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Related Experiment Video

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Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

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Monitoring vegetation change and dynamics on U.S. Army training lands using satellite image time series analysis.

J M S Hutchinson¹, A Jacquin², S L Hutchinson³

¹Department of Geography, Kansas State University, 118 Seaton Hall, Manhattan, KS 66506-2904, USA.

Journal of Environmental Management

|December 3, 2014

Summary

Sustainable management of military lands requires monitoring vegetation health. This study used BFAST on NDVI data to analyze vegetation trends at Fort Riley, revealing widespread browning and distinct post-disturbance responses, aiding land management.

Keywords:

BFAST Disturbance Military training activities Remote sensing Trend Vegetation dynamics

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Area of Science:

Environmental Science
Remote Sensing
Ecology

Background:

Military training lands require sustainable natural resource management.
Proactive monitoring is crucial for identifying environmental impacts on these lands.
Vegetation condition analysis offers valuable sustainability indicators for land managers.

Purpose of the Study:

To explore a method for analyzing vegetation condition and trends as sustainability indicators for military lands.
To assess the utility of these indicators for identifying vegetation-related environmental impacts.
To provide tools for commanders and land managers for sustainable land use.

Main Methods:

Applied the BFAST (Breaks For Additive Season and Trend) time series decomposition method.
Utilized a ten-year MODIS NDVI (Normalized Difference Vegetation Index) time series dataset.
Calculated three indicators of vegetation change from the BFAST trend component.

Main Results:

The majority of Fort Riley showed a browning trend between 2001 and 2010, validated by high-resolution imagery.
Significant differences in linear trend frequencies between Fort Riley and Konza Prairie Biological Station suggest links to land use.
Distinct post-disturbance vegetation trajectories were observed at the two sites, indicating varied responses to different disturbance types.

Conclusions:

Remotely sensed vegetation index time series with BFAST provide a rapid assessment of military training lands.
Characterizing vegetation trends and disturbance responses promotes sustainable military land use.
This approach aids land managers in targeting areas for rehabilitation activities.