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• Environmental objective analysis, ranking and clustering of Hungarian cities

  91-108

  László Makra

  Zoltán Sümeghy

  Views:

  58

  The aim of the study was to rank and classify Hungarian cities and counties according to their environmental quality and level of environmental awareness. Ranking of the Hungarian cities and counties are represented on their „Green Cities Index” and „Green Counties Index” values. According to the methodology shown in Part 1, cities and counties were grouped on different classification techniques and efficacy of the classification was analysed. However, they did not give acceptable results either for the cities, or for the counties. According to the parameters of the here mentioned three algorithms, reasonable structures were not found in any clustering. Clusters received applying algorithm fanny, though having weak structure, indicate large and definite regions in Hungary, which can be circumscribed by clear geographical objects.

• Agricultural sector, rural environment and biodiversity in the Central and Eastern European EU member states

  46-64

  Jaan Liira

  Tsipe Aavik

  Oliver Parrest

  Martin Zobel

  Views:

  50

  During the second half of the 20th century, agriculture and the rural environment diverged in Western and Central and Eastern European countries (CEEC). CEE countries itself are heterogeneous in the respect of land use intensity and history. In the current review we focus on the comparison of the agricultural sector and threats on biodiversities of EU new-member countries from Central and Eastern Europe and the old EU(15) member states. The clustering of countries revealed groups distinguished according to the level of their economic productivity, discriminating mostly among eastern and western European countries. CEE countries sub-divided according to geographic region, including also some old members of the EU. Within the western cluster, two large sub-clusters became evident according to economy affected by altitudinal and climatic differences. Partly because there are still areas where the intensity of land use remained low, the biological diversity in many regions of Central and Eastern Europe has remained high. However, loss of extensively used habitats, the restoration on intensive agriculture, reforestation with exotic species and urbanization are major threats to nature in CEE countries. The estimated variability among CEE countries is caused by different historical and cultural backgrounds of those countries. Due to the complexity and geographical diversity of driving forces, there remains much uncertainty in the possible impacts of particular factors on land use. This complexity and diversity have to be considered when planning economic as well as ecological means for developing the agricultural sector and conserving biodiversity in the future of CEE countries.

• Unsupervised classification of high resolution satellite imagery by self-organizing neural network

  37-44

  Árpád Barsi

  Katalin Gáspár

  Zsuzsanna Szepessy

  Views:

  42

  The current paper discusses the importance of the modern high resolution satellite imagery. The acquired high amount of data must be processed by an efficient way, where the used Kohonen-type self-organizing map has been proven as a suitable tool. The paper gives an introduction to this interesting method. The tests have shown that the multispectral image information can be taken after a resampling step as neural network inputs, and then the derived network weights are able to evaluate the whole image with acceptable thematic accuracy.