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AN ECOLOGICAL REGIONALIZATION MODEL BASED ON NOAA/AVHRR DATA
Yingchun Zhou
Department of Geography, University of Nebraska-Lincoln, Lincoln, NE 68508, USA
Email: yzhou@unlinfo.unl.edu
Commission IV, Working Group 1
KEY WORDS: Modelling Remote, Sensing GIS Resource Management Vegetation Ecoregion Mapping
ABSTRACT
Ecoregions are developed to assist in natural resource management and policy making. A quantitative, multivariate
regionalization model was developed and applied on vegetation region mapping of Nebraska, the United States. The
model aggregated small ecosystems into larger regions in a hierarchical clustering procedure. Ecosystem elements were
merged into clusters based on the similarities of their ecological features, and their spatial neighborhood derived from
GIS topological files. Vegetation regions of Nebraska were generated using digital State Soil Geographical data and
multitemporal NOAA/AVHRR NDVI data of the growing season in 1991.
INTRODUCTION
Ecoregions are geographical zones that contain a number
of similarly functioning ecosytems. They may represent
broad similarities in ecosystem components including
climate, geology, geomorphology, soils, and vegetation
(Bailey et al, 1985; Wiken, 1986), or they may be
designed to address more specific themes, such as
vegetation types, soils, or water quality. Ecoregion
frameworks are developed to assist in natural resource
and environment management and policy making. In the
United States, several ecoregion schemes have been
developed. Kuchler (1970) mapped potential natural
vegetation of the Unite States. The Land Resource
Regions and Major Land Resource Areas (MLRA) were
developed by the U.S. Department of Agriculture (USDA)
to assist agricultural management (USDA, 1981). Other
major frameworks are Ecoregions of the United States by
the USDA Forest Service, and Ecoregion Maps compiled
by the U.S. Environmental Protection Agency (Gallant et
al, 1989). Ecoregions provide a framework in which
similar responses may be expected within relatively
homogeneous areas. Therefore, it is possible to formulate
management policy and apply it on a regionwide basis
rather than a site-by-site basis (Bailey et al, 1985).
Most previous ecological regionalizations have been
completed by a qualitative approach which employs
continual, interactive expert judgements for selecting,
analyzing, and classifying data in order to generate regions
(Gallant et al, 1989). Quantitative tools are not sufficiently
developed for incorporating the multivariate judgements
needed to delineate regions. The objectives of this
research were to develop a quantitative, multivariate
regionalization model and apply it onto satellite imagery
for vegetation zoning in Nebraska of the United States.
1001
The model was developed to aggregate small ecosystems
into large ecoregions based on similarity of biotic and
abiotic features. The mergers of ecosystems can be
conceptualized by using a hierarchical dendrogram. In
this research, State Soil Geographic (STATSGO) data map
units were defined as the elementary ecosystems. Bi-
weekly composites of Normalized Difference Vegetation
Index (NDVI) derived from NOAA/AVHRR were used as
surrogates of vegetation conditions.
STUDY AREA AND DATA SOURCES
The state of Nebraska lies between 40° and 43° north
latitude, and between 95.5° and 104° west longitude
(Figure 1). Nebraska is part of the broad region which
gently slopes up from the Mississippi River in the east to
the Rocky Mountains in the west. The sedimentary rocks
of this area are of several types, including limestone,
sandstone, and shale. Located in the interior of North
America, Nebraska has a continental climate with a
considerable temperature range from summer to winter.
The total growing season precipitation is generally
adequate for crop production (Searcy and Longwell, 1964).
Nebraska is primarily a grassland area with some forests
and woodlands distributed along river valleys throughout
the state. Most of its land has been cultivated for
agricultural use.
NOAA satellites provide daily Advanced Very High
Resolution Radiometer (AVHRR) data at a ground
resolution of 1x1 km. The coarse resolution and high
repeat frequency of AVHRR data facilitate large area study
and environmental monitoring. In vegetation mapping, it
is possible to create phenological profiles from
multitemporal AVHRR data to discriminate vegetation
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B4. Vienna 1996