Species composition and minimum sampling area of a riparian mixed broadleaved-Korean pine forest in Changbai Mountain Nature Reserve

Riparian areas are unique although often small component of the overall watershed landscape. The structure of riparian forests along Erdaobai River on the north slope of Changbai Mountain were investigated by using field data collected from eight sampling transects perpendicular to the Erdaobai River channel. Two kinds of species-area saturation curves were used to examine the relationship between species number and minimum sampling area. The results showed that riparian gymnosperms accounted for a high proportion of all gymnosperms in the Changbai Mountain Nature Reserve while riparian ferns and angiosperms accounted for a relatively low proportion. The average minimum sampling areas of riparian forest that included 60%, 80%, and 90% of the community species pool were about 85, 185, and 328 m 2 , respectively; while those for nonriparian forest were about 275, 390, and 514 m 2 , correspondingly.

Multiple Measurement Models of Articulated Arm Coordinate Measuring Machines

The existing articulated arm coordinate measuring machines（AACMM） with one measurement model are easy to cause low measurement accuracy because the whole sampling space is much bigger than the result in the unstable calibration parameters. To compensate for the deficiency of one measurement model, the multiple measurement models are built by the Denavit-Hartenberg＇s notation, the homemade standard rod components are used as a calibration tool and the Levenberg-Marquardt calibration algorithm is applied to solve the structural parameters in the measurement models. During the tests of multiple measurement models, the sample areas are selected in two situations. It is found that the measurement errors＇ sigma value（0.083 4 ram） dealt with one measurement model is nearly two times larger than that of the multiple measurement models（0.043 1 ram） in the same sample area. While in the different sample area, the measurement errors＇ sigma value（0.054 0 ram） dealt with the multiple measurement models is about 40% of one measurement model（0.137 3 mm）. The preliminary results suggest that the measurement accuracy of AACMM dealt with multiple measurement models is superior to the accuracy of the existing machine with one measurement model. This paper proposes the multiple measurement models to improve the measurement accuracy of AACMM without increasing any hardware cost.

Validation of GIS layers in the EU:getting adapted to available reference data

An optimal validation of a thematic map would ideally require in-situ observations of a large sample of units specifically conceived for the map under validation.This is often not possible due to budget limitations.The alternative can be using photo-interpretation of high or very high resolution images instead of in-situ observations or using available data sets that do not fully comply with the ideal characteristics:unit size,reference date or sampling plan.This paper illustrates some examples of use of available data in the European Union.For land cover maps,the best existing data set is probably Land Use/Cover Areaframe Survey(LUCAS)that has been conducted by Eurostat on four occasions since 2001.Because LUCAS is based on systematic sampling,advantages and limitations of systematic sampling are discussed.A fine-scale population density map is presented as an example of a situation in which reference data on a statistical sample cannot be collected.