U.S. Department of the InteriorU.S. Geological Survey

Assessment of Conifer Health in Grand County, Colorado using Remotely Sensed Imagery

Chris ColeParallel IncorporatedU.S. Geological SurveyRocky Mountain Geographic Science Center

Purposes of study

Evaluate the feasibility of and develop methodology for the use of medium resolution remotely sensed imagery for conifer health assessment

Evaluate the potential to apply study results and methodologies to provide a strategic assessment of coniferous forest health statewide

Study Area

Grand County, Colorado A pilot study area for a host of USGS Fire Science

Activities Boasts a diverse range of land-cover, land

ownership Contains a wide range of coniferous forest health

conditions

Grand County, Colorado

Methodology

Summer/Fall 2008 Landsat TM and ASTER imagery were collected spanning Grand County

Persistent cloud cover complicated analysis and classification efforts

Imagery were radiometrically normalized via reflectance transformation (rescaled), linear regression

Mosaicked to form a single, cloud minimized three band multispectral dataset (green, red, NIR)

Methodology

Data derivatives from multispectral image Band Ratios Normalized Difference Vegetation Index (NDVI) – sensitive

to vegetation health

Samples selected – healthy and non-healthy conifers Were collected from 30-m multispectral data, based upon

image interpretation and spectral reflectance characteristics

High-resolution multispectral imagery also employed Multi-year Aerial Surveys Samples include range of conifer species type and health

Methodology

Sample signatures used to perform a supervised classification (maximum likelihood algorithm)

Produced an updated USGS NLCD for Grand County based upon 2008 remotely sensed data Focused upon characterization of changes in conifer and

mixed vegetation cover Thinning/clearcutting Emergent conifer regrowth

This dataset was used to exclude non-coniferous vegetation from final classification

Methodology – Spectral Plot

Unhealthy

Conifer

Healthy Conifer

Results

Accuracy assessment confirms this approach produced a consistent conifer health classification at 30-m resolution within Grand County Overall Classification accuracy 95.71% Producer’s accuracy 91.43% Kappa .9143

Methodologies are sound, flexible, and could be adapted and expanded to assess statewide coniferous forest health

1995 Conifer Health Conditions

Green = Likely Healthy Conifers

2006 Conifer Health Assessment

Green = Likely Healthy Conifers

Orange = Likely Unhealthy Conifers

2008 Conifer Health Assessment

Green = Likely Healthy Conifers

Orange = Likely Unhealthy Conifers

Next Steps

Field verification of Grand County classification results

Exploitation and classification of high resolution remotely sensed imagery for finer scale conifer health assessment QuickBird (2.4-meter) CAP ARCHER (1-meter)

Example – preliminary fine scale forest health analysis

CAP ARCHER Hyperspectral image, 1-meter spatial resolution

Preliminary generalized forest health classification using CAP ARCHER

Conclusions

Medium resolution remotely sensed imagery can be employed to assess coniferous forest health conditions in Grand County, Colorado

Results from these efforts, and methodologies can be applied to provide strategic assessment of forest health conditions statewide