IDEAS home Printed from https://ideas.repec.org/p/ags/unasrr/234254.html
   My bibliography  Save this paper

Comparing 30 Meter Imagery from Landsat 5 and 7 for Crop Area Estimation

Author

Listed:
  • Craig, Michael E.

Abstract

This paper compares digital, multi-spectral imagery from the Landsat 5 Thematic Mapper with that of the Landsat 7 Enhanced Thematic Mapper when used to discriminate crop types for area estimation. Comparisons are done for different types of crop areas in several states, using images that are only one day apart. The overlaps between adjacent paths in several major crops states are used to define the analysis areas. A simple non-parametric paired sample sign test is used to determine statistical significance of differences. Standardized techniques as used in the Agency's Cropland Data Layer Project are used for image processing, including a modified supervised pattern recognition /clustering approach for cover type signatures and maximum likelihood for categorization. Ground truth data consist of 211 one and two square mile areas selected in a stratified random sample and visited in June of the corresponding crop year. Sampling rates for the ground data range from one in 30 to one in 166 depending on the state and land use stratum.

Suggested Citation

  • Craig, Michael E., 2002. "Comparing 30 Meter Imagery from Landsat 5 and 7 for Crop Area Estimation," NASS Research Reports 234254, United States Department of Agriculture, National Agricultural Statistics Service.
    • Handle: RePEc:ags:unasrr:234254
    DOI: 10.22004/ag.econ.234254
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/234254/files/02_02_Compare_L5_L7_MEC.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.234254?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Vogel, Fred A. & Bange, Gerald A., 1999. "Understanding USDA Crop Forecasts," USDA Miscellaneous 320799, United States Department of Agriculture.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. MacDonald, Stephen, 2005. "A Comparison of USDA's Agricultural Export Forecasts with ARIMA-based Forecasts," MPRA Paper 70912, University Library of Munich, Germany.
    2. Siddhartha S. Bora & Ani L. Katchova & Todd H. Kuethe, 2021. "The Rationality of USDA Forecasts under Multivariate Asymmetric Loss," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1006-1033, May.
    3. Michael K. Adjemian & Valentina G. Bruno & Michel A. Robe, 2020. "Incorporating Uncertainty into USDA Commodity Price Forecasts," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 696-712, March.
    4. repec:kap:iaecre:v:15:y:2009:i:4:p:470-482 is not listed on IDEAS
    5. Tianyang Zhang & Ziran Li, 2022. "Can a rational expectation storage model explain the USDA ending grain stocks forecast errors?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(3), pages 313-337, March.
    6. Isengildina, Olga & Irwin, Scott H. & Good, Darrel L., 2013. "Do Big Crops Get Bigger and Small Crops Get Smaller? Further Evidence on Smoothing in U.S. Department of Agriculture Forecasts," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 45(1), pages 1-13, February.
    7. Isengildina-Massa, Olga & Irwin, Scott H. & Good, Darrel L. & Gomez, Jennifer K., 2008. "The Impact of Situation and Outlook Information in Corn and Soybean Futures Markets: Evidence from WASDE Reports," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 40(1), pages 89-103, April.
    8. repec:ags:unassr:234254 is not listed on IDEAS
    9. Kaus, Taylor T. & Mattos, Fabio L., 2017. "Too much information? How relevant are agricultural reports that provide similar information?," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258367, Agricultural and Applied Economics Association.
    10. Raghav Goyal & Michael K. Adjemian, 2023. "Information rigidities in USDA crop production forecasts," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(5), pages 1405-1425, October.
    11. Goyal, Raghav & Adjemian, Michael K., 2022. "Information Rigidities in USDA Forecasts," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322339, Agricultural and Applied Economics Association.
    12. Goyal, Raghav & Adjemian, Michael K., 2021. "The 2019 government shutdown increased uncertainty in major agricultural commodity markets," Food Policy, Elsevier, vol. 102(C).
    13. Olga Isengildina-Massa & Scott H. Irwin & Darrel L. Good & Jennifer K. Gomez, 2008. "Impact of WASDE reports on implied volatility in corn and soybean markets," Agribusiness, John Wiley & Sons, Ltd., vol. 24(4), pages 473-490.
    14. Arnade, Carlos Anthony & Hoffman, Linwood A., 2020. "The Impact of Public Information on Commodity Market Performance : The Response of Corn Futures to USDA Corn Production Forecasts," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304181, Agricultural and Applied Economics Association.
    15. No, Sung Chul & Salassi, Michael E., 2008. "A Sequential Rationality and Efficiency Test of U.S. Department of Agriculture Program Crop Price Estimates: Rice, Wheat, and Soybeans," 2008 Annual Meeting, February 2-6, 2008, Dallas, Texas 6814, Southern Agricultural Economics Association.
    16. GwanSeon Kim & Mehdi Nemati & Steven Buck & Nicholas Pates & Tyler Mark, 2020. "Recovering Forecast Distributions of Crop Composition: Method and Application to Kentucky Agriculture," Sustainability, MDPI, vol. 12(7), pages 1-17, April.
    17. Sung No & Michael Salassi, 2009. "A Sequential Rationality Test of USDA Preliminary Price Estimates for Selected Program Crops: Rice, Soybeans, and Wheat," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 15(4), pages 470-482, November.
    18. Adjemian, Michael K. & Bruno, Valentina G. & Robe, Michel A., 2016. "Forward‐Looking USDA Price Forecasts," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235931, Agricultural and Applied Economics Association.
    19. Botto, Augusto C. & Isengildina, Olga & Irwin, Scott H. & Good, Darrel L., 2006. "Accuracy Trends and Sources of Forecast Errors in WASDE Balance Sheet Categories for Corn and Soybeans," 2006 Annual meeting, July 23-26, Long Beach, CA 21332, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    20. Isengildina-Massa, Olga & Irwin, Scott H. & Good, Darrel L., 2008. "Quantile Regression Methods of Estimating Confidence Intervals for WASDE Price Forecasts," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6409, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    21. Adjemian, Michael K. & Irwin, Scott H., 2020. "The market response to government crop news under different release regimes," Journal of Commodity Markets, Elsevier, vol. 19(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:unasrr:234254. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://www.nass.usda.gov/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.