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The Web Mapping Services (WMS) are very useful means for presentation of digital geospatial data in the Internet environment. Typical Open Source example of these services is development environment MapServer, which was originally developed by the University of Minnesota ForNet project in cooperation with NASA and the Minnesota Department of Natural Resources. MapServer is not a full-featured Geographical Information System (GIS), but provides the core functionality to support a wide variety of web applications. Complex and open information system about forest (and cultural) land is presented in real example of MapServer application with data from the Mendel University Training Forest. MapServer is used in effective representing of data for the University Forest staff, students and general public from October 2002. MapServer is usually applied in education process of GIS and Remote Sensing and for sharing of the Faculty of Forestry and Wood Technology Departments geospatial data.

This article describes a comparison of various programs for the automatic supervised classification used for identification of forest tree species representation from the aerial photographs. These programs were represented by American software Erdas Imagine 8.4, Czech products LuciaG 4.0 and TopoL DMT 6.014. The study displays a minor production forest area with proportion of four most frequently occurring tree species - spruce, larch, oak and ash in the research area of the forest region around Bystřice pod Hostýnem, the Czech Republic. For the reason of lower quality of spectrozonal photographs it was necessary to use some corrections; such as highlighting pen techniques, namely Kernel Processor Low-Frequency and High-Frequency filters, belonging to space operations. Photographs, modified in this way, served for a construction of individual training sets, which were consequently used within individual classification methods of directed classification in each comparative software. Self-classification took place at the level of a particular tree species. Classification accuracy was determined by comparison of results and reference data from the terrain research.
The outcome is, that the best classification for oak and ash was in combination with TopoL program, classification according to gravity centre and combination of solation + insolation signature of the treetop parts with an aggressive shade.
On the contrary, for spruce and larch was the best classification in combination with software Erdas Imagine, classification roles of intervals mahalanobis with combination of solation signature of the treetop parts, along these tree edges with an aggressive shade.

Digital terrain model (DTM) is considered as an important geospatial data layer. At the present in the Czech Republic, digital contour data sources are often used for constructing regular raster DTM; the initial process requires interpolation between the points in order to estimate values in a regular grid pattern. The commonly used data sources are: the Primary Geographic Data Base (ZABAGED), the Digital Territory Model (DMÚ25) and eventually the Regional Plans of Forest Development (OPRL). In this paper, some constructions of DTM based on the above mentioned data were tested using several software products. Algorithm parameters can be optimized in several ways; in this sense the most useful operations proved comparing the first and second derivative of DTM and its real appearance in terrain and using cross-validation procedure or terrain data measurements to compute and minimize the root mean square error values (RMSE). The Forest Training Enterprise "Masaryk Forest" was the area for the experimental optimization of DTM.

In the area of economical classification tasks, the accuracy maximization is often used to evaluate classifier performance. Accuracy maximization (or error rate minimization) suffers from the assumption of equal positive and negative error costs. Furthermore, accuracy is not able to express true classifier performance under skewed class distribution. Due to these limitations, the use of accuracy on real tasks is questionable. In a real binary classification task, the difference between the costs of positive and negative error is usually critical. To overcome this issue, the Receiver Operating Characteristic (ROC) method in relation to decision-analytic principles can be used. One essential advantage of this method is the possibility of classifier performance visualization by means of a ROC graph. This paper presents concrete examples of binary classification, where the inadequacy of accuracy as the evaluation metric is shown, and on the same examples the ROC method is applied. From the set of possible classification models, the probabilistic classifier with continuous output is under consideration. Mainly two questions are solved. Firstly, the selection of the best classifier from a set of possible classifiers. For example, accuracy metric rates two classifiers almost equivalently (87.7 % and 89.3 %), whereas decision analysis (via costs minimization) or ROC analysis reveal different performance according to target conditions of unequal error costs of positives and negatives. Secondly, the setting of an optimal decision threshold at classifier's output. For example, accuracy maximization finds the optimal threshold at classifier's output in value of 0.597, but the optimal threshold respecting higher costs of negatives is discovered by costs minimization or ROC analysis in a value substantially lower (0.477).

The aim of this study was detection of prevalence of the parasitecoenoses of sika deer (Cervus nippon) living in the wild in the area of Western Bohemia (Czech Republic) and to compare roundup data with results from previous investigations.
All together 560 samples of excrements and 8 grallochs were examined. The research was done from March 2005 to June 2007. The samples of excrements were collected during the whole research period in periodical monthly intervals always in the amount of 20 pieces. Grallochs were examined by partial helmintological dissection, the samples of excrements by Baermann method and flotation. Parasites were detected only in 26.8 % of examined samples. The spectrum of detected parasites included: coccidia Eimeria spp. (8.6 %), lungworms (LW) Dictyocaulus sp. and Bicaulus sagittatus (23.4 %), and nematode worms from the group of gastrointestinal nematodes (GIN) (7.9 %). In fine we can confirm that the Sika game is quite resistant against parasitoses under our conditions, and health of Sika game in monitored localities is good.

There are several metods of permanent pasture renovation. Different technologies were investigated on a pasture sward. Three seeders (Einböck seeder with the tine harrow, no-till Sulky disc seeder and SPP 8 strip seeder) and two fertilization regimes (with no fertilization and with mineral fertilization N₉₀P₃₀K₆₀ kg.ha^-1) were used to determine optimum methods of establishment and the use of oversowed pasture swards. In the first year, renovated plots had a higher DM production than control plots. The pasture oversowing had no effect on herbage production in the second production year. The fertilization had no effect in the first production year with a higher clover content in the sward. The share of clovers was higher in plots oversown with the Einböck and Sulky seeders but only in the second and third cuts of the first production year and in the third cut of the second production year. The highest content of clovers was observed in the second and third cuts. There was a positive correlation between the clover content in DM yield and herbage DM production. The oversowing did not show any effect on the grass content in the pasture sward.

Non-variant phase transformations in the binary diagrams have both, some common features and some differences. The authors arranged an interactive animation by the help of the computer to catch the time course of non-variant transformations in many contexts. The program helps to illustrate and describe the matter all of non-variant transformations.

In 2002-2006, mapping the goshawk (Accipiter gentilis L.) population was carried out at the SE edge of the Chřiby Upland, the Czech Republic. At the same time, the food spectrum of the predator was determined in detail in 2004. The studied area amounted to about 30 km². In the area, 5 nest localities occurred. Each year five occupied nests were observed. The food spectrum was analysed according to leftovers of food in nests and in the vicinity of the nests. In total, 387 leftovers of food were found. Birds represented 52%, mammals 42% and other animals (insect, reptiles etc.) 6% of prey. The population of goshawk was monitored from the period of a wedding flight to a period when young birds left their nest during the period of five years. The number of eggs was on average 2.9 per one nest. The total number of laid eggs was 73 during five years. The number of brood was on average 2.7 per one nest. Sex ratio was 47/53 per cent in favour of males. The total number of hatched birds was 68 during five years, out of the number 32 females and 36 males. Moreover, dimensions of nests at particular localities were also determined. The diameter of nests was on average 72.2 cm and the mean height of the actual nest was 48 cm. Nests occurred at an average height of 21.3 m.