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Action: Map forest disturbance (harvest, insect damage, storm damage, fire, etc) across a Landsat frame (timing, intensity, location) for 1984-2005 PowerPoint PPT Presentation


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Carbon Consequences. Biomass. Atmospheric source. Biologic C Flux. Regrowth Dominated. area histograms. Disturbance Dominated. Balanced. Action: Map forest disturbance (harvest, insect damage, storm damage, fire, etc) across a Landsat frame (timing, intensity, location) for 1984-2005.

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Action: Map forest disturbance (harvest, insect damage, storm damage, fire, etc) across a Landsat frame (timing, intensity, location) for 1984-2005

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Action map forest disturbance harvest insect damage storm damage fire etc across a landsat frame timing intensity

Carbon Consequences

Biomass

Atmospheric

source

Biologic

C Flux

Regrowth Dominated

area histograms

Disturbance Dominated

Balanced

Action: Map forest disturbance (harvest, insect damage, storm damage, fire, etc) across a Landsat frame (timing, intensity, location) for 1984-2005

Why? Interested in knowing forest carbon flux for North America, and how it is changing

Disturbance rate ->

Forest age ->

Carbon Flux


Action map forest disturbance harvest insect damage storm damage fire etc across a landsat frame timing intensity

Spatial Sample of US Disturbance

Annual or Biennial Image

Time Series (1972-2004)

Disturbance history / stand age

~25 Sample Sites


Action map forest disturbance harvest insect damage storm damage fire etc across a landsat frame timing intensity

Search for leaf-on, cloud-free annual images for a given location; optimize scene selection for anniversary dates.

Need to balance:

- cloud avoidance

- seasonality

- data quality (e.g. L7 vs L5)

- year selection

Download/buy data (Landsat-7 data now free; Landsat-5 by end of year)


Action map forest disturbance harvest insect damage storm damage fire etc across a landsat frame timing intensity

III. Orthorectify images to map base using GLS data set and SRTM digital topography; clip images to common X-Y spatial domain

- image-image registration essential; orthorectification desirable (facilitates GIS integration with other data)

IV. Calibrate each image to radiance, and apply atmospheric correction to convert images to surface reflectance

- not essential for change detection, but useful for additional studies (e.g. integration with other sensor data; canopy reflectance modeling)


Action map forest disturbance harvest insect damage storm damage fire etc across a landsat frame timing intensity

Orthorectified (2)


Action map forest disturbance harvest insect damage storm damage fire etc across a landsat frame timing intensity

Landsat 1Gs (2)


Action map forest disturbance harvest insect damage storm damage fire etc across a landsat frame timing intensity

100 km

Atmospheric Correction

1990’s Landsat-5 mosaic

TOA reflectance

Surface reflectance

BOREAS Study Region

100 km

100 km


Action map forest disturbance harvest insect damage storm damage fire etc across a landsat frame timing intensity

  • Find a sample of “mature” forest in each scene either by visual inspection or automated histogram thresholding; obtain mean reflectance and standard deviation for this set of pixels, for each scene

  • VI. Calculate per-pixel “Forestness Index” for each reflectance image according to:

  • FI = 1/n * S [(ri – rmf_mean) / rmf_stdev]

  • Where ri is the reflectance for band i (from 1,n), and rmf_mean, _stdev are the mean and standard deviations of the mature forest band for that image.


Action map forest disturbance harvest insect damage storm damage fire etc across a landsat frame timing intensity

(b) Disturbance

(a) Permanent forest

Forestness index

Year index (19xx)

(c) Thinning

(d) Aforestation

(e) Permanent non-forest

Time Trajectories of Forestness Index

Indicate Forest Dynamics


Action map forest disturbance harvest insect damage storm damage fire etc across a landsat frame timing intensity

VII Use rule-based system and thresholds to identify disturbance events (e.g. “if FI increases > 8 and stays >6 for at least three consecutive years, then mark Year 1 as disturbance”).

- agriculture identified by frequent large changes in FI value

- clouds can be identified as large “single event” changes in FI

VIII. Filter maps using sieve filter to remove speckle (single pixel changes).


Action map forest disturbance harvest insect damage storm damage fire etc across a landsat frame timing intensity

Fig. 1. (a) Location of samples selected across the conterminous United States, where biennial time

series stacks of Landsat images (LTSS) were acquired and analyzed to map forest disturbance

over the past three decades. The background forest group map shows that most of the forest

groups in the United States have been represented by the samples. (b) An example disturbance

map developed using the LTSS in a 28.5-kilometer-square area south of Lake Moultrie in South

Carolina. Persisting forest, nonforest, and water are shown in green, gray, and blue, respectively. All

other colors represent changes mapped in different years. (c) Percent of forest land disturbed annually,

calculated according to the derived disturbance map for the entire South Carolina Landsat scene.


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