Monitoring and Modeling Cropland Loss in Rapidly Growing Urban and Depopulating Rural Counties Using Remotely Sensed Data and GIS

References

• Amissah-Arthur , A. , Mougenot , B. and Loireau , M. 2000 . Assessing farmland dynamics and land degradation on Sahelian landscapes using remotely sensed and socioeconomic data . International Journal of Geographical Information Science , 14 ( 6 ) : 583 – 599 .
   Web of Science ®Google Scholar
• Anderson , J. R. , Hardy , E. E. , Roach , J. T. and Witmer , R. E. 1976 . A land use and land cover classification scheme for use with remote sensor data U.S. Geological Survey Professional Paper 964
   Google Scholar
• Banai , R. 1993 . Fuzziness and Geographical Information Systems: Contributions from the analytic hierarchy process . International Journal of Geographical Information Systems , 7 : 315 – 329 .
   Web of Science ®Google Scholar
• Batty , M. and Xie , Y. 1997 . Possible urban automata . Environment and Planning B: Planning and Design , 24 : 175 – 192 .
   Web of Science ®Google Scholar
• Berry , M. W. , Flamm , R. O. , Hazen , B. C. and MacIntyre , R. L. 1996 . The Land‐Use Change and Analysis System (LUCAS) for Evaluating Landscape Management Decisions . IEEE Computational Science and Engineering , 3 ( 1 ) : 24 – 35 .
   Web of Science ®Google Scholar
• Census Bureau . 2003 . State and county quick facts , United States Census Bureau . http://quickfacts.census.gov/qfd/states/19000.html
   Google Scholar
• Civco , D. L. , Prisole , M. P. , Hurd , J. D. , Wilson , E. H. and Arnold , C. L. 2002 . Quantifying and describing urbanized landscapes in the northeast United States . Photogrammetric Engineering and Remote Sensing , 68 ( 10 ) : 1083 – 1090 .
   Web of Science ®Google Scholar
• 2004 . The Changing Midwest Assessment , St. Paul, MN : North Central Research Station, USDA Forest Service . http://www.ncrs.fs. fed.us/4153/deltawest/
   Google Scholar
• Clarke , K. C. , Hoppen , S. and Gaydos , L. J. Methods and techniques for rigorous calibration of a cellular automaton model of urban growth . Proceedings, Third International Conference/Workshop on Integrating GIS and Environmental Modeling . January 21-26 1996 , Santa Fe, NM. Santa Barbara, CA : National Center for Geographic Information and Analysis . CD‐ROM, http://www.ncgia.ucsb.edu/conf/SANTA_FE_CD-ROM/main.html, access: May 1999
   Google Scholar
• Clarke , K. S. , Gaydos , L. J. and Hoppen , S. 1997 . A self‐modifying cellular automation model of historical urbanization in the San Francisco Bay area . Environment and Planning B: Planning and Design , 24 : 247 – 261 .
   Web of Science ®Google Scholar
• Cosner , S. 2001 . Preserving Iowa's Farmland: Why is it important? How can it be done? Retrieved March 2004 from http://www.extension.iastate.edu/Publications/PM1868B.pdf
   Google Scholar
• Dai , X. and Khorram , S. Quantification of the impact of misregistration on the accuracy of remotely sensed changed detection . Proceedings of the IEEE Geosciences and Remote Sensing Symposium . pp. 1763 – 1765 . Texas : IEEE .
   Google Scholar
• Egbert , S. L. , Nellis , M. D. , Lee , R. -Y. , Price , K. P. and Boyce , R. 1998 . Mapping Conservation Reserve Program (CRP) grasslands using multi‐seasonal thematic mapper imagery . Geocarto International , 13 ( 4 ) : 17 – 24 .
   Google Scholar
• 1999 . ERDAS Field Guide , Atlanta, Georgia : ERDAS Inc. .
   Google Scholar
• Giglierano , J. D and Rau , S. 1993 . Iowa land cover map 1975-1984 , Iowa Department of Natural Recourses . Retrieved November 2003, http://www.igsb.uiowa.edu/nrgis/enviro.idc
   Google Scholar
• Guerschman , J. P. , Pacin , F. , Paruelo , J. M. , Di Bella , C. and Giallorenzi , M. C. 2003 . Land cover classification in the Argentine Pampas using multi‐temporal Landsat TM data . International Journal of Remote Sensing , 24 ( 17 ) : 3381 – 3402 .
   Web of Science ®Google Scholar
• Guo , X. , Price , K. P. and Stiles , J. 2003 . Grasslands Discriminant Analysis Using Landsat TM Single and Multitemporal Data . Photogrammetric Engineering and Remote Sensing , 69 ( 11 ) : 1255 – 1262 .
   Web of Science ®Google Scholar
• The Iowa State University Extension . 2004 . Crop and land use tables and charts Retrieved May 2004 from http://extension.agron.iastate.edu/soils/tables_charts.html
   Google Scholar
• Jenerette , G. D. and Wu , J. 2001 . Analysis and simulation of and use change in the central Arizona‐Phoenix region, USA . Landscape Ecology , 16 : 611 – 626 .
   Web of Science ®Google Scholar
• Klosterman , R. E. 1999 . The What if? Collaborative planning support system . Environment and Planning B: Planning and Design , 26 : 393 – 408 .
   Web of Science ®Google Scholar
• Landis , J. and Zhang , M. 1998 . The second generation of the California urban futures model: Part 1: Model logic and theory . Environment and Planning B , 30 : 657 – 666 .
   Google Scholar
• Li , H. and Reynolds , J. F. 1997 . “ Modeling effects of spatial pattern, drought, and grazing on rates of rangeland degradation: A combined Markov and cellular automaton approach ” . In Scale in Remote Sensing and GIS , Edited by: Quattrochi , D. A. and Goodchild , M. F. 211 – 30 . New York : Lewis Publishers .
   Google Scholar
• Li , X. and Yeh , A. G. 2000 . Modelling sustainable urban development by the integration of constrained cellular automata and GIS . International Journal of Geographical Information Science , 14 : 131 – 152 .
   Web of Science ®Google Scholar
• LUCC . 1999 . “ Land use and land cover: Implementation strategy ” . In IGBP Report 48, IHDP Report 10 , Stockholm : IGBP Secretariat .
   Google Scholar
• National Resources Inventory . 1982 . Instructions for Collecting Sample Data , USDA . Revised May 1980
   Google Scholar
• Parker , D. C. , Manson , S. M. , Janssen , M. A. , Hoffmann , M. J. and Deadman , P. 2003 . Multi‐Agent Systems for the Simulation of Land‐Use and Land‐Cover Change: A Review . Annals of the Association of American Geographers , 93 ( 2 ) : 314 – 337 .
   Web of Science ®Google Scholar
• Pijankowski , B. , Long , D. , Gage , S. and Cooper , W. A Land transformation model: conceptual elements spatial object class hierarchy, GIS command syntax and an application for Michigan's Saginaw Bay watershed . Land Use Modeling Workshop . June 5-6 1997 . Sioux Falls, SD Retrieved April 2004 from http://www.ncgia.ucsb.edu/conf/landuse97
   Google Scholar
• Platt , R. H. 1981 . Farmland conversion: national lesson for Iowa . Professional Geographer , 33 ( 1 ) : 247 – 261 .
   Web of Science ®Google Scholar
• Pontius , R. G. 2000 . Quantification error versus location error in comparison of categorical maps . Photogrammetric Engineering and Remote Sensing , 66 ( 8 ) : 1011 – 1016 .
   Web of Science ®Google Scholar
• Price , K. P. , Egbert , S L. , Nellis , M. D. , Lee , R. and Boyce , R. 1997 . Developing a land cover modeling protocol for the high plains using multi‐seasonal thematic imagery . Transactions of the Kansas Academy of Science , 100 : 21 – 33 .
   Google Scholar
• Sand , D. 2001 . The farm bill's effect on Iowa's landscape , Iowa natural Heritage Foundation . Accessed March 2004 http://www.inhf.org/farmbillmap.htm#grasslands%20lostAmerican
   Google Scholar
• Shabazian , D. and Johnston , R. 2000 . UPLAN ‐ Urban Growth Model , UC Davis, Information Center for the Environment . retrieved April, 2004 from http://snepmaps.des.ucdavis.edu/uplan/
   Google Scholar
• Sugumaran , R. , Zerr , D. and Prato , T. 2002 . Multi‐temporal IKNONS images for local government planning and management . Canadian Journal of Remote Sensing , 28 ( 1 ) : 90 – 95 .
   Web of Science ®Google Scholar
• Torrens , P. M. and O'Sullivan , D. 2001 . Editorial: Cellular automata and urban simulation: where we go from here? . Environment and Planning B , 28 : 163 – 168 .
   Web of Science ®Google Scholar
• USDA . 2003 . “ Iowa Agricultural Statistics ” . In National Agricultural Statistics Service , United States Department of Agriculture . retrieved December 2003 from http://www.nass.usda.gov/ia/
   Google Scholar
• Verbyla , D. L. and Boles , S. H. 2000 . Bias in land cover change estimates due to misregistration . International Journal of Remote Sensing , 21 ( 18 ) : 3553 – 3560 .
   Web of Science ®Google Scholar
• Waddell , P. UrbSim ‐ The Oregon Prototype Metropolitan Land Use Model . Proceedings of the ASCE Conference Transportation, Land Use, and Air Quality: Making the Connection . May 1998 , Portland, Oregon. Retrieved April 2004 from http://www.urbansim.org/Papers/UrbanSim-JAPA.pdf
   Google Scholar
• Ward , D. , Phinn , R. and Murray , T. 2000 . Monitoring growth in rapidly urbanizing areas using remotely sensed data . Professional Geographer , 52 ( 3 ) : 371 – 386 .
   Web of Science ®Google Scholar
• Wilson , E. H. , Arnold , C. , Hurd , J. D. , Civco , D. L. and Prisloe , M. P. 2003 . Development of a geospatial model to quantify, describe and map urban growth . Remote Sensing of Environment , 86 ( 3 ) : 275 – 285 .
   Web of Science ®Google Scholar
• Yang , X. and Lo , C. P. 2003 . Modelling urban growth and landscape changes in the Atlanta metropolitan area . International Journal of Geographical Information Science , 17 ( 5 ) : 463 – 488 .
   Web of Science ®Google Scholar