Investigating tundra and taiga biomes with remote sensing
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Investigating Tundra and Taiga Biomes with Remote Sensing. Jessica Robin SSAI/NASA/GSFC. Photo courtesy of M. K. Raynolds. Photo – M. K. Raynolds. Outline of presentation. Climate change and arctic vegetation Remote sensing research Field research by Martha Reynolds (UAF)

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Investigating Tundra and Taiga Biomes with Remote Sensing

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Investigating Tundra and Taiga Biomes with Remote Sensing

Jessica Robin


Photo courtesy of M. K. Raynolds

Photo – M. K. Raynolds

Outline of presentation

  • Climate change and arctic vegetation

  • Remote sensing research

  • Field research by Martha Reynolds (UAF)

  • Research with GLOBE data

Arctic Temperatures (1966-1995)

Image courtesy of National Snow & Ice Center

2001 temperatures compared to 1950 to 1981 “normal” temperatures

Image courtesy of Goddard Institute of Space Science

Northern Greening (1981-1999)

Image courtesy of Liming Zhou, Boston University

Photo – D. A. Walker

Arctic Climate Impact Assessment

Report put out in 2004 by the Arctic Council and the International Arctic Science Committee (IASC)International panel

The summary report, graphics and detailed scientific report can be found on the web at:

Key Findings of the ACIA regarding vegetation

Arctic vegetation zones are very likely to shift causing wide-ranging impacts.

  • Treeline is expected to move northward and to higher elevations, with forest replacing a significant fraction of existing tundra, and tundra vegetation moving into polar deserts.

  • More productive vegetation is likely to increase carbon uptake, although reduced reflectivity of the land is likely to outweigh this, causing further warming.

  • Disturbances such as insect outbreaks and forest fires are very likely to increase in frequency, severity and duration, facilitating invasion by non-native species.

  • Where suitable soils are present, agriculture will have the potential to expand northward due to a longer and warmer growing season.

Remote Sensing Research




Goetz et al. 2005 summary of 1981-2003 trends in AVHRR NDVI

Strong Positive


Near Zero


Strong Negative









Time-integrated NDVI

Jia and Epstein

Recent studies have shown increases in satellite-sensed indices (NDVI) of circumpolar tundra vegetation.

NDVI of boreal forests shows decreasing trends.

The spring season has started earlier and max NDVI has increased

  • NDVI trends for the forested and tundra regions, broken down by six-year intervals.

  • The forested areas show a recent decline in the maximum NDVI.

  • Tundra regions have shown a continued increase in NDVI and a marked 10-day shift toward earlier onset of greening.

  • There is no corresponding shift in the cessation of the greening period.

10% increase in NDVI

10-day spring shift in growing season length

Goetz et al. 2005. PNAS,102: 13521-13525

(Sturm et al. 2001)

Changes in arctic shrubs

Yukon Flats National Wildlife Refuge, Riordan et al. 2006 JGR

Shrinking lakes due to warmer temperatures leading to changes in permafrost and more evaporation affects vegetation.

Community changes in ITEX experiment after 6 years

  • Satellite data show changes

  • Greenhouse warming experiments show changes

  • but very few studies have been able to document changes occurring to undisturbed tundra

Open-top chamber


Field Research

Current research by Martha K. Raynolds University of Alaska Fairbanks

  • Trying to measure existing tundra vegetation conditions in enough detail and in enough places that future changes due to climate change can be measured.


Arctic tundra bioclimate subzones

a – mosses, liverworts and lichens, b – forbs, c – prostrate dwarf-shrubs, d – non-tussock graminoids, e -hemiprostrate dwarf shrubs, f – erect dwarf shrubs, g – low shrubs, h – tussock graminoids

  • Plant physiognomy occurring in different Tundra Bioclimate Subzones

  • A – mosses, liverworts and lichens with some grasses and forbs

  • B – rushes and prostrate dwarf shrubs with mosses, liverworts and lichens

  • C – hemiprostrate and prostrate dwarf shrubs with bryophytes and lichens

  • D – sedges, erect and prostrated dwarf shrubs with bryophytes and lichens

  • E – tussock sedges, low and erect dwarf shrubs with bryophytes and lichens


of the Tundra Bioclimate Zone

Subzone A

A = coldest

E = warmest


Subzone B

No shrubs

Erect dwarf





Subzone C

Subzone D


Subzone E

Research with GLOBE Data

Monitoring vegetation phenology with GLOBE Data

  • Satellite data from the past two decades shows a corresponding increase in growing season in northern latitudes

    (Myneni, R.B., Keeling, C.D., Tucker, C.J., Asrar, G., and Nemani, R.R., 1997, Increased plant growth in the northern high latitudes from 1981 to 1991, Nature, 386:698-702.)

  • However, minimal on-ground observations of plant phenology exist to validate such satellite findings


  • Analyze the efficacy of phenology monitoring using GLOBE and satellite derived vegetation indices from AVHRR and MODIS data

  • Compare AVHRR and MODIS data


10 Schools

Elementary-High School

Public, Charter, Private, Home

Anchorage area (3)

Fairbanks area (7)

Lat: 61.17° – 64.85° N

Lon: 147.52°-149.41° W



  • Students made observations & measurements (2001-2004)

    • budburst, green-up, leaf growth & green down

    • research focused on budburst and green-up

  • Trees/Shrubs: Betula, Populus, Salix

    (Viereck, Leslie, A. and Little, Elbert L. Jr. 1972. Alaska Trees and Shrubs. Agriculture Handbook No. 410. Forest Service, USDA, Washington D.C)



GLOBE Students, Alaska

Photo courtesy of Cheryl Pratt and Elena Sparrow, U of Alaska Fairbanks


  • Advanced Very High Resolution Radiometer

  • On board NOAA’s POES(Polar Orbiting Environmental Satellites) since 1979

  • Research includes NDVI data for Fairbanks and Anchorage regions from 2001 - 2004


  • Moderate Resolution Imaging Spectroradiometer

  • On board Terra – Earth Observing System (EOS)

  • Terra satellite launched in 1999

  • This research includes NDVI data for Fairbanks and Anchorage regions from 2001 - 2004

Comparison of satellite data


  • Different processing and spectral characteristics restrict continuity between AVHRR and MODIS NDVI datasets

  • NDVI has limitations in boreal regions due to snow, large extent of conifers, and clouds

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