Calculation of Upper Confidence Bounds on Proportion of Area containing Not-sampled Vegetation Types: An Application to Map Unit definition for Existing Vegetation Maps

Autor/innen

  • Paul L. Patterson USDA Forest Service, Rocky Mountain Research Station, FIA, USA
  • Mark Finco USDA Forest Service, Remote Sensing Applications Center, USA

Schlagwörter:

Map unit, remote sensing, FIA, dominance type, grid sampling, confidence bounds, mid-level map

Abstract

This paper explores the information forest inventory data can produce regarding forest types that were not sampled and develops the equations necessary to define the upper confidence bounds on not-sampled forest types. The problem is reduced to a Bernoulli variable. This simplification allows the upper confidence bounds to be calculated based on Cochran (1977). Examples are provided that demonstrate how the resultant equations are relevant to creating mid-level vegetation maps by assisting in the development of statistically defensible map units.

Autor/innen-Biografien

  • Paul L. Patterson, USDA Forest Service, Rocky Mountain Research Station, FIA, USA

    Dr. Paul Patterson is a mathematical statistician for the Interior West region of the Forest Inventory and Analysis (FIA) program of the USDA Forest Service. Dr. Patterson provides statistical and analytical support to all aspects of the FIA program. Hi [...]

  • Mark Finco, USDA Forest Service, Remote Sensing Applications Center, USA

    Dr. Mark Finco is a senior scientist and principal at RedCastle Resources Inc., the primary contractor at the Remote Sensing Applications Center (RSAC), U.S. Forest Service. Dr. Finco currently leads the technical staff for RSAC’s Inventory, Analysis and Accuracy Assessment and Operations Programs, and has responsibility for RSAC’s contract support to the Forest Inventory and Analysis (FIA) program.  For over a decade, he has been active in projects which range widely in scale and application, ranging from exploiting large-scale aerial photography to collect forest inventory data to using MODIS imagery in conjunction with FIA data to develop nationwide maps of forest metrics.  

Literaturhinweise

Bechtold, W.A.; Patterson, P.L. Editors. (2005). The enhanced Forest Inventory and Analysis program-national sampling design and estimation procedures. Gen. Tech. Rep. SRS-80. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. http://www.srs.fs.usda.gov/pubs/gtr/gtr_srs080/gtr_srs080.pdf. Lasted accessed August 2, 2011.

Brohman, R.; Bryant, L. eds. 2005. Existing Vegetation Classification and Mapping Technical Guide. Gen. Tech. Rep. WO-67. Washington, DC: U.S. Department of Agriculture Forest Service, Ecosystem Management Coordination Staff. 305 p. http://www.fs.fed.us/emc/rig/includes/VEG_guide.pdf. Lasted accessed August 2, 2011.

Buffalo Ranger District (2009). Buffalo Valley Fuels Reduction Project - Draft Environmental Assessment, U.S. Department of Agriculture Forest Service, Bridger-Teton National Forest, Buffalo Ranger District, October 2009. 100p.

Cochran, W.G. 1977. Sampling Techniques. Ed. 3. Wiley, New York. 428 p.

Gillham, J.; Goetz, W.; Fisk, H.; Lachowski, H.; Davy, L. 2007. Existing vegetation summary: Bridger-Teton National Forest. RSAC-0091-TECH1. Salt Lake City, UT: U.S. Department of Agriculture, Forest Service, Remote Sensing Applications Center. 124 p.

Thompson, Michael T.; DeBlander, Larry T.; Blackard, Jock A. 2005. Wyoming's Forests, 2002. Resour. Bull. RMRS-RB-6. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 148 p. http://www.fs.fed.us/rm/ogden/pdfs/wyoming_state.pdf. Lasted accessed August 2, 2011.

Veröffentlicht

2011-08-01

Ausgabe

Rubrik

Special Section on Advanced FIA Data Analysis

Zitationsvorschlag

Calculation of Upper Confidence Bounds on Proportion of Area containing Not-sampled Vegetation Types: An Application to Map Unit definition for Existing Vegetation Maps. (2011). Mathematical and Computational Forestry & Natural-Resource Sciences (MCFNS), 3(2), Pages: 98-101 (4). https://www.tmp.17921125833755a190e36a5857.temporary.link/index.php/Journal/article/view/MCFNS.3-98

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