Landsat time series analysis for temperate forest cover change detection in the Sierra Madre Occidental, Durango, Mexico

Alís Novo-Fernández, Shannon Franks, Christian Wehenkel, Pablito M. López-Serrano, Matthieu Molinier, Carlos A. López-Sánchez

Research output: Contribution to journalArticleScientificpeer-review

3 Citations (Scopus)

Abstract

The Sierra Madre Occidental (SMO) is the longest continuous mountain complex in Mexico and is characterised by high species diversity and a high proportion of endemism. The rate of deforestation is high in Mexico, as in other megadiverse countries, and protection of the country's biodiversity is a top priority. Quantification of changes in vegetation cover is essential for this purpose. Temporal information is required to enable classification of vegetation cover and change processes. In this study, the disturbances that occurred in the temperate forest of the SMO in the State of Durango (Mexico) during the period 1986–2012 were quantified using Landsat Time Series Stacks (LTSS) and the Vegetation Change Tracker (VCT) algorithm. The results obtained confirmed that land cover changes were detected with high overall accuracy (97.6%). In order to analyze the forest losses corresponding to the only official data available in Mexico, we retrieved land use and vegetation mapping (USV) data from the Mexican National Institute of Statistics and Geography (INEGI). The aridity index was established and fragmentation analysis was carried out in the study area, showing that forest pests and forest fires were the principal disturbance events in the SMO of Durango, and that the climate greatly influenced the occurrence of disturbances. The LTSS-VCT analysis revealed that for the period 1986–2012, about 34% of the temperate forest cover in the SMO in Durango was lost due to different types of disturbance, representing an annual rate of loss of forest cover of 1.3% and affecting 32,840 ha of land per year. The trend analysis of USV data showed very similar changes to those indicated by the LTSS-VCT analysis in terms of loss of temperate forest. However, differences were observed in regards to the absolute values of forest cover and vegetation loss, with analysis of the USV data indicating forest losses of 28% due to disturbances and an annual disturbance rate of 1%, affecting 49,940 ha of land per year. The LTSS-VCT approach proved efficient for mapping data on forest disturbance acquired by a medium spatial resolution (Landsat) sensor in the SMO in the State of Durango, providing satisfactory results and at low cost.
Original languageEnglish
Pages (from-to)230-244
Number of pages15
JournalInternational Journal of Applied Earth Observation and Geoinformation
Volume73
DOIs
Publication statusPublished - 2 Jul 2018
MoE publication typeNot Eligible

Fingerprint

Time series analysis
time series analysis
temperate forest
forest cover
Landsat
disturbance
vegetation mapping
vegetation
time series
Time series
vegetation cover
Biodiversity
trend analysis
endemism
aridity
forest fire
detection
Deforestation
deforestation
species diversity

Keywords

  • Change detection
  • Time series analysis
  • Landsat
  • Temperate forests
  • Vegetation change tracker

Cite this

Novo-Fernández, Alís ; Franks, Shannon ; Wehenkel, Christian ; López-Serrano, Pablito M. ; Molinier, Matthieu ; López-Sánchez, Carlos A. / Landsat time series analysis for temperate forest cover change detection in the Sierra Madre Occidental, Durango, Mexico. In: International Journal of Applied Earth Observation and Geoinformation. 2018 ; Vol. 73. pp. 230-244.
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abstract = "The Sierra Madre Occidental (SMO) is the longest continuous mountain complex in Mexico and is characterised by high species diversity and a high proportion of endemism. The rate of deforestation is high in Mexico, as in other megadiverse countries, and protection of the country's biodiversity is a top priority. Quantification of changes in vegetation cover is essential for this purpose. Temporal information is required to enable classification of vegetation cover and change processes. In this study, the disturbances that occurred in the temperate forest of the SMO in the State of Durango (Mexico) during the period 1986–2012 were quantified using Landsat Time Series Stacks (LTSS) and the Vegetation Change Tracker (VCT) algorithm. The results obtained confirmed that land cover changes were detected with high overall accuracy (97.6{\%}). In order to analyze the forest losses corresponding to the only official data available in Mexico, we retrieved land use and vegetation mapping (USV) data from the Mexican National Institute of Statistics and Geography (INEGI). The aridity index was established and fragmentation analysis was carried out in the study area, showing that forest pests and forest fires were the principal disturbance events in the SMO of Durango, and that the climate greatly influenced the occurrence of disturbances. The LTSS-VCT analysis revealed that for the period 1986–2012, about 34{\%} of the temperate forest cover in the SMO in Durango was lost due to different types of disturbance, representing an annual rate of loss of forest cover of 1.3{\%} and affecting 32,840 ha of land per year. The trend analysis of USV data showed very similar changes to those indicated by the LTSS-VCT analysis in terms of loss of temperate forest. However, differences were observed in regards to the absolute values of forest cover and vegetation loss, with analysis of the USV data indicating forest losses of 28{\%} due to disturbances and an annual disturbance rate of 1{\%}, affecting 49,940 ha of land per year. The LTSS-VCT approach proved efficient for mapping data on forest disturbance acquired by a medium spatial resolution (Landsat) sensor in the SMO in the State of Durango, providing satisfactory results and at low cost.",
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Landsat time series analysis for temperate forest cover change detection in the Sierra Madre Occidental, Durango, Mexico. / Novo-Fernández, Alís; Franks, Shannon; Wehenkel, Christian; López-Serrano, Pablito M.; Molinier, Matthieu; López-Sánchez, Carlos A.

In: International Journal of Applied Earth Observation and Geoinformation, Vol. 73, 02.07.2018, p. 230-244.

Research output: Contribution to journalArticleScientificpeer-review

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AU - Novo-Fernández, Alís

AU - Franks, Shannon

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