126
Views
1
CrossRef citations to date
0
Altmetric
Research Article

Assessing multi-temporal changes of natural vegetation cover between 1987-2018 using serial NDVI: A case study of Tlemcen national park (north-west of Algeria)

&
Pages 37-53 | Published online: 03 Feb 2021
 

ABSTRACT

Landscape spatial metrics were investigated to assess changes of multi-temporal vegetation cover within the Tlemcen national park (TNP) in north-western Algeria over 31 years. Five landscape metrics, namely number of patches (NP), landscape shape index (LSI), class area (CA), largest patch index (LPI), and percentage of landscape (PLAND) were applied and analysed to assess the fragmentation in the TNP at landscape and class levels. Three Landsat images acquired at three periods of time (1987, 1999 and 2018) with different sensors, namely Thematic Mapper (TM), Enhanced Thematic Mapper (ETM+) and Operational Land Imager (OLI) were used. After rigorous pre-processing steps, these images were transformed and thresholded into Normalised Difference Vegetation Index (NDVI) maps that represent the major vegetation cover classes in TNP. The obtained results revealed that during the study period the TNP has undergone a progressive and significant landscape fragmentation.

Acknowledgments

The authors would like to thank the NASA-USGS for Landsat datasets, and the anonymous reviewers for their constructive comments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,097.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.