A W F Projects   |   Prof. Dr. Christoph Kleinn - M.Sc. Jong-Su Yim
Research on an efficient forest assessment design as planning tool for sustainable forest management in South-Korea


This research project is about design elements of the national level forest inventory for a country with difficult forest conditions, with the objective to develop efficient and objective-oriented inventory design options on scientific grounds.
South-Korea has a forest cover of over 60%. Topography is mountainous in the densely forested North of South-Korea. Together with a very low density network of forest roads, this topography presents extremely difficult conditions for forest inventory field work.
The national forest inventory has been carried out in South-Korea since the 1970s. Since the inventory is based on aerial photograph interpretation and field surveys, it is a rotation system at interval of 10 years by provinces; currently, this NFI is in its fourth cycle implemented by the Korea Forest Research Institute; but – despite of the changing information needs and technological development - the inventory design has remained unchanged.
Therefore, one of the major points in optimizing the Korean NFI is trying to reduce the field work effort by an efficient integration of remote sensing and by an optimization of plot and sampling design.


In this study, three research questions will be worked on with the overall objective to raise the efficiency of the Korean NFI:

1) Remote sensing integration: With field and map data from the third NFI, regionalization approaches are being researched into and compared. Focus is on regression modelling approaches and the knn-method, their applicability to Korean forest conditions is tested and their possible limitations are identified.

2) Plot design optimization: With field data from the third NFI and own field observations, type and size of the field observation units (field plots) are optimized for the conditions of different forest types.

3) Sampling design optimization: With field data from the third NFI and in simulation studies sampling design options are compared and analysed, integrating also the findings of the technical objectives (1) and (2).

While the research and further development of assessment methods is being carried out for the specific conditions of South Korean forests, the results are of general interest in forest inventory research.


A. Research on remote sensing support for the large area forest inventory

01.05 - 02.05: Preoperative
03.05 - 05.05: Image processing and enhancement
06.05 - 09.05: Geo-referencing of field plot
10.05 - 01.06: Pixelwise prediction and assessment of accuracy

B. Research on plot design optimization

01.06 - 03.06: Analysis of forest structure
04.06 - 06.06: Statistical and Practical considerations

C. Research on sampling design optimization

06.06 - 08.06: Analysis of respective results of work step A and B
08.06 - 10.06: Generating artificial population
11.06 - 02.07: Simulation study
03.07 - 06.07: Reporting


Holmström H., M. Nilsson and G. Stáhl, 2002: Forecasted reference sample plot data in estimations of stem volume using satellite spectral data and the kNN method. International Journal of Remote sensing 23(9): 757–1774.

Katila M. and Tomppo E., 2002: Stratification by ancillary data in multisource forest inventories employing k-nearest-neighbour estimation. Canadian Journal of Forest Research 32(9): 1548–1561.

Kleinn C., 1994: Comparison of the performance of line sampling to other forms of cluster sampling. Forest Ecology and management 68:365–373.

Kleinn, C., 1996: Ein Vergleich der Effizienz von verschiedenen Clusterformen in forstlichen Großrauminventuren. Forstw. Cbl. 115:378–390.

Kleinn, C., C. Ramírez, P. Holmgren, G. Chavez. Submitted. A national forest resources assessment for Costa Rica based on low intensity sampling. Submitted 2003 to Forest Ecology and Management.

Korea Forest Research Institute (KFRI), 1996: Manual of the fourth national forest inventory in South-Korea. 49p.

Korea Forest Service, 2003: Statistical yearbook of forestry. 408p.

Magnussen, S., P. L. Boudewyn, M. Wulder and D. Seemann, 2000: Predictions of forest inventory cover type proportions using Landsat TM. Silva Fennica 34(4):351–370.

Shin M. Y., J. S. Yim and D. K. Rho, 2002: The Opinion Trend of Forest Specialists for National Forest Inventory System in Korea. Korean Journal of Forest Resource Measurement 5(2):21–34.

Tomppo E., C. Goulding and M. Katila, 1999: Adapting Finnish Multi-Source Forest Inventory Techniques to the New Zealand Preharvest Inventory. Scand. J. For. Res. 14: 182–192.

Internet pages:
FAO.2003. FRA 2005 terms and definition.


Prof. Dr. Man-Yong Shin
Department of Forest Resource
Kookmin University


Prof. Dr.Christoph Kleinn
Institut für Waldinventur und Waldwachstum
Büsgenweg 5, 37077 Göttingen
Tel. +49 551 39 3472

 Participating Scientists

M.Sc. Jong-Su Yim
Institut für Waldinventur und Waldwachstum
Büsgenweg 5, 37077 Göttingen
Tel. +49 551 39 3576


DFG (Deutsche Forschungsgemeinschaft)
KOSEF (Korea Sceince and Engineering Foundation)

 Time Frame

January 2005 – June 2007