Impact of Iran's Forest Nationalization Law on Forest Cover Changes over Six Decades: A Case Study of a Zagros Sparse Coppice Oak Forest.
Google Earth Engine
change detection
conservation policies
declassified satellite photography
historical aerial photos
machine learning
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
12 Jan 2023
12 Jan 2023
Historique:
received:
05
12
2022
revised:
28
12
2022
accepted:
10
01
2023
entrez:
21
1
2023
pubmed:
22
1
2023
medline:
25
1
2023
Statut:
epublish
Résumé
Forest nationalization policies in developing countries have often led to a reduction in local forest ownership rights and short- or long-term exploitative behaviors of stakeholders. The purpose of this research is to quantify the effect of Iran's Forest Nationalization Law (FNL) in a part of Zagros Forest over a 68-year time period (1955-2022) using 1955 historical aerial photos, 1968 Corona spy satellite photography, and classification of multi-temporal Landsat satellite images. A past classification change detection technique was used to identify the extent and the pattern of land use changes in time. For this purpose, six periods were defined, to cover the time before and after the implementation of FNL. A 0.27% deforestation trend was identified over the period after the FNL. Dense and open forested area has decreased from 7175.62 ha and 68,927.46 ha in 1955 to 5664.26 ha and 59,223.38 ha in 2022. The FNL brought decisive changes in the legal and forest management systems at the state level, mainly by giving their ownership to the state. Accordingly, the FNL and the related conservation plans have not fully succeeded in protecting, rehabilitating, recovering, and developing the sparse Zagros Forest ecosystems, as their most important goals.
Identifiants
pubmed: 36679670
pii: s23020871
doi: 10.3390/s23020871
pmc: PMC9862390
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
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