Remote Sensing Analyses to Detect Effects of

Community-based Rangeland Ecosystem

Management on Rangeland Vegetation

Jay Angerer

Texas A&M University

MOR2 Annual Meeting

June 15-16, 2012

Research Questions

During the last 30 years, has change occurred in vegetation characteristics such as green up, peak biomass and vegetation condition across Mongolia that can be detected with remote sensing?

Are there differences in vegetation response (using remote sensing data as a proxy) in soums managed by CBREM versus those that are not?

Can we detect changes in rainfall variability that could influence the status of grazinglands as equilibrium vs. non-equilibrium systems?

Historical Time Series

Analysis Time series analysis to examine

trends in satellite greenness (NDVI) for historical record (nationwide)

Patterns of green-up and senescence

Patterns in integrated NDVI (proxy for biomass accumulation)

Trends in vegetation condition index

TIMESAT Software TIMESAT software will be used for the developing the

time series data Calculates yearly beginning of season, end of season, amplitude, integrated

NDVI values

Available from: http://www.nateko.lu.se/TIMESAT/timesat.asp?cat=0

Green-up End of

Season

Integrated

NDVI

Data Sources

Advanced Very High Resolution Radiometer (AVHRR) – Normalized Difference Vegetation Index (NDVI) data Data processed by NASA-Global Inventory Modeling and

Mapping Studies

1981 to 2010

8 km resolution

Widely used

Available at http://www.glcf.umd.edu/data/gimms/

Paired Soum Analysis

Time series analysis for paired soums

Do differences exist in green-up, end of season, integrated NDVI, and vegetation condition for paired CBREM and non-CBREM soums?

Pre and Post CBREM analysis

What is the role of rainfall in this difference/pattern?

Vegetation Condition Index

Trends Vegetation Condition Index is calculated

by scaling NDVI for period of interest to

the historical minimum and maximum

(Current NDVI – minNDVI) / (maxNDVI – minNDVI) * 100

Values less than 30 are considered drought

Examine spatial extent and occurrence/intensity of

drought for the time series

Data Sources

Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data Expedited MODIS (eMODIS) - New product available from

USGS

2000 to present

Resolution of 250m

Available for Asia region

Download from: http://dds.cr.usgs.gov/emodis/CentralAsia/

AVHRR NDVI Pre and Post CBREM Analysis for each study soum

1981 to 1998 as Pre CBREM

1999 to Present as Post-CBREM

Data Sources

Unified Precipitation Dataset Product available from NOAA that uses optimal

interpolation

0.50 degree resolution (~55 km)

Daily Product, 1979 to present

Available from: ftp://ftp.cpc.ncep.noaa.gov/precip/CPC_UNI_PRCP/GAUGE_GLB/

Global Telecommunications System (GTS) Station Data Daily climate data for reporting World Meteorological

Organization (WMO) stations

Includes about 26 stations in Mongolia

Archived by Texas A&M

Rainfall Coefficient of

Variability (CV) Mapping Calculate Rainfall CV from CPC Unified

Precipitation data

Map the CV to identify potential equilibrium/non-

equilibrium zones

Examine in relation to paired soums

Rainfall CV Mapping

von Wehrden, H., J. Hanspach, P. Kaczensky, J. Fischer and K. Wesche. 2012.

A global assessment of the non-equilibrium concept in rangelands.

Ecological Applications, 22(2):393-399

Texas A&M splining of WMO

Dataset

Current Status

Processing AVHRR data using TIMESAT

software

eModis data has been processed, clipped,

and staged for TIMESAT analysis

CV analysis being conducted on Unified

Precipitation dataset

Questions or Comments?