• Title of article

    Mapping forest growth and decline in a temperate mixed forest using temporal trend analysis of Landsat imagery, 1987–2010

  • Author/Authors

    Czerwinski، نويسنده , , Chris J. and King، نويسنده , , Douglas J. and Mitchell، نويسنده , , Scott W.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2014
  • Pages
    13
  • From page
    188
  • To page
    200
  • Abstract
    Forest management seeks sustainability for a diverse set of goals, including economic objectives, provision of ecosystem services, and provision of a variety of possible land uses. It is important to quantify, map and monitor forest dynamics resulting from natural and anthropogenic processes over time periods appropriate to the temporal scale of change as well as to land management goals and decision making. This paper presents temporal trend analyses of temperate mixed forest dynamics in Gatineau Park, Québec, Canada, using a time series of Landsat 5 TM scenes. Several vegetation indices were first evaluated as indicators of field measured vegetation abundance parameters such as leaf area index, canopy openness, DBH, and basal area. Of these, Tasseled Cap Wetness (TCW) provided the best relationships (e.g., r = 0.81 against LAI) and it differentiated between coniferous, mixed and deciduous forests. Thirteen clear sky 5 TM scenes from the growing seasons of 1987 to 2010 were relatively calibrated and assembled into an image time-series. TCW applied to the image time-series followed by Theil–Sen and Contextual Mann–Kendall trend analysis detected subtle and gradual field-verified forest change. Gradual and abrupt forest decline or regrowth periods were identified; over the full period, 641 ha (1.8% of the park) exhibited statistically significant growth, and 689 ha (1.9%) exhibited decline. Mapping the timing, location, magnitude, and duration of forest change will help inform land management policy and actions within Gatineau Park and such methods may be applied in other similar forests.
  • Keywords
    Landsat time-series , Forest change , Temporal trend analysis , empirical modeling
  • Journal title
    Remote Sensing of Environment
  • Serial Year
    2014
  • Journal title
    Remote Sensing of Environment
  • Record number

    1634102