Data partnership synergy: The Cropland Data Layer

2009 17th International Conference on Geoinformatics, Geoinformatics 2009

Volumn , Issue , 2009, Pages

  Mueller, Rick ^a   Boryan, Claire ^a   Seffrin, Robert ^a  

^a Research and Development Division   (United States)

Author keywords

Agriculture; AWiFS; Common Land Unit; Decision tree classification; Partnership

Indexed keywords

AGRICULTURAL LANDSCAPES; CLASSIFICATION METHODS; COLLABORATIVE PARTNERSHIPS; COMMON LAND UNIT; COMMON LAND UNITS; COUNTY LEVEL; DATA LAYER; DATA SETS; DATA SHARING; DECISION MAKERS; DECISION SUPPORTS; DECISION TREE CLASSIFICATION; ESTIMATION PROCESS; FOREST CANOPIES; GEO-SPATIAL; GROUND DATA; GROUND TRUTH; GROUND TRUTH DATA; GROWING SEASON; IMAGE ARCHIVES; LAND COVER; LAND COVER CLASSIFICATION; MULTI-SPECTRAL IMAGERY; NATIONAL AGRICULTURAL STATISTICS SERVICES; NON-AGRICULTURAL LANDS; PUBLIC DOMAINS; REGRESSION MODELING; REGRESSION TREES; SATELLITE DATA; STATISTICAL REPORTING; TECHNOLOGICAL EFFICIENCY; TRAINING DATA; US DEPARTMENT OF AGRICULTURES;

AGRICULTURAL PRODUCTS; CROPS; DECISION SUPPORT SYSTEMS; DECISION TREES; LANDFORMS; REMOTE SENSING; SATELLITE IMAGERY;

CLASSIFICATION (OF INFORMATION);

EID: 74349110063     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/GEOINFORMATICS.2009.5293489     Document Type: Conference Paper

References (15)

1. J. Allen, and G. Hanuschak, "The Remote Sensing Applications Program of the National Agricultural Statistics Service: 1980-1987," NASS Staff Report No. SRB-08-88, USDA, Washington, DC, 1988.
2. F. Vogel, and G. Bange, "Understanding USDA Crop Forecasts," In: NASS/WAOB Miscellaneous Publication No. 1554, U.S. Department of Agriculture, Washington DC, 1999.
3. M. Ozga, and M. Craig, "PEDITOR - Statistical Image Analysis for Agriculture," Presentation at the Washington Statistical Society (WSS) Seminar, USDA/NASS, Washington, DC, April, 1995.
4. R. Mueller, and R Seffrin, "New methods and satellites: A program update on the NASS Cropland Data Layer acreage program," ISPRS WG VIII/10 Workshop 2006 on Remote Sensing Support to Crop Yield Forecast and Area Estimates, Stresa, Italy, pp. 97 - 102, Nov. 2006.
5. rd International Workshop on the Analysis of Multi-temporal Remote Sensing Images, Biloxi, MS, May 2005.
6. J. Vogelmann, T. Sohl, P. Campbell, and D. Shaw, "Regional land cover chacterization using Landsat thematic mapper data and ancillary data sources," Environmental Monitoring and Assessment, Vol. 51, pp. 415 - 428, 1998.
7. C. Homer, C. Huang, L. Yang, B. Wylie, and M. Coan, "Completion of the 2001 National Land Cover Database for the conterminous United States," Photogrammetric Engineering & Remote Sensing Vol. 70, No. 7, pp. 829-840, July 2004.
8. D. Johnson, "A comparison of coincident Landsat-5 TM and Resourcesat-1 AWIFS imagery for classifying cropland," Photogrammetric Engineering & Remote Sensing Vol 74, No. 11 November 2008.
9. T. Anderson, T. Payne, K. Clarke, and C. Ernst, "USDA Service Center Agencies geospatial data management team Data Management Plan for Common Land Unit data," February, 2005 Accessed, July 04, 2009.
10. J. Hearld, "USDA establishes a Common Land Unit," ESRI ArcUser Online. April-June 2002, Accessed, July 04, 2009, .
11. R. Mueller, "Categorized mosaicked imagery from the National Agricultural Statistics Service cropland acreage estimation program," ASPRS 2000 Conference, ASPRS, Bethesda, MD. May 2000.
12. M. Friedl, and C. Brodley, "Decision tree of land cover from remotely sensed data," Remote Sensing of the Environment, 61: 339-409, 1997.
13. M. Hansen, R. Dubayah, and R. Defries, "Classification trees: An alternative to traditional landcover classifiers," International Journal of Remote Sensing, 17, pp. 1075-1081, 1996.
14. R. Lawrence, A. Bunn, S. Powell, and M. Zambon, "Classification of remotely sensed imagery using Stochastic Gradient Boosting as a refinement of classification tree analysis," Remote Sensing of the Environment, 90, pp. 331-336, 2004.
15. R. Quinlan, "Bagging, boosting, and C4.5," AAAI-96 Fourteenth National Conference on Artificial Intelligence, Portland OR, 1996.