 29046577