Author: Administrator; jradema
Date: 2003-04-13

*Introduction
*Field Methods
*Image Processing
*Results
*Results
*Discussion

Estimating pine tree biomass using NDVI, vegetation corrected NDVI and red band radiance
John Rademacher

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Tree biomass, oven dry weight of living tree tissue expressed as Mg/ha, is an important variable in estimating carbon budgets, fire behavior and edge modeling. In the past, landscape level biomass estimates relied on using point data and scaling it to a landscape level by using Forest Service (FS) stand maps. Unfortunate, the FS stand maps were never intended to be used in this fashion creating inaccuracies in fine scale landscape biomass estimates. Recently, AVHR satellite using the NDVI vegetative index accurately estimated tree biomass at a course scale (1km resolution). Unfortunately, fine scale landscape studies are unable to use course scale biomass estimate. A few studies have shown landsat 7 band is negatively correlated with tree biomass (r=-.56 jake pine and r=-.88 wet land vegetation).
The objective of this study was to determine the accuracy of NDVI vegetation correction or red wavelength radiance on tree biomass estimates using a 2001 landsat 7 image.
Terminology
Edge: The boundary between two contrasting vegetative patch types.
Patch: A homogeneous vegetative stand (similar species, age, biomass…)
Interior patch: Area of a patch that is not influenced by adjacent edges

Study site
The study site is located in the northern portion of Chequamegon National Forest in northern Wisconsin (Washburn ranger district, 46º30’-46º45’N, 91º02’-91º22’W).
The site is characterized by Precambrian shield bedrock and Wisconsin-age glaciated landscapes. The soils are typically deep loamy, glacial outwashed sands, classified as Psamments and Orthods. The topography of the region is generally flat to gently rolling hills and the elevation ranges between 232 and 459 meters. Landforms are characteristically level terraces and pitted outwashes.
Field data collection
During the 2002 field season fifty .05 ha circular were established within the two forest types (jake pine, red pine and mixed hardwood). Each forest type was further divided by age; young, intermediate young, intermediate old and mature. Every forest age group had 5 plots.
Biomass calculations
Total above ground tree biomass was estimated by using the equation M=aDb , where M is the oven dry weight of total above ground tree biomass per (kg), D is the diameter at breast height (cm) and a and b are regression parameters. We used reported closest geographical regression parametersfor red pine (Pinus resinosa), (Perala 1994, Ter-Mikaelian 1997 and Ker 1980) jack pine (Pinus banksiana) (Perala 1994, Ter-Mikaelian 1997 and Hegyi 1972), white birch (Betula papyrifera) , big tooth aspen (Populus grandidentata), Red oak (Quercus rubra), sugar maple (Acer saccharum), Trembling aspen (Populus tremulodies) (Perala 1994 Ter-Mikaelian 1997), Red maple (Acer rubrum)(Crow 1983 Ter-Mikaelian 1997) and choke cherry (Prunus virginiana) (Young 1980 ).
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Introduction:

Field Methods

Field Methods

Introduction:

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Field Methods

Introduction:

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The 2001 Landsat 7 image was sub-sampled to only contain Chequamegon National Forest.
NDVI (band 3– band 4 ) / (band 3 +band 4)The digital number for each band was converted to radiance by using the equation found in chapter 11 of the Landsat 7 user’s handbook
Vegetation corrected NDVI was calculated by using the equation,
(band 3– band 4 ) / (band 3 +band 4)*(1 - band5 - min band5)/(band 5 max - band 5 min). The digital number for each band was converted to radiance by using the equation found in chapter 11 of the Landsat 7 user’s handbook and a conditional equation in ERDAS was used to remove all negative reflectance values. .
Red wave length radiance was calculated by converting the digital number to radiance by using the equation found in chapter 11 of the Landsat 7 user’s handbook

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Image Processing

Image Processing

NDVI (X axis) vs. pine tree biomass (y axis).
NDVI vegetative correction (X axis) vs. pine tree biomass (y axis). Circled area represents five late succession jack pine open canopy forest (50 years old) and two intermediate old jack pine plot (27 years old) that had a road influencing the NDVI value ( the plot was less than two pixels away from the road).
Red band radiance (x axis) vs. pine tree biomass (y axis). Circled area represents five late succession jack pine open canopy forest (50 years old) and one intermediate old jack pine plot (27 years old) that had a road influencing the radiance value (the plot was less than two pixels away from the road).

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Results

Results

Interior patch pine biomass can be predicted in the Chequamegon National Forest by using either red reflectance or NDVI vegetation correction. Both methods have limitations in 1) estimating late succession open canopy jack pine forest and 2) estimating tree biomass near roads or high contrast edges (see outliers on results graph). Preliminary data indicates road affect can influence the vegetative corrected NDVI and red ban radiance up to two pixels on both sides of the road. This is a major limitation in estimating biomass in heavily fragmented landscape such as the Chequamegon National Forest. In the Chequamegon National Forest 8% of the total area is within two pixels from a road and approximately 42% of the total area is influenced by at least one edge. To adequately estimate landscape level biomass at 30 meter we need to see if there is a relationship between vegetative corrected NDVI or red reflectance and edge biomass.

Discussion

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Total above ground pine tree biomass estimation map using NDVIc expressed as Mg/ha. White areas represent hardwood and shrub patch types.
Total above ground pine tree biomass estimation map using red band radiance expressed as Mg/ha. White areas represent hardwood and shrub patch types.
One to one line comparison of NDVIc and red band radiance biomass estimations. 1/3 of the data points were used to construct this graph.

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