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

Using Advanced Satellite Products to Better Understand I&M Data within the Context of the Larger Ecoregion

Kevin James, NPS I&M Heartland NetworkJeff Morisette, USGS Fort Collins Science Center

w/ Colin Talbert, USGS Fortand Pete Ma, NASA Goddard Space Flight Center

Background… “Parks are part of larger ecological systems and must

be managed in that context” (Fancy, Gross, & Carter, 2008).

Work funded through the USGS/NPS National Park Monitoring Project. Starting third year of funding.

Primary objective: help park managers use cutting edge moderate- (250m) and high- (30m) resolution remote sensing products to place I&M observations within the context of the larger ecosystem.

Background… The foundation for this work is existing and freely

available remote sensing data products:

NASA-funded 250m spatial resolution land surface phenology product for North America

Landsat data available from USGS for free.

These products represent a significant national investment in ecosystem monitoring.

Objectives: Characterize phenology across the Southern Plains,

Heartland, and Northern Great Plains Networks from 2000 on.

Building on the remote sensed vegetation indices and available Network data, identify appropriate sampling periods and locations that maximize information content for vegetation vital signs monitoring.

Evaluate the impact of management actions in light of intra- and inter-annual vegetation and climate variability.

Initial parks: selection criteria

Proposal focused on three networks: Southern Plains, Northern Great Plains, and Heartland Network

We wanted at least one park per network Fairly large in spatial extent Existing data from either I&M or fire

monitoring programs Fairly native grassland

Theodore Roosevelt NP

Windcave NP

Tallgrass Prairie NP

Chickasaw NRA

Lake Meredith NRA

MODIS land surface phenology data

Modified TIMESAT Parameters

Phenology Product User Guide, Tan et alhttp://accweb.nascom.nasa.gov/project/docs/User_guide_PHN.pdf.

1. Beginning of season2. End of season3. Length of season4. Base value5. Peak time 6. Peak value7. Amplitude8. Left derivative9. Right derivative10. Integral over season -

absolute11. Integral over season -

scaled 12. Maximum value13. Minimum value14. Mean value15. Root Mean Square Error

Web-Enabled Landsat Data (WELD) Monthly composites…

Displaying the imagery

ArcGIS Explorer application

Annual variations in species richness

Annual variation in and out of TAPR

Annual variations in species richness at TAPR

Variations in grassland obligates at TAPR

A (very) preliminary model for bird species richness

An ensemble model* using• Maxent• Boosted Regression Trees• Logistic Regression• MARS• Random Forest

* Following Stohlgren TJ, P. Ma, S. Kumar, M. Rocca, J.T. Morisette, C.S. Jarnevich, and N. Benson. 2010. Ensemble habitat mapping of invasive plant species., Risk Analysis, 30(2)224-235.

Future work

Develop a standard operating procedure (SOP) for integrating MODIS Phenology Data into the I&M program.

Correlative analysis connecting the I&M data to these remote sensing variables

Analysis of comparing phenology metrics inside and outside the park but with the stratification based on land cover type.