apping and analyzing change of impervious surface for two decades using ulti-temporal Landsat imagery in Missouri

Abstract Human population growth and associated sprawl has rapidly converted open lands to developed use and affected their distinctive ecological characteristics. Missouri reflects a full range of sprawl characteristics that include large metropolitan centers, which led growth in 1980s, and smaller metropolitan and rural areas, which led growth in 1990s. In order to study the historical patterns of sprawl, there is a need to quantitatively and geographically depict the extent and density of impervious surface for three time periods of 1980, 1990, and 2000 for the entire state of Missouri. We mapped impervious surface using Sub-pixel Classifier™, an add-on module of Erdas Imagine for the three time periods, where impervious surface growth was derived as the subtraction of impervious surface mapped from the different time periods. Accuracy assessment was performed by comparing satellite derived impervious surface images with ground-truth acquired from high resolution air photos. Results show that during 1980–2000, 129,853 ha of land were converted to impervious surface. Sprawl was prominent on urban fringe (within the urban boundaries) during 1980s with 23,674 ha of land converted to impervious surface compared to 22,918 ha in 1990s. There was a temporal shift in the rural landscapes (outside the urban boundaries) in the 1990s with 48,079 ha of land converted to impervious surface compared to 35,180 ha in 1980s. Major findings based on analysis of the impervious surface growth include: (i) new growth of impervious surfaces are concentrated on areas with 0.5–1.0% road cover; (ii) most new growths are either inside or close to urban watersheds; and (iii) most new growths are either inside or close to counties with metropolitan cities. This research goes beyond the usual hot spots of metropolitan areas to include rural landscapes where negative impact was exerted to the ecosystem due to the low density development and larger affected areas.

[1]  Volker C. Radeloff,et al.  Characterizing dynamic spatial and temporal residential density patterns from 1940-1990 across the North Central United States , 2004 .

[2]  R. O’Connor,et al.  Residential expansion as a continental threat to U.S. coastal ecosystems , 2000 .

[3]  M. Ridd Exploring a V-I-S (vegetation-impervious surface-soil) model for urban ecosystem analysis through remote sensing: comparative anatomy for cities , 1995 .

[4]  K. Clarke,et al.  Impact of Urban Sprawl on Water Quality in Eastern Massachusetts, USA , 2007, Environmental management.

[5]  Limin Yang,et al.  Development of a 2001 National land-cover database for the United States , 2004 .

[6]  R. Cervero Road Expansion, Urban Growth, and Induced Travel: A Path Analysis , 2001 .

[7]  Susan L Handy,et al.  Smart Growth and the Transportation-Land Use Connection: What Does the Research Tell Us? , 2005 .

[8]  David Salt,et al.  Resilience Thinking : Sustaining Ecosystems and People in a Changing World , 2017 .

[9]  Peter A. Rogerson,et al.  The Geographical Analysis of Population: With Applications to Planning and Business , 1994 .

[10]  Daniel L. Civco,et al.  CHARACTERIZATION OF SUBURBAN SPRAWL AND FOREST FRAGMENTATION THROUGH REMOTE SENSING APPLICATIONS , 2000 .

[11]  D. Lu,et al.  Use of impervious surface in urban land-use classification , 2006 .

[12]  R. Heimlich,et al.  Development at the Urban Fringe and Beyond: Impacts on Agriculture and Rural Land , 2012 .

[13]  J. Wickham,et al.  Thematic accuracy of the 1992 National Land-Cover Data for the eastern United States: Statistical methodology and regional results , 2003 .

[14]  Limin Yang,et al.  COMPLETION OF THE 1990S NATIONAL LAND COVER DATA SET FOR THE CONTERMINOUS UNITED STATES FROM LANDSAT THEMATIC MAPPER DATA AND ANCILLARY DATA SOURCES , 2001 .

[15]  Toby N. Carlson,et al.  The impact of land use — land cover changes due to urbanization on surface microclimate and hydrology: a satellite perspective , 2000 .

[16]  Chengquan Huang,et al.  Development of A circa 2000 Landcover DatabaseFor The United States , 2002 .

[17]  Paul A. Longley,et al.  Data-rich models of the urban environment: RS, GIS and 'lifestyles' , 2001 .

[18]  Elizabeth Brabec,et al.  Impervious Surfaces and Water Quality: A Review of Current Literature and Its Implications for Watershed Planning , 2002 .

[19]  Jerry Anthony,et al.  Do State Growth Management Regulations Reduce Sprawl? , 2004 .

[20]  David M. Theobald,et al.  Land‐Use Dynamics Beyond the American Urban Fringe* , 2001 .

[21]  Qihao Weng,et al.  Landscape as a continuum: an examination of the urban landscape structures and dynamics of Indianapolis City, 1991–2000, by using satellite images , 2009 .

[22]  G. Fuguitt The nonmetropolitan population turnaround. , 1985, Annual review of sociology.

[23]  Alan T. Murray,et al.  Monitoring Growth in Rapidly Urbanizing Areas Using Remotely Sensed Data , 2000 .

[24]  M. Reisner Cadillac Desert: The American West and Its Disappearing Water , 1987 .

[25]  T. Esch,et al.  Large-area assessment of impervious surface based on integrated analysis of single-date Landsat-7 images and geospatial vector data , 2009 .

[26]  J. Brueckner Urban Sprawl: Diagnosis and Remedies , 2000 .

[27]  R. Peiser Decomposing urban sprawl , 2001 .

[28]  Alan T. Murray,et al.  Estimating impervious surface distribution by spectral mixture analysis , 2003 .

[29]  G. Foody Assessing the accuracy of land cover change with imperfect ground reference data , 2010 .

[30]  G. Daily,et al.  Effects of household dynamics on resource consumption and biodiversity , 2003, Nature.

[31]  John I. Carruthers,et al.  Growth at the fringe: The influence of political fragmentation in United States metropolitan areas , 2003 .

[32]  Volker C. Radeloff,et al.  Rural and Suburban Sprawl in the U.S. Midwest from 1940 to 2000 and Its Relation to Forest Fragmentation , 2005 .

[33]  Paul C. Sutton,et al.  A scale-adjusted measure of Urban sprawl using nighttime satellite imagery , 2003 .

[34]  R. Freilich Smart Growth in Western Metro Areas , 2003 .

[35]  Michael A. Wulder,et al.  An accuracy assessment framework for large‐area land cover classification products derived from medium‐resolution satellite data , 2006 .

[36]  M. McKinney,et al.  Urbanization, Biodiversity, and Conservation , 2002 .

[37]  Michael J. Choate,et al.  Effects of Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper plus radiometric and geometric calibrations and corrections on landscape characterization , 2001 .

[38]  Kenneth M. Johnson,et al.  Continuity and Change in Rural Migration Patterns, 1950–1995* , 2009 .

[39]  Limin Yang,et al.  An approach for mapping large-area impervious surfaces: synergistic use of Landsat-7 ETM+ and high spatial resolution imagery , 2003 .

[40]  A. Yeh,et al.  Measurement and monitoring of urban sprawl in a rapidly growing region using entropy , 2001 .

[41]  M. Alberti Advances in Urban Ecology: Integrating Humans and Ecological Processes in Urban Ecosystems , 2008 .

[42]  Karen Payne,et al.  Techniques for Mapping Suburban Sprawl , 2002 .

[43]  Qinhuo Liu,et al.  Monitoring urban expansion with remote sensing in China , 2001 .

[44]  M. Turner,et al.  Explaining Human Settlement Patterns in a Recreational Lake District: Vilas County, Wisconsin, USA , 2002, Environmental management.

[45]  Xiaojun Yang,et al.  Drivers of Land-Use/Land-Cover Changes and Dynamic Modeling for the Atlanta, Georgia Metropolitan Area , 2002 .

[46]  W. B. Clapham Continuum-based classification of remotely sensed imagery to describe urban sprawl on a watershed scale , 2003 .

[47]  C. Arnold,et al.  IMPERVIOUS SURFACE COVERAGE: THE EMERGENCE OF A KEY ENVIRONMENTAL INDICATOR , 1996 .

[48]  Pavlos S. Kanaroglou,et al.  Smart growth strategies, transportation and urban sprawl: simulated futures for Hamilton, Ontario , 2008 .

[49]  Peter A. Bednekoff,et al.  Model Based Inference in the Life Sciences: A Primer on Evidence David R. Anderson Model Based Inference in the L , 2009, Animal Behaviour.

[50]  P. Berke,et al.  Greening Development to Protect Watersheds: Does New Urbanism Make a Difference? , 2003 .

[51]  Russell G. Congalton,et al.  A review of assessing the accuracy of classifications of remotely sensed data , 1991 .

[52]  D. Civco,et al.  IMPERVIOUS SURFACE MAPPING FOR THE STATE OF CONNECTICUT 1 , 1997 .

[53]  Kenneth M. Johnson,et al.  Nonmetro Recreation Counties: Their Identification and Rapid Growth , 2003 .

[54]  D. Lu,et al.  Residential population estimation using a remote sensing derived impervious surface approach , 2006 .

[55]  C. Homer,et al.  Monitoring urban land cover change by updating the National Land Cover Database impervious surface products , 2009, 2009 Joint Urban Remote Sensing Event.

[56]  M. Bauer,et al.  Estimating and Mapping Impervious Surface Area by Regression Analysis of Landsat Imagery , 2007 .

[57]  Scott L. Powell,et al.  Quantification of impervious surface in the Snohomish Water Resources Inventory Area of Western Washington from 1972–2006 , 2007 .

[58]  John R. Jensen,et al.  Introductory Digital Image Processing: A Remote Sensing Perspective , 1986 .

[59]  Carl W. Condit,et al.  Nature's Metropolis: Chicago and the Great West , 1991 .

[60]  Shupeng Chen,et al.  Remote sensing and GIS for urban growth analysis in China , 2000 .

[61]  R. L. Knight,et al.  Ranching the View: Subdivisions versus Agriculture , 1995 .

[62]  Andrea Wright Parmenter,et al.  Ecological Causes and Consequences of Demographic Change in the New West , 2002 .