AN ASSESSMENT OF SOIL PRODUCTIVITY LOSS DUE TO URBANIZATION IN
PENNSYLVANIA, U.S.
Egide Nizcyimana and G.W. Petersen
The Pennsylvania State University. University Park. PA. U.S.
M.L. Imhoff. NASA-Goddard Space Flight Center. Greenbelt. MD, U.S.
W.T. Lawrence. Bowie State University. Bowie. MD. U.S.
Commission VII. Working Group 5
KEY WORDS: remote sensing: GIS: soil productivity class: urban land usc; soil databases.
ABSTRACT:
This work compares two sources of urban land use and two soil productivity modeling schemes in their ability to
provide the magnitude and distribution of soil productivity losses under urbanization in the state of Pennsylvania. U.S.
The location and extent of urbanization was determined by generating urban land use class GIS layers from Landsat
Thematic Mapper (TM) and the U.S. Air Force Defense Meteorological Satellite Program's Operational Linescan
System (DMSP/OLS) nighttime imagery. The level of soil productivity was determined using results of the Soil
Ratings for Plant Growth (SRPG) model and The United States Department of Agriculture-Natural Resources
Conservation Service's (USDA-NRCS) Land Capability Classification (LCC) groupings from the Pennsylvania State
Soil Gcographic (STATSGO) databasc. The magnitude of soil productivity loss duc to urbanization was obtained by
analysis of data resulting from GIS overlays of various combination of urban land usc and soil productivity class
layers. Results indicated that despite its coarse ground resolution (2600 m), the DMSP/OLS compared well with
Landsat TM (30 m resolution) in providing the distribution of urban land usc in Pennsylvania. The LCC system was
not as good as the SRPG soil productivity rating model in grouping soils into meaningful productivity classes. Urban
land use covered less than 5% of the land in Pennsylvania. However. the most productive soils were also the most
urbanized with more than half of the urban land usc in the state occurring on the most productive soils. This kind of
data is uscful for decision-makers in state and regional agencies because it provides a basis for developing sound
management and/or land usc plans.
1. INTRODUCTION large cities. Pittsburgh and Philadelphia. and many
medium and small sizcd citics and towns.
Concern about the impact of expanding urbanızation ın
the U.S. on the land's capacity to producc food. fucl
and fiber has increased in recent years. As more land
is converted to urban uses. the question arises as to
whether or not we are systematically reducing our
ability to produce food bv placing our housing and
infrastructure on the most productive soils.
2. MATERIALS AND METHODOLOGY
Sources of the urban land use class were the U.S. Air
Force Defense Meteorological Satellite Program's
Preliminary analyses using thc DMSP/OLS nighttime
imagery and the Food and Agricultural Organization's
(FAO) Fertility Capability Classification (FCC)
indicated that the best agricultural soils were the most
urbanized and some unique soils were on the verge of
disappearing (Imhoff et al. 1996). This study
compares two remote sensing sources of urban land usc
distributions (Landsat TM versus DMSP/OLS imagery)
and two soil productivity classification schemes (SRPG
versus LCC) in an effort to determine the distribution
of soil productivity losscs because of urbanization in
the state of Pennsylvania. U.S. Pennsylvania has two
Operational Linescan System (DMSP/OLS)
nighttime imagery and the Multi-Resolution Land
Characteristic (MRLC) data for the state of
Pennsylvania. The DMSP/OLS imagery is acquired
at a spatial resolution of 2600 m. Although the
primary mission of the OLS is the acquisition of day
and nighttime cloud cover. its nighttime capability
made possible by a high resolution photometer.
makes the sensor ideal for acquiring images of light
sources on the Earth's surface. Preliminary studies of
spatiallv-processed DMSP/OLS data have given
population estimates comparable to those of
traditional census methods for the conterminous U.S.
460 International Archives of Photogrammetry and Remote Sensing. Vol. XXXII, Part 7, Budapest, 1998
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