Deriving current land-use information for metropolitan transportation planning through integration of remotely sensed data and GIS

lkansportation planners and metropolitan planning organizations require up-to-date land-use information to allocate transportation resources and to forecast the location and type of growth within metropolitan areas and associated increases in transportation volumes. For rapidly changing areas, extant geographic databases may not contain current land-use information. Other layers in the GIS database have potential for aiding image-based procedures for updating land-use layers. Results from the first of two case studies suggest that land-use change detection using high spatid resolution imagery is useful for detecting individual change features, but that automatic delineation of these features yields imprecise boundaries, such that interactive delineation is likely to be required. Results from the second case study indicate that many GIs data layers maintained by metropolitan planning organizations provide useful information for

[1]  David J. Cowen,et al.  Improved urban infrastructure mapping and forecasting for BellSouth using remote sensing and GIS technlogy , 1994 .

[2]  A-Xing Zhu,et al.  Measuring Uncertainty in Class Assignment for Natural Resource Maps under Fuzzy Logic , 1997 .

[3]  James E. Moore,et al.  Future directions for EGIS: applications to land use and transportation planning , 1989 .

[4]  R. Welch,et al.  Spatial resolution requirements for urban studies , 1982 .

[5]  Philip J. Howarth,et al.  Landsat digital enhancements for change detection in urban environments , 1983 .

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

[7]  Peter R. Stopher,et al.  SMART: simulation model for activities, resources and travel , 1996 .

[8]  W. Malila Change Vector Analysis: An Approach for Detecting Forest Changes with Landsat , 1980 .

[9]  Neil Wrigley,et al.  Categorical Data Analysis for Geographers and Environmental Scientists , 1985 .

[10]  Fangju Wang,et al.  A knowledge-based vision system for detecting land changes at urban fringes , 1993, IEEE Trans. Geosci. Remote. Sens..

[11]  R T Newkirk,et al.  A Common Knowledge Database for Remote Sensing and Geographic Information in a Change-Detection Expert System , 1990 .

[12]  Douglas A. Stow,et al.  Category identification of changed land-use polygons in an integrated image processing/geographic information system , 1992 .

[13]  L. Janssen,et al.  Implementation of temporal relationships in knowledge based classification of satellite images. , 1991 .

[14]  A. Strahler,et al.  Artificial neural network response to mixed pixels in coarse-resolution satellite data , 1996 .

[15]  D. Toll,et al.  Detecting residential land use development at the urban fringe , 1982 .

[16]  Philip J. Howarth,et al.  Procedures for change detection using Landsat digital data , 1981 .