Land-cover change and environmental impact analysis in the Greater
Mankato area of Minnesota using remote sensing and GIS modelling
F. YUAN*
Department of Geography, Minnesota State University—Mankato, Mankato, MN
56001, USA
(Received 31 December 2006; in final form 16 February 2007 )
Land use and land-cover (LULC) data provide essential information for
environmental management and planning. This research evaluates the land-
cover change dynamics and their effects for the Greater Mankato Area of
Minnesota using image classification and Geographic Information Systems (GIS)
modelling in high-resolution aerial photography and QuickBird imagery. Results
show that from 1971 to 2003, urban impervious surfaces increased from 18.3% to
32.6%, while cropland and grassland decreased from 54.2% to 39.1%. The
dramatic urbanization caused evident environmental impacts in terms of runoff
and water quality, whereas the annual air pollution removal rate and carbon
storage/sequestration remained consistent since urban forests were steady over
the 32-year span. The results also indicate that highly accurate land-cover
features can be extracted effectively from high-resolution imagery by incorporat-
ing both spectral and spatial information, applying an image-fusion technique,
and utilizing the hierarchical machine-learning Feature Analyst classifier. This
research fills the high-resolution LULC data gap for the Greater Mankato Area.
The findings of the study also provide valuable inputs for local decision-makers
and urban planners.
1. Introduction
Land-use and land-cover changes (LULCC) have great effects for the environmental
and socio-economic sustainability of communities. When one type of use replaces
another, the effects tend to be superimposed and cumulative. During the process of
urbanization, when rural areas are converted to urban land uses, hydrological circle
and rates of soil erosion will change accordingly (Tong and Chen 2002). Meanwhile,
when agricultural land is decreasing, the dependence on the use of fertilizers and
pesticides to increase the productivity is rising. As a consequence, unused nutrients,
mainly nitrogen and phosphorus, near the soil surface could be transported by
surface runoff to water bodies, thereby degrading water quality by causing
eutrophication (Tilman et al. 2001). The amount of urban impervious surfaces
has emerged as an important indicator of environmental quality (Arnold and
Gibbons 1996). It influences the non-point source pollution and water quality by
directly affecting the amount of runoff to water bodies (Dougherty et al. 2004). In
addition, because of the heat-storage capacities of urban impervious surfaces, as well
as waste heat from transportation and industry, the temperatures are usually higher
*Email: fei.yuan@mnsu.edu
International Journal of Remote Sensing
Vol. 29, No. 4, 20 February 2008, 1169–1184
International Journal of Remote Sensing
ISSN 0143-1161 print/ISSN 1366-5901 online # 2008 Taylor & Francis
http://www.tandf.co.uk/journals
DOI: 10.1080/01431160701294703

in the city (Oke 1976, Eliasson 1992, Weng 2001a). As a result, the higher
temperatures in urban areas increase air conditioning demands and affect local
climate by affecting the energy balance and thus modifying precipitation patterns
(Carlson and Arthur 2000). Moreover, urbanization leads to habitat fragmentation
and irreversible resource loss (Collinge 1996, Nikolakaki 2004). The expanding city
is a remarkable producer of wastes and causes large problems of environmental
pollution as well.
An integrated remote sensing and Geographical Information Systems (GIS)
modelling method has become a trend for environmental assessment and manage-
ment for its capabilities of managing and manipulating large amounts spatial data to
satisfy planner and policymaker’s growing needs of accurate LULCC information.
For instance, Weng (2001a) evaluated the impacts of urban expansion on surface
temperature and surface runoff (Weng 2001b) in the Zhujiang Delta of South China
using the integrated method. Findings from these studies indicated that urban
development had raised the surface radiant temperature by 13 K in the urbanized
area and had increased the annual runoff depth by 8.1 mm during the 1989–1997
periods. Tong and Chen (2002) modelled the relationship between land use and
surface water quality in the State of Ohio. Their study revealed that there was a
significant relationship between land use and in-stream water quality, especially for
nitrogen, phosphorus, and faecal coliforms. In particular, agricultural and
impervious urban lands produced a much higher level of nitrogen and phosphorus
than other land surfaces. Arthur et al. (2003) performed satellite and ground-based
microclimate and hydrologic analyses coupled with a regional urban growth model
in south-eastern Pennsylvania. Gillies et al. (2003) derived the impervious surface
area (ISA) from 1979 to 1997 for the Line Creek Watershed located to the south of
the city of Atlanta, GA, and reported evident mussel habitat degradation and loss of
species in areas where ISA expansion was observed. Milesi et al. (2003) reported that
an increase in urban development for the south-eastern United States of 1.9% during
the 1992–2000 period reduced the annual net primary production (NPP) of the
south-eastern United States by 0.4%. Claggett et al. (2004) assessed development
pressure in the Baltimore–Washington, DC region using a cellular automata model
and a supply/demand allocation model. Carlson (2004) analysed and predicted
surface runoff by simple runoff calculations and an urban growth model for Spring
Creek Watershed in Central Pennsylvania. Weng and Yang (2006) analysed the
relationship between the local air pollution pattern and urban land use for
Guangzhou in China. They reported that the spatial patterns of air pollutants were
positively correlated with urban built-up density and land surface temperature. Ode
and Fry (2006) assessed urban pressure on woodland for the Malmo´´-Lund region in
Sweden using a GIS-based model.
The findings of earlier studies on environmental impacts of LULCC have been
conducted mainly at regional scales in 30-m Landsat or coarser spatial resolution
imagery, which offer possibilities for monitoring LULCC and their effects in a
synoptic view. However, for local land use and urban planning purposes, the 30-m
resolution is not enough. According to Antrop (2004), only sub-5-m resolution may
provide satisfactory results in a highly heterogeneous urban environment. The
recent availability of high-resolution satellite remote-sensing images coupling with
historical aerial photography offers an improved opportunity to monitor environ-
ment at local scales. Moreover, due to the increasing sizes of datasets obtained by
modern remote sensing, accurate LULC extraction in a highly automated fashion
1170 F. Yuan