Afforestation Case Study Evaluations
To demonstrate NASA-CASA model estimates of afforestation carbon gains over time, several comparisons of
NASA-CASA model predictions to
case study afforestation projects are presented here. CQUEST users can
follow the steps outlined below to conduct similar afforestation
project evaluations anywhere in the
continental United States. Applicable CQUEST data layers are shown in red.
Carbon gains from NASA-CASA model NPP predictions are expressed at 1-km or 8-km spatial resolution in average flux units of g C m-2
Step 1: General Area Delineation
Unless an absolute location is already known, the user must decide on the general geographic area of the
reported carbon sequestration
project. This area is commonly determined in reference to a reported city,
county, or management unit location(s) under Political Features,
delineated in the following linked examples by a gray boundary line. A sub-area (not identified in the
examples) of 8x8 MODIS 1-km pixels is
selected to represent the geographic area characteristic of the land use conditions described in the case study, e.g. marginal cropland.
Step 2: Determining Baseline Cropland NPP Value
The lowest productivity cropland NPP value within the 8X8 km area, set from Crop NPP
Carbon, is identified as
a baseline for potential carbon gain. This value is then compared to the
NASA-CASA model estimate from annual Forest NPP Carbon , which
was derived from interpolated satellite
image products that cover the same 8x8 km project sub-area. CQUEST users may use the Select Box tool to
help identify the range of values in the 8X8 km area.
Step 3: Determining Predicted Forest NPP Value
Carbon sequestered over the projected years of afforestation is computed as the highest interpolated
forest NPP value from Forest NPP Carbon
within the same 8x8 km sub-area,
adjusted for the total area of the reported sequestration project. Subtraction of a fraction the baseline
Crop NPP Carbon (typically 20-30% per year) can be included to correct for carbon that might have been
stored in cropland soils in the absence of intensive cultivation.
Step 4: Adjustments for Carbon Loss
Users must infer the probable combined effects of dead biomass decomposition, forest disturbance, and aging
(abbreviated DDA for decomposition,
disturbance, and aging) on net carbon sequestration rates for the
projected length of the case study. In any forestation project, carbon sequestration
potential in vegetation and soils
may decline over a time period on the order of several decades to centuries, depending
upon the forest type, species selection,
soil nutrient availability, elevation, and latitudinal zone (Brown
et al., 1996).
For the case studies linked below, a constant DDA value of 0.5 was applied across all case study locations.
Comparison of projected afforestation carbon
gains in the United States with NASA-CASA model predictions of
gross carbon gain show close agreement (R2 = 0.81 for linear regression coefficient; p < 0.05).
have more specific estimates of DDA values for their locations, this variable may be adjusted to better
reflect individual project conditions.
Predicted forest wood biomass in Forest Wood Carbon from the NASA-CASA model
for a nearby (group of) currently
forested pixel(s) can be identified as an additional check on the
potential carbon sequestration reported for each reported afforestation project.
Click on the afforestation project locations in the map below to view example case study and model
Brown, S., J. Sathaye, M. Cannell, and P. Kauppi. 1996. Management of forests for mitigation of greenhouse
gas emissions. In R. T. Watson, M.C. Zinyowera,
and R.H. Moss (eds.), Climate Change 1995: Impacts,
Adaptations and Mitigation of Climate Change: Scientific-Technical Analyses. Contribution of Working Group
II to the Second Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University
Press, Cambridge and New York, Chapter 24.