A W F Projects   |   Prof. Dr. Christoph Kleinn - M.Sc. Haijun Yang
Modified adaptive cluster sampling with conditional extension of field plots - development of response and estimation design


While standard forest inventories, in which closed forest areas are the major target objects, are well developed with respect to potential sampling design options, there are many open questions when it comes to the inclusion of other woody resources like small patches and groups of trees or scattered trees outside the forest (TOF).

In the arid and ecologically vulnerable region of western China, the tree resources outside the forest exert a significant function in anti-desertification, and also in disaster prevention in general.

However, these tree resources are - as of yet - not integrated into the forest inventories nor in the general forest management carried out in this region.

Basic research is, therefore, required to develop adapted sampling and response design options to allow efficient information procurement.

This is a Sino-German research project funded by DFG (Deutsche Forschungsgemeinschaft) and NFSC (National Science Foundation of China).


Overall objective of this research is to support sustainable forest management by increasing the efficiency of sampling for a particular class of population, characterized by the occurrence of relatively rare and predominantly clustered objects.

On the scientific and technical level, the objective is to devise a set of estimators for a new class of adaptive sampling (called "modified adaptive cluster sampling"), which has a simpler adaptation process than the standard adaptive cluster sampling.


03.06 - 04.06: Preparation
04.06 - 05.06: Selection of study sites, provision of materials, image analysis and mapping
06.06 - 12.06: Data acquisition and generation
01.07 - 08.07: Simulation studies with artificial and field data
09.07 - 08.08: Estimator development for conditional plot extension
09.08 - 10.08: Comparison of the performance of proposed response design to others
11.08 - 12.08: Elaboration of approaches how to include the proposed design element in forest inventories and other sampling studies for natural resources assessment
01.09 - 02.09: Reporting


Acharya, B., Bhattarai, G., Gier, A. de, and Stein, A. 2000. Systematic adaptive cluster sampling for the assessment of rare tree species in Nepal. Forest Ecology and Management 137: 65–73.

Brown, J. A. 1994. The application of adaptive cluster sampling to ecological studies. PP. 86–97. In: D. J. Fletcher and B. F. J. Manly, eds., Statistics in Ecology and Environmental Monitoring. Dunedin: University of Otago Press.

Brown, J.A. 2003. Designing an efficient adaptive cluster sample. Environmental and Ecological Statistics 10, pp. 95–105

Kleinn, C. 2000b. On large area inventory and assessment of trees outside forests. Unasylva 200 (2000/1) Vol. 51., pp. 3–10.

Kleinn, C., Morales, D., Ramirez, C., Suazo, G. and Morales, J. 2000. TROF project. (2000). Scientific annual report, Central American Partners. Unpublished draft project document, 17p.

Roesch, F. A. Jr. 1993. Adaptive Cluster Sampling for Forest Inventories. Forest Science, Vol. 39, No. 4, pp. 655–669.

Sadio, S., Kleinn, C. and Michaelsen T. (eds.) 2002. Proceedings – Expert consultation on enhancing the contribution of trees outside forests to sustainable livelihoods. Rome 26–28 November 2001. FAO Forest Conservation, Research and Education Service, Forest Resources Division. 171p.

Smith, D. R., J. A. Brown, and N. C. H. Lo. 2004. Application of adaptive cluster sampling to biological populations. In: W. L. Thompson (ed.), Sampling rare or elusive species: Concepts, designs, and techniques for estimating population parameters. Island Press, Covelo, CA

Thompson, S.K. 1990. Adaptive cluster sampling. Journal of the American Statistical Association 85: 1050–1059.

Thompson, S.K. and Seber, G.A.F. 1996. Adaptive Sampling. New York, Wiley, 265pp.

An annotated bibliography on sampling rare and clustered populations [PDF, 60KB]


Prof. Dr. Shouzheng Tang
Institute of Forest Resources Information
Chinese Academy of Forestry
P.R. China


Prof. Dr.Christoph Kleinn
Abteilung Waldinventur und Fernerkundung
Büsgenweg 5, 37077 Göttingen
Tel. +49 551 39 3472

 Participating Scientists

M.Sc. Haijun Yang
Abteilung Waldinventur und Fernerkundung
Büsgenweg 5, 37077 Göttingen
Tel. +49 551 39 3574


DFG (Deutsche Forschungsgemeinschaft)
NFSC (National Science Foundation of China)

 Time Frame

March 2006 – February 2009