Skip to main content
Log in

Improved strategies for coverage estimation by using replicated line-intercept sampling

  • Published:
Environmental and Ecological Statistics Aims and scope Submit manuscript

Abstract

Coverage, i.e., the area covered by the target attribute in the study region, is a key parameter in many surveys. Coverage estimation is usually performed by adopting a replicated protocol based on line-intercept sampling coupled with a suitable linear homogeneous estimator. Since coverage is a parameter which may be interestingly represented as the integral of a suitable function, improved Monte Carlo strategies for implementing the replicated protocol are introduced in order to achieve estimators with small variance rates. In addition, new specific theoretical results on Monte Carlo integration methods are given to deal with the integrand functions arising in the special coverage estimation setting.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Affleck DRL, Gregoire TG and Valentine HT (2005). Design unbiased estimation in line intersect sampling using segmented transects. Environ Ecol Stat 12: 139–154

    Article  Google Scholar 

  • Barabesi L (2003a). A Monte Carlo integration approach to Horvitz-Thompson estimation in replicated environmental designs. Metron LXI: 355–374

    Google Scholar 

  • Barabesi L (2003). Sampling designs for monitoring ecological diversity. In: El-Sharaawi, A (eds) Environmetrics, Encyclopedia of Life Support Systems (EOLSS), developed under the auspices of the UNESCO, pp. Eolss Publishers, Oxford

    Google Scholar 

  • Barabesi L and Fattorini L (1997). Line intercept sampling with finite populations: A stereological approach. Metron LV: 23–37

    Google Scholar 

  • Barabesi L and Fattorini L (1998). The use of replicated plot, line and point sampling for estimating species abundancies and ecological diversity. Environ Ecol Stat 5: 353–370

    Article  Google Scholar 

  • Barabesi L and Marcheselli M (2003). A modified Monte Carlo integration. Int Math J 3: 555–565

    Google Scholar 

  • Barabesi L and Marcheselli M (2005). Some large-sample results on a modified Monte Carlo integration method. J Stat Plan Inference 135: 420–432

    Article  Google Scholar 

  • Barabesi L and Pisani C (2002). Ranked set sampling for replicated sampling designs. Biometrics 58: 586–592

    Article  PubMed  Google Scholar 

  • Barabesi L and Pisani C (2004). Steady-state ranked set sampling for replicated environmental sampling designs. Environmetrics 15: 45–56

    Article  Google Scholar 

  • Bonham CD (1989). Measurements for terrestrial vegetation. Wiley, New York

    Google Scholar 

  • Bra’ezis H (1983). Analyse fonctionelle. Masson, Paris

    Google Scholar 

  • Canfield RH (1941). Application of line intercept method in sampling range vegetation. J For 39: 388–394

    Google Scholar 

  • Cruz-Orive LM (1993) Systematic sampling in stereology. In: Bulletin of the International Statistical Institute, Proceedings of 49th Session, Florence. 1993, 53:451–468

  • Evans M and Swartz T (2000). Approximating integrals via Monte Carlo and deterministic methods. Oxford University Press, Oxford

    Google Scholar 

  • Garca’ıa-Fiñana M and Cruz-Orive LM (2000). Fractional trend of the variance in Cavalieri sampling. Image Anal Stereol 19: 71–79

    Google Scholar 

  • Gregoire TG and Monchevich NS (1994). The reflection method of line intercept sampling to eliminate boundary bias. Environ Ecol Stat 1: 219–226

    Article  Google Scholar 

  • Gregoire TG and Valentine H (2003). Line intersect sampling: ell-shaped transect and multiple intersection. Environ Ecol Stat 10: 263–279

    Article  Google Scholar 

  • Haber S (1966). A modified Monte-Carlo quadrature. Math Comput 20: 361–368

    Article  Google Scholar 

  • Haber S (1967). A modified Monte-Carlo quadrature. II, Math Comput 21: 388–397

    Article  Google Scholar 

  • Husch B, Miller CI and Beers TW (1982). Forest mensuration. Wiley, New York

    Google Scholar 

  • Kaiser L (1983). Unbiased estimation in line-intercept sampling. Biometrics 39: 965–976

    Article  Google Scholar 

  • Lucas HA and Seber GAF (1977). Estimating coverage and particle density using line-intercept method. Biometrika 64: 618–622

    Article  Google Scholar 

  • Rubinstein RY (1981). Simulation and the Monte Carlo method. Wiley, New York

    Google Scholar 

  • Ryan DAJ (2004). Point sampling strategies for estimating coverage from benthic video transects. Environmetrics 15: 193–207

    Article  Google Scholar 

  • Seber GAF (1979). Transect of random length. In: Cormack, RM, Patil, GP and Robson, DS (eds) Sampling biological population, pp 183–192. International Co-operative Publishing House, Fairland, Maryland

    Google Scholar 

  • Todinov MT (2002). Distribution of properties from sampling inhomogeneous materials by line transects. Probabilistic Eng Mech 17: 131–141

    Article  Google Scholar 

  • Thompson SK (2002). Sampling. Wiley, New York

    Google Scholar 

  • U.S. Environmental Protection Agency (2002) Guidance on choosing a sampling design for environmental data collection, EPA QA/G-5S, Washington, DC, pp 1–166

  • Valentine HT, Gove JH and Gregoire TG (2001). Monte Carlo approaches to sampling forest tracts with lines or points. Can J Forestry Res 31: 1410–1424

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Lucio Barabesi.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Barabesi, L., Marcheselli, M. Improved strategies for coverage estimation by using replicated line-intercept sampling. Environ Ecol Stat 15, 215–239 (2008). https://doi.org/10.1007/s10651-007-0048-6

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10651-007-0048-6

Keywords

Navigation