Shrub encroachment and agricultural intensification have been a widespread occurrence in the former communist and socialist countries of Central and Eastern Europe. Such changes have strongly affected grassland areas which are seen as hotspots of biodiversity in Europe. In this study we have investigated the changes in grassland cover as well as the causal mechanism of those changes in a selected region in Northern Croatia during the post-socialist transition. By using the mixed methods approach we combined remote sensing, statistical modelling and a household-based questionnaire (n=285) to map the changes in the grassland cover and to assess the socioeconomic and bio-physical contributing factors of the documented changes. The results demonstrate that areas seeing general depopulation trends and population ageing, along with increases in the amount of educated people are characterized by shrub encroachment and farmland abandonment, while flatlands and lowland areas are seeing higher rates of grassland to farmland conversion. The results also show that the partial de-agrarization characteristic for the socialist period has become a full de-agrarization in the post-socialist period, with the main impetus being education, rather than employment, as was the case during socialism.

The Medvednica Nature Park was established in 1981. At that time its main phenomena were forests and forest communities which covered some two thirds of the protected area. The Park is located in close vicinity to Zagreb, the largest city in Croatia, which has been characterised by a considerable growth in population and area during the last several decades.This article reconstructs a segment of Medvednica protected area's environmental history from 1978 to 2007. The study combines textual and tabular as well as cartographic and remote sensing data in order to provide a clear insight into the proportions of deforestation and reforestation, and their spatial patterns across the entire area of the Park.Results indicate forest transition on more than one tenth of the protected area. These are mostly contact zones of human activities and forest communities located at the edges of the protected area and at its higher elevations. Results also indicate net forest gain of 8.3% over the 1978-2007 period. S obzirom na to da su šume bile glavni razlog osnutka Parka prirode Medvednica, primarni fokus istraživanja bio je usmjeren upravo na prostorne promjene šumskog pokrova. Rezultati upućuju da se promjena šumskog pokrova (deforestacija ili reforestacija) odvija na više od jedne desetine ukupne površine Parka. Riječ je o kontaktnim zonama ljudskih aktivnosti i šumskih zajednica koje se nalaze uglavnom na rubu te zonama na višim nadmorskim visinama zaštićenog područja. Rezultati također pokazuju da bilanca prostornih promjena šumskog pokrova ide u korist reforestacije za otprilike 8. 3% tijekom razdoblja 1978. -2007.

The academic picture of a globalized European countryside, and particularly of rural areas in postsocialist, new member states of the European Union, is one of huge and increasing complexity, diversity, and uncertainties about the future. The aim of this research is to construct alternative scenarios for rural Croatia in 2030, acknowledging its postsocialist transition as an important framework. Future development scenarios were constructed by integrating quantitative and qualitative approaches. The main methods used

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U radu je provedena prostorna analiza upisnih područja državnih (redovnih) osnovnoškolskih ustanova u Gradu Zagrebu. Prostorna analiza provedena je na temelju podataka prikupljenih od nadležnih gradskih službi te Državnog zavoda za statistiku, koji su objedinjeni u bazu podataka, odnosno kartirani, obrađeni i vizualizirani pomoću GIS aplikacija.Ustanovljeno je da upisna područja definirana Odlukom o mreži osnovnih škola na području Grada Zagreba iz 2007. prelaze granice gradskih četvrti, naselja, pa čak i županije, diskontinuirana su i međusobno se prožimaju. Značajni broj kućnih brojeva dodijeljenih određenim upisnim područjima izlazi izvan GUP-om preporučenog obuhvata od šesto metara. Istražene su prosječne i maksimalne udaljenosti pripadajućih kućnih brojeva od osnovnih škola, koje također prelaze udaljenost od šesto metara.Bufferi izrađeni na temelju adresa osnovnih škola i preklopljeni sa slojevima podataka o korištenju i namjeni prostora u Gradu Zagrebu upućuju na kvalitetu okruženja pojedinih škola i potencijalne prijetnje u njihovu susjedstvu. Analiza je pokazala značajne razlike u korištenju i namjeni prostora u okruženju škola.

It has been shown that simulation models are reliable tools for predicting land changes, which contributes to better understanding and management of human impact on the environment. Land use and land cover changes in the Lower Neretva Region between 1990 and 2035 have been analysed and modelled in this study. The final simulation model of future changes was created based on cellular automata and artificial neural networks, implemented in the MOLUSCE plugin for QGIS. In addition, a test simulation model for 2020 was created, which showed high accuracy. Input variables for the final simulation model included a digital elevation model (DEM), slope, distance from water bodies, distance from built-up areas, and population density by settlement in 2011 and 2021. According to the results, forests and grasslands will expand and occupy almost 45% of the area. A slight increase in built-up and agricultural areas is expected, while swamps, water bodies, and sparse vegetation areas will decrease.

Klasifikacija zemljišnog pokrova urbanog i periurbanog prostora pomoću objektno orijentirane analize multispektralnih snimaka Luka ValožićUpotrebom metode nadzirane klasifikacije primjenjuje se stečeno znanje, iskustvo i razumijevanje prostora kako bi se odabrali odgovarajući uzorci klasa zemljišnog pokrova koji će usmjeriti algoritme računalnog programa na podjelu svih elemenata slike u zadani broj imenovanih razreda. Algoritmom multirezolucijske segmentacije koji uzima u obzir spektralna i geometrijska svojstva slike, satelitska se snimka prema zadanim parametrima dijeli u određeni broj homogenih skupina piksela. Na taj način stvoreni segmenti ili objekti slike upotrebljavaju se umjesto pojedinih piksela kao jedinice uzoraka klasa zemljišnog pokrova. Za provjeru točnosti klasifikacije i izradu matrice pogrešaka koriste se prostorno nasumično raspoređeni uzorci referentnih i klasificiranih podataka stratificirani prema unaprijed definiranim klasama zemljišnog pokrova. Na 32. međunarodnom geografskom kongresu održanom 2012. u Kölnu u Njemačkoj rad je predstavljen pod naslovom Object-based LULC classification of urban and periurban areas.Ključne riječi: zemljišni pokrov, satelitske snimke, metoda nadzirane klasifikacije, segmentacija slike, matrica pogrešaka, V-I-S model Land Cover Classification of Urban and Peri-urban Areas Using Object-oriented Analysis of Multispectral ImagerySupervised classification of remote sensing imagery implies usage of a priori knowledge of analysed area of interest for proper selection of land cover classes' samples. Spectral and geometric properties of the satellite image were taken into account by parameters of the multiresolution segmentation algorithm that has been used to divide the selected subset of the scene into homogeneous groups of pixels. Such image segments were used as land cover samples for supervised classification. Accuracy assessment was performed by means of error matrix based on stratified random samples.

Changes in land use and land cover are the result of complex interactions between humans and their environment. This study examines land use and land cover changes in the Lower Neretva Region between 1990 and 2020. Political and economic changes in the early 1990s resulted in changes in the landscape, both directly and indirectly. Multispectral image processing was used to create thematic maps of land use and land cover for 1990, 2005, and 2020. Satellite images from Landsat 5, Landsat 7 and Landsat 8 were the main source of data. Land use and land cover structure was assessed using a hybrid approach, combining unsupervised and manual (visual) classification methods. An assessment of classification accuracy was carried out using a confusion matrix and kappa coefficient. According to the results of the study, the percentage of built-up areas increased by almost 33%. Agricultural land and forests and grasslands also increased, while the proportion of swamps and sparse vegetation areas decreased.