Publication Cover
Canadian Journal of Remote Sensing
Journal canadien de télédétection
Volume 36, 2010 - Issue 6
143
Views
6
CrossRef citations to date
0
Altmetric
Research Article

Parcel-based classification of agricultural crops via multitemporal Landsat imagery for monitoring habitat availability of western burrowing owls in the Imperial Valley agro-ecosystem

&
Pages 750-762 | Received 13 Mar 2010, Accepted 15 Jan 2011, Published online: 02 Jun 2014

References

  • Akbari, M., Mamanpoush, A., Gieske, A., Miranzadeh, M., Torabi, M. and Salemi, R. 2006. Crop and landcover classification in Iran using Landsat 7 imagery. International Journal of remote Sensing, Vol. 27, No. 19, pp. 4117–4135. doi:10.1080/01431160600784192.
  • Bailey, R.G. 1994. Ecological classification for the United States. USDA Forest Service, Washington DC.
  • Bauer, M.E. 1985. Spectral inputs to crop identification and condition assessment. Proceedings of the IEEE, Vol. 73, No. 1–2, pp. 1071–1085.
  • Beck, R. and Gessler, P.E. 2008. Development of a Landsat time-series for the inland northwest and an application in forest status assessment. Western Journal of Applied Forestry, Vol. 23, No. 1, pp. 53–60.
  • Belward, A.S. and de Hoyos, A. 1987. A comparison of supervised maximum likelihood and decision tree classification for crop cover estimation from multitemporal LANDSAT MSS data. International Journal of Remote Sensing, Vol. 8, No. 1, pp. 229–235. doi:10.1080/01431168708948636.
  • Benz, U.C., Hofmann, P., Willhauck, G., Lingenfelder, I. and Heynen, M. 2004. Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information. ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 58, No. 3–4, pp. 239–258. doi:10.1016/j.isprsjprs.2003.10.002.
  • Blaschke, T. 2010. Object based image analysis for remote sensing. ISPRS International Journal of Photogrammetry and Remote Sensing, Vol. 65, No. 1, pp. 2–16.
  • Breiman, L. 2001. Random Forests. Machine Learning, Vol. 45, No. 1, pp. 5–32.
  • Burnett, C. and Blaschke, T. 2003. A multi-scale segmentation/object relationship modelling methodology for landscape analysis. Ecological Modelling, Vol. 168, No. 1, pp. 233–249. doi:10.1016/S0304-3800(03)00139-X.
  • Carlson, C.A. 1985. Wildlife and agriculture: can they coexist? Journal of Soil and Water Conservation, Vol. 40, No. 3, pp. 263–266.
  • CDFA. 2010. California Agricultural Production Statistics 2009–2010. California Department of Food and Agriculture. Available from http://www.cdfa.ca.gov/statistics/ [accessed 23 November 2010].
  • Chander, G. and Markham, B. 2003. Revised Landsat-5 TM radiometric calibration procedure and postcalibration dynamic ranges. IEEE Transaction on Geosciences and Remote Sensing, Vol. 41, No. 11, pp. 2647–2677.
  • Chavez, P.S.Jr. 1996. Image-based atmospheric corrections —Revisited and improved. Photogrammetric Engineering and Remote Sensing, Vol. 62, No. 9, pp. 1025–1036.
  • Cohen, J. 1960. A coefficient of agreement for nominal scales. Educational and Psychological Measures, Vol. 20, No. 1, pp. 37–40. doi:10.1177/001316446002000104.
  • Congalton, R.G. and Green, K. 1999. Assessing the Accuracy of Remotely Sensed Data Lewis Publishers, New York, pp. 1–137.
  • Craig, M.E. 2001. The NASS cropland data layer program. In Proceedings, third international conference on geospatial information in agriculture and forestry, Denver, Colorado, 5–7 November 2001.
  • Cutler, R.D., Edwards, T.C.Jr, Beard, K.H., Cutler, A., Hess, K.T., Gibson, J. and Lawler, J. 2007. Random Forests for classification in ecology. Ecology, Vol. 88, No. 11, pp. 2783–2792.
  • Desante, D.F. and Ruhlen, E.D. 2004. Density and abundance of burrowing owls in the agricultural matrix of the Imperial Valley, California. Studies in Avian Biology, Vol. 27, No. 1, pp. 116–119.
  • Desclee, B., Bogaert, P. and Defourny, P. 2006. Forest change detection by statistical object-based method. Remote Sensing of Environment, Vol. 102, No. 1–2, pp. 1–11. doi:10.1016/j.rse.2006.01.013.
  • Evans, J.S. and Cushman, S.A. 2009. Gradient modeling of conifer species using random forest. Landscape Ecology, Vol. 24, No. 1, pp. 673–683. doi:10.1007/s10980-009-9341-0.
  • Falkowski, M.J., Gessler, P.E., Morgan, P., Hudak, A.T. and Smith, A.M.S. 2005. Characterizing and mapping forest fire fuels using ASTER imagery and gradient modeling. Forest Ecology and Management, Vol. 217, No. 1, pp. 129–146. doi:10.1016/j.foreco.2005.06.013.
  • Falkowski, M.J., Evans, J.S., Martinuzzi, S., Gessler, P.G. and Hudak, A.T. 2009. Characterizing forest succession with lidar data: An evaluation for the inland northwest, USA. Remote Sensing of Environment, Vol. 113, No. 1, pp. 946–956.
  • Fensham, R.J. 2008. Leichhardt's maps: 100 years of change in vegetation structure in inland Queensland. Journal of Biogeography, Vol. 35, No. 1, pp. 141–156.
  • Foody, G.M. 2002. Status of land cover classification accuracy assessment. Remote Sensing of Environment, Vol. 80,, No. 1, pp. 185–201. doi:10.1016/S0034-4257(01)00295-4.
  • Haack, B. 1987. An assessment of Landsat MSS and TM data for urban and near-urban land-cover digital classification Source. Remote Sensing of Environment, Vol. 21, No. 2, pp. 201–213. doi:10.1016/0034-4257(87)90053-8.
  • Haug, E.A., Millsap, B.A. and Martell, M.S. 1993. Burrowing owl (Speotyto cunicularia). In The Birds of North America, No. 611. Edited by Poole, A. and Gill, F.. The Academy of Natural Sciences, Philadelphia, Pennsylvania, USA, and The American Ornithologists' Union, Washington, D.C., USA.
  • Hay, G.J. and Castilla, G. 2008. Geographic object-based image analysis (GEOBIA): A new name for a new discipline. Object-Based Image Analysis, Lecture Notes in Geoinformation and Cartography,  75–89. doi:10.1007/978-3-540-77058-9_4.
  • Janssen, L.L.F. and Middelkoop, H. 1992. Knowledge based crop classification of a Landsat Thematic Mapper image. International Journal of Remote Sensing, Vol. 13, No. 15, pp. 2872–2837.
  • Klute, D.S., Ayers, L.W., Green, M.T., Howe, W.H., Jones, S.L., Shaffer, J.A., Sheffield, S.R. and Zimmerman, T.S. 2003. Status assessment and conservation plan for the western burrowing owl in the United States. U.S. Department of Interior, Fish and Wildlife Service, Washington, D.C., USA, Biological Technical Publication FWS/BTP-R6001-2003.
  • Lawrence, R.L., Wood, S.D. and Sheley, R.L. 2006. Mapping invasive plants using hyperspectral imagery and Breiman Cutler classifications (RandomForest). Remote Sensing of Environment, Vol. 100, No. 1, pp. 356–362. doi:10.1016/j.rse.2005.10.014.
  • Lu, D. and Weng, Q. 2007. A survey of image classification methods and techniques for improving classification performance. International Journal of Remote Sensing, Vol. 28, No. 5, pp. 823–870. doi:10.1080/01431160600746456.
  • Manning, J.A. 2009. Burrowing owl population size in the Imperial Valley, California: survey and sampling methodologies for estimation. Final report to the Imperial Irrigation District, Imperial, California, April 15. Available from https://www.ebidexchange.com/SolicitationDocuments.aspx?cid = 974162d4-8c5f-48ee-8cef-8e7bbac1d9e7&uid = b87808f6-3268-4892-85d0-6d7d434af184&sid = 18886 Attachment C [accessed 10 January 2011]
  • Manning, J.A. 2011. Factors affecting the detection probbility of burrowing owls in southwest agroecosystem environments. Journal of Wildlife Management, In Press.
  • Markham, B.L. and Barker, J.L. 1986. Landsat MSS and TM post-calibration dynamic ranges, exoatmospheric reflectances and at-satellite temperatures. EOSAT Technical Notes, Vol. 1, No. 1, pp. 3–8.
  • Moulton, C.E., Brady, R.S. and Belthoff, J.R. 2006. Association between wildlife and agriculture: underlying mechanisms and implications for burrowing owls. Journal of Wildlife Management, Vol. 70, No. 3, pp. 708–716. doi:10.2193/0022-541X(2006)70[708:ABWAAU]2.0.CO;2.
  • Mueller, R. and Ozga, M. 2002. Creating a cropland data layer for an entire state. Proceedings, 2002 American congress on surveying and mapping/American Society for Photogrammetry and Remote Sensing conference and technology exhibition. Bethesda, MD: American Society for Photogrammetry and Remote Sensing. Available from http://www.nass.usda.gov/Education_and_Outreach/Reseach_Reports/02_01_CreateCDL_State_RWM.pdf [accessed 23 November 2010].
  • Murphy, M., Evans, J.S. and Storfer, A. 2010. Quantifying Bufo boreas connectivity in Yellowstone National Park with landscape genetics. Ecology, 91,, No. 1, pp. 252–261.
  • Oetter, D.R., Cohen, W.B., Berterretche, M., Maiersperger, T.K. and Kennedy, R.E. 2001. Land cover mapping in an agricultural setting using multiseasonal Thematic Mapper data. Remote Sensing of Environment, Vol. 76, No. 1, pp. 139–155. doi:10.1016/S0034-4257(00)00202-9.
  • Ortiz, M.J., Formaggio, A.R. and Epiphanio, J.C.N. 1997. Classification of croplands through integration of remote sensing, GIS, and historical database. International Journal of Remote Sensing, Vol. 18, No. 1, pp. 95–105. doi:10.1080/014311697219295.
  • Peterjohn, B.G. 2003. Agricultural landscapes: can they support healthy bird populations as well as farm products? The Auk, Vol. 120, No. 1, pp. 14–19. doi:10.1642/0004-8038(2003)120[0014:ALCTSH]2.0.CO;2.
  • Pontius , R.G.Jr. 2000. Quantification error versus location error in the comparison of categorical maps. Photogrammetric Engineering and Remote Sensing, Vol. 66, No. 8, pp. 1011–1016.
  • Prasad, A.M., Iverson, L.R. and Liaw , A. 2006. Newer classification and regression tree techniques: bagging and random forests for ecological prediction. Ecosystems, Vol. 9, No. 1, pp. 181–199. doi:10.1007/s10021-005-0054-1.
  • Rosenberg, D.K. and Haley, K.L. 2004. The ecology of burrowing owls in the agroecosystem of the Imperial Valley, California. Studies in Avian Biology, Vol. 27, No. 1, pp. 120–135.
  • Sauer, J.R., Hines, J.E. and Fallon, J. 2008. The North American breeding bird survey, results and analysis 1966–2007. Version 5.15.2008. U.S. Geological Survey Patuxent Wildlife Research Center, Laurel, Maryland, USA., Available from http://www.mbr-pwrc.usgs.gov/bbs/ [accessed 26 April 2010].
  • Smith, A.M.S., Falkowski, M.J., Hudak, A.T., Evans, J.S. and Robinson, A.P. 2010. Comparing field and remote estimates of forest canopy cover. Canadian Journal of Remote Sensing, Vol. 35, No. 5, pp. 447–459.
  • Townshend, J.R.G., Huang, C., Kalluri, S.N.V., Defries, R.S., Liang, S. and Yang, K. 2000. Beware of per-pixel characterization of land cover. International Journal of Remote Sensing, Vol. 21, No. 4, pp. 839–843. doi:10.1080/014311600210641.
  • Tucker, C.J. 1979. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of the Environment, Vol. 8, No. 1, pp. 127–150. doi:10.1016/0034-4257(79)90013-0.
  • Turker, M. and Arikan, M. 2005. Sequential masking classification of multi-temporal Landsat7 ETM+ images for field-based crop mapping in Karacabey, Turkey. International Journal of Remote Sensing, Vol. 26, No. 17, pp. 3813–3830. doi:10.1080/01431160500166391.
  • USDA NASS. 2007. USDA, National Agricultural Statistics Service, 2007 California Cropland Data Layer. Available from http://www.nass.usda.gov/research/Cropland/metadata/metadata_ca07.htm [accessed 23 November 2010].
  • USDA NASS. 2009. The USDA/NASS Cropland Data Layer. Available from http://www.nass.usda.gov/research/Cropland/Method/cropland.pdf [accessed 23 November 2010].
  • Vogelman, J.E., Howard, S.M., Yang, L., Larson, C.R., Wylie, B.K. and Van Driel, N. 2001. Completion of the 1990s National Land Cover Data set for the conterminous United States for Landsat Thematic Mapper data and ancillary data sources. Photogrammetric Engineering and Remote Sensing, Vol. 67, No. 1, pp. 650–655.
  • Wardlow, B.D. and Egbert, S.L. 2008. Large-area crop mapping using time-series MODIS 250 m NDVI data: An assessment for the U.S. Central Great Plains. Remote Sensing of Environment, Vol. 112, No. 1, pp. 1096–1116.
  • Wellicome, T.I. and Holroyd, G.L. 2001. The second international burrowing owl symposium: background and context. Journal of Raptor Research, Vol. 35, No. 1, pp. 269–273.
  • Williams, D. 2004. Landsat-7 Science Data User's Handbook [online] Available from http://landsathandbook.gsfc.nasa.gov/handbook.html [cited 8 August 2010].
  • Witt, G.B., Luly, J. and Fairfax, R.J. 2006. How the west was once: vegetation change in south-west Queensland from 1930 to 1995. Journal of Biogeography, Vol. 33, No. 1, pp. 1585–1596. doi:10.1111/j.1365-2699.2006.01531.x.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.