Impact of Transitional Dynamics Induced by Socio-Economic Changes in Post-Communist Romania on Land Cover and Use

Impact of transitional dynamics induced by socio-economic changes in post-communist Romania on land cover and use

Alexandru-Ionuţ PETRIŞOR “Ion Mincu” University of Architecture and Urbanism & National Institute for Research and Development in Constructions, Urbanism and Sustainable Spatial Development URBAN-INCERC, Bucharest, Romania [email protected]

1. Background eco-energy (defined as the initial energy of a territorial system before the conscious intervention of man over its structures), at In a seminal study published in 2011, Dale et al. introduced the two spatial scales. Petrişor (2012b) carried out a national analysis term “global change” to encompass all anthropogenic impacts aimed at assessing the extent of urbanization during 1990–2000 affecting our planet, including land use and cover changes, and 2000–2006; results indicated that, since the urban settle- climate change and alterations in the use of energy. According ments make up only a small share of the total land cover, the to Jensen (2000), land cover represents a description of what true extent can be determined only when rationing the area of is actually there from a biophysical viewpoint, and land use areas affected by change to the area covered by built up or urban identifies how the human communities utilize what lies on features. Overall, the three studies suggest that socio-economic the surface of Earth; the definition was changed by Petrişor et drivers are the main factors accounting for land use and cover al. (2010), showing that land use indicates a detailed typology changes, especially in the developing economies. of natural systems and the utilization of the artificial ones by human communities. The European Union utilizes three-level CORINE classification (de Lima 2005); the first one reflects land 2. Data and methodology cover, while the second and third ones correspond to a more or less detailed description of land use in man-dominated systems The methodology used in this study is an alteration of the or typology of natural systems (Petrişor et al. 2010). combined methodologies used in similar studies (Petrişor et al. Several studies on assessing land cover and use changes based 2010; Ianoş et al. 2011; Petrişor 2012a, b; Petrişor et al. 2014). on CORINE data were carried out in Romania. The study carried Essentially, the idea consists of assessing changes grouped by out by Petrişor (2012a) assessed all types of changes occurred underlying causes or transitional dynamics, and then analyzed in Romania during 1990–2000 and 2000–2006 by their underly- their spatial distribution, mapping it against specific features or ing cause, using a different classification. The results indicated generalizing it via spatial interpolation, based on the size and that the most important phenomena were several antagonistic spatial distribution of parcels affected by each type individually. phenomena, affecting forests (afforestation and reforestation In the previous studies, transitional dynamics were defined dif- vs. deforestation), agriculture (agricultural development vs. ferently, based on the particular interest. Here, the classification agricultural abandonment) and urban areas (urbanization vs. is fine-tuned, to account for some ideas developed during the urban restructuring); there were two important conclusions. Land Use and Cover Changes Commission of the International One the one hand, these phenomena characterized transition Geographical Union Symposium held in Bucharest and Braşov, economies, and on the other hand they indicated the lack of Romania (June 23–26, 2014), such as differentiating between the a controlled development (development and decline affected extensive and intensive development of agriculture. different parcels, suggesting that the initiative of development Several data sets were used for the analyses. Land use and occurred elsewhere instead of helping out a declining area). cover changes were examined based on the two CORINE (abbre- A similar study was carried out in greater detail, but only over viation of ‘Coordination of Information on the Environment’) a part of Romania (the North-Eastern Region of Development), datasets freely available from the European Environment Agency and using a different classification, by Petrişor et al. (2014). (EEA) for two periods, 1990–2000 (http://www.eea.europa.eu/ Furthermore, the findings were correlated with socio-economic data-and-maps/data/corine-land-cover-changes-clc1990-clc2000- issues characteristic to the region. The results indicated that 100-m-version-12-2009) and 2000–2006 (http://www.eea.europa. urbanization, afforestation and reforestation vs. deforestation, eu/data-and-maps/data/corine-land-cover-3). The boundaries of and development vs. abandonment of agriculture were the main European countries, including Romania, were derived from drivers of change, suggesting again that spatial development was the dataset included with ArcView GIS 3.X; CORINE subsets uncontrolled/unplanned (e.g., the agriculture was developed were clipped by the Romanian boundaries and projected unto over previously forested areas), and characteristic to developing Stereo 1970 (EPSG 31700/Dealul Piscului 1970 datum), the countries. coordinate reference system used in Romania. For each data Finally, three other studies were focused on the urban set, the transitional dynamics were assessed based on the status regions: Petrişor et al. (2010) looked at three phenomena affect- of each parcel in the beginning and ending period. Separate ing urban areas during 1990–2000 – urban development, urban analyses were run for 1990–2000 and 2000–2006. Several types restructuring, and de-urbanization, using spatial interpolation of changes were identified; they were classified as land cover to pinpoint the areas mostly affected by each phenomenon indi- changes (LC) if the level 1 class modified during the two periods vidually. Ianoş et al. (2011) looked again at the urban areas, tying and land use changes (LU) if transformations occurred at the the urbanization process to a decrease in the level of primary third level. Given that the period 1990–2000 is longer than the

29 UKRAINE UKRAINE

HUNGARY MOLDOVA HUNGARY MOLDOVA

SERBIA SERBIA

Deforestation (90—00) Deforestation (90—00) Deforestation (00—06) Deforestation (00—06) Urban growth (90—00) Urban growth (90—00) Urban growth (00—06) Urban growth (00—06) Afforestation/reforestation (90—00) Afforestation/reforestation (90—00) Afforestation/reforestation (00—06) BULGARIA Afforestation/reforestation (00—06) BULGARIA Abandonment of agriculture (90—00) Abandonment of agriculture (90—00) Abandonment of agriculture (00—06) Abandonment of agriculture (00—06) Intensive development of agriculture (90—00) 0 100 200 km Intensive development of agriculture (90—00) 0 100 200 km Extensive development of agriculture (90—00) Extensive development of agriculture (90—00)

Fig. 1 — Main transitional dynamics during 1990—2006 in Romania Fig. 2 — Main transitional dynamics during 1990—2006 in Romania by elevation (yellow shades). by natural protected areas (yellow).

Ecological regions Carpathian montane coniferous forests UKRAINE Central European mixed forests UKRAINE East European forest steppe Biogeographical regions Pannonian mixed forests Alpine MOLDOVA Balkan mixed forests MOLDOVA Black sea Pontic steppe Continental Sea Pannonian Steppic HUNGARY HUNGARY

SERBIA SERBIA

Fig. 3 — Main transitional dynamics during 1990—2006 in Romania Fig. 4 — Main transitional dynamics during 1990—2006 in Romania by biogeographical region. by ecological region.

Extensive development of agriculture (90—00) Intensive development of agriculture (90—00) Abandonment of agriculture (90—00) Abandonment of agriculture (00—06) UKRAINE UKRAINE Afforestation/reforestation (90–00) Afforestation/reforestation (00–06) Urban growth (90—00) MOLDOVA HUNGARY MOLDOVA Urban growth (00—06) Deforestation (90—00) Deforestation (00—06) Soil Alisol Andosol Arenosol Cambisol Fluvisol Gleysol Greyzem Chernozem Histosol Kastanozem Leptosol Luvisol SERBIA Marsh Phaeozem Planosol Podzol Podzoluvisol Regosol SERBIA Solonchak Solonetz Town BULGARIA BULGARIA Vertisol Urban growth (90—00) Water body 0 100 200 km 0 100 200 km Unknown Urban growth (00—06)

Fig. 5 — Main transitional dynamics during 1990—2006 in Romania Fig. 6 — Distribution of urban growth during 1990—2006 in Romania by the distribution of soils. (parcels grown for visibility).

30 period 2000–2006 and corresponds to more political and social 2. Biogeographical and ecological regions were freely avail- unsettledness, several types of changes occurred only in this able from EEA (http://www.eea.europa.eu/data-and-maps/ period. Overall, the main transitional dynamics were defined as: data/biogeographical-regions-europe-1 and http://www.eea. europa.eu/data-and-maps/data/digital-map-of-european-eco- (A) Phenomena characteristic to both periods: logical-regions); both datasets were clipped by the Romanian 1. Abandonment of agriculture: LU transformation of class 1 boundaries and projected unto Stereo 1970. agricultural parcels into an inferior use (e.g., permanent crops 3. The soil coverage was derived from the European Soil Data- to pastures) base (ESDB), obtained by request from the Joint Research 2. Intensive development of agriculture: LU transformation of Center (JRC) (Panagos et al. 2012) – details are available at class 1 agricultural parcels into a superior use (e.g., pastures http://eusoils.jrc.ec.europa.eu/esdb_archive/ESDB/Index. to permanent crops) htm. The dataset for Romania, obtained by clipping the data 3. Extensive development of agriculture: LC transformation of clipped by the Romanian boundaries and projecting it unto other class (except for forested or natural) into agricultural Stereo 1970, used the Food and Agriculture Organization of land (e.g., urban to agricultural) the United Nations (FAO) 1990 classification – level 1. 4. Deforestation: LC transformation of forested parcels into 4. Romanian natural protected areas of national and interna- other classes (e.g., forest to built up) or LU transformation to tional interest form a subset derived by spatially joining all an inferior use (e.g., coniferous forest to transitional wood- the subsets freely available from the Romanian Ministry of land/shrubs) the Environment and Climate Change (http://www.mmediu. 5. Afforestation or reforestation: Dutcă and Abrudan (2010) ro/beta/domenii/protectia-naturii-2/arii-naturale-protejate/). consider that afforestation represents the transformation of The Romanian national system of protected areas is partially other land-uses into forest, or the increase of the canopy cov- compatible with the International Union for Conservation of erage over the 10% threshold through plantations or natural Nature classification, and the subsets included: (1) national regeneration, and reforestation is the re-establishment of for- parks (IUCN II) and natural parks (IUCN V); (2) scientific ests after a temporary condition leading to a decrease of the reserves (IUCN I), natural monuments (IUCN III) and natural canopy coverage below 10% due to a human-induced or natu- reserves (IUCN IV) – only reserves with an area exceeding ral phenomenon. In this study, afforestation and reforestation 5 ha were included for each class; (3) NATURA 2000 sites: were considered together as a LC transformation from other Special Protection Areas (SPAs) for birds, Special Areas of classes into forests or LU transformations within the forest/ Conservation (SACs) and Emerald Areas of Special Conser- natural class to a superior use (e.g., transitional woodland/ vation Interest (ASCIs); (4) Biosphere Reserves (Mand and shrubs to coniferous forest). This definition also accounts for Biosphere Program); (5) RAMSAR sites, obtained based on the colonization of abandoned agricultural parcels by forest their legal limits, corresponding to other categories. vegetation (Petrişor et al. 2014). 6. Floods: LC transformation of other classes into water (e.g., The maps are the result of two types of analyses: (1) overlaying agricultural to water) the distribution of each transitional dynamic against spatial clas- 7. Urban growth or sprawl: LC transformation of other classes sifications (elevation, biogeographical and ecological regions, (except for forest) into urban (e.g., agricultural to urban) distribution of soils, natural protected areas); (2) using the Geo- 8. Urban restructuring: LU transformations within the urban class statistical Analyst of ArcGIS to interpolate via ordinary kriging the centers of parcels affected by each transitional dynamic by (B) Phenomena occurring only during the first period: their size. Centers were obtained using the X-Tools extension of 9. Aridization: LC transformation of waters into another class, ArcView 3.X. The resulting contours, reflecting the intensity of or disappearance of vegetation (e.g., pastures into sandy each transitional dynamic, were overlaid, when appropriately, areas) against the elevation and/or protected areas, or simply mapped 10. Dams: LC transformation of wetlands into waters against the national boundaries. 11. Unknown transformations: defined as such in the CORINE changes data set. 3. Results and Discussion Nevertheless, not all of these changes were considered. The analyses were limited to the most important types, which through The findings are presented in the next 26 figures listed below. the spatial distribution (number of parcels affected and their Figures 1–5 describe the main transitional dynamics affecting area) allowed for depicting a certain spatial distribution through the Romanian territory during 1990–2000 and 2000–2006, spatial interpolation. These included abandonment of agricul- mapped against elevation (Fig. 1), natural protected areas (Fig. 2), ture, deforestation, afforestation or reforestation, urban growth biogeographical regions (Fig. 3), ecological regions (Fig. 4) and or sprawl and urban restructuring for both periods, and intensive soils (Fig. 5). Perhaps the clearest message is given by Fig. 1; and extensive development of agriculture for the first period only. the image shows that the most important changes were the In addition, we used several other datasets. deforestations occurring in the two northern groups of the Car- 1. Elevation was derived from the data freely available from the pathians (northeast and northwest) and the abandonment of Consultative Group on International Agricultural Research of agricultural land, especially in the southeast during 1990–2000. the Consortium for Spatial Information (http://srtm.csi.cgiar. Since most protected areas cover the Carpathians (Fig. 2), the org/SELECTION/inputCoord.asp), consisting of raster cells of land use and cover changes occurred near or even within these approximately 90 × 90 m. Each cell was reduced to each geo- areas (however, most areas were declared in 2007; the intense metrical center using the X-Tools extension of ArcView GIS 1990–2000 land use and cover changes occurred prior to the 3.X, and centers were interpolated using the Geostatistical declaration of most areas, but still raise questions related to Analyst of ArcGIS 9.X via ordinary kriging, obtaining 100m the establishment of such areas, when one of the conditions is elevation curves. the existence of pristine natural conditions). On a similar note,

31 Urban growth (90–00) Urban growth (00–06) 1 UKRAINE 1 UKRAINE 2 2 3 HUNGARY MOLDOVA 3 HUNGARY MOLDOVA 4 4

SERBIA SERBIA

BULGARIA BULGARIA

0 100 200 km 0 100 200 km

Fig. 7 — Density of urban growth during 1990—2000 in Romania Fig. 8 — Density of urban growth during 2000—2006 in Romania (darker shades indicate higher intensity). (darker shades indicate higher intensity).

Intensive development of agriculture (90—00) UKRAINE 1 UKRAINE 2 HUNGARY MOLDOVA 3 HUNGARY MOLDOVA 4

SERBIA SERBIA

BULGARIA BULGARIA Intensive development of agriculture (90—00) 0 100 200 km Extensive development of agriculture (90—00) 0 100 200 km

Fig. 9 — Development of agriculture during 1990—2000 in Romania Fig. 10 — Centers of intensive development of agriculture during 1990—2000 by elevation (parcels grown for visibility). in Romania by elevation.

Extensive development of agriculture (90—00) 1 UKRAINE UKRAINE 2 3 HUNGARY MOLDOVA HUNGARY MOLDOVA 4

SERBIA SERBIA

BULGARIA BULGARIA Abandonment of agriculture (90—00) 0 100 200 km Abandonment of agriculture (00—06) 0 100 200 km

Fig. 11 — Centers of extensive development of agriculture during 1990—2000 Fig. 12 — Agricultural abandonment during 1990—2006 in Romania by elevation in Romania by elevation. (parcels grown for visibility).

32 Abandonment of agriculture (90—00) Abandonment of agriculture (00—06) 1 UKRAINE 0 UKRAINE 2 1 3 HUNGARY MOLDOVA 2 HUNGARY MOLDOVA 4 3 4

SERBIA SERBIA

BULGARIA BULGARIA

0 100 200 km 0 100 200 km

Fig. 13 — Centers of agricultural abandonment during 1990—2000 in Romania Fig. 14 — Centers of agricultural abandonment during 2000—2006 in Romania by elevation. by elevation.

UKRAINE UKRAINE

HUNGARY MOLDOVA HUNGARY MOLDOVA

SERBIA SERBIA

BULGARIA BULGARIA Afforestation/reforestation (90—00) Afforestation/reforestation (90—00) Afforestation/reforestation (00—06) 0 100 200 km Afforestation/reforestation (00—06) 0 100 200 km

Fig. 15 — Afforestation/reforestation during 1990—2006 in Romania by elevation Fig. 16 — Afforestation/reforestation during 1990—2006 in Romanian protected areas (parcels grown for visibility). (parcels grown for visibility).

Afforestation/reforestation (90—00) Afforestation/reforestation (00—06) 0 UKRAINE 0 UKRAINE 1 1 2 HUNGARY MOLDOVA 2 HUNGARY MOLDOVA 3 3 4 4

SERBIA SERBIA

BULGARIA BULGARIA

0 100 200 km 0 100 200 km

Fig. 17 — Centers of afforestation/reforestation during 1990—2000 in Romania Fig. 18 — Centers of afforestation/reforestation during 2000—2006 in Romania by elevation. by elevation.

33 Afforestation/reforestation (90—00) Afforestation/reforestation (00—06) 0 UKRAINE 0 UKRAINE 1 1 2 HUNGARY MOLDOVA 2 HUNGARY MOLDOVA 3 3 4 4

SERBIA SERBIA

BULGARIA BULGARIA

0 100 200 km 0 100 200 km

Fig. 19 — Centers of afforestation/reforestation during 1990—2000 in Romania Fig. 20 — Centers of afforestation/reforestation during 2000—2006 in Romania by protected areas. by protected areas.

UKRAINE UKRAINE

HUNGARY MOLDOVA HUNGARY MOLDOVA

SERBIA SERBIA

BULGARIA BULGARIA Deforestation (90—00) Deforestation (90—00) Deforestation (00—06) 0 100 200 km Deforestation (00—06) 0 100 200 km

Fig. 21 — Deforestation during 1990—2006 in Romania by elevation Fig. 22 — Deforestation during 1990—2006 in Romania by protected areas (parcels grown for visibility). (parcels grown for visibility).

Deforestation (90—00) Deforestation (00—06) 0 UKRAINE 0 UKRAINE 1 1 2 HUNGARY MOLDOVA 2 HUNGARY MOLDOVA 3 3 4 4

SERBIA SERBIA

BULGARIA BULGARIA

0 100 200 km 0 100 200 km

Fig. 23 — Centers of deforestation during 1990—2000 in Romania by elevation. Fig. 24 — Centers of deforestation during 2000—2006 in Romania by elevation.

34 Deforestation (90—00) Deforestation (00—06) 0 UKRAINE 0 UKRAINE 1 1 2 HUNGARY MOLDOVA 2 HUNGARY MOLDOVA 3 3 4 4

SERBIA SERBIA

BULGARIA BULGARIA

0 100 200 km 0 100 200 km

Fig. 25 — Centers of deforestation during 1990—2000 in Romania by protected areas. Fig. 26 — Centers of deforestation during 2000—2006 in Romania by protected areas.

the mountains correspond to the alpine biogeographical region (west, south and east). Intensive development seems to charac- (Fig. 3) and Carpathian montane coniferous forests (Fig. 4); this terize mostly the western half of the country, while the eastern explains why these regions were mostly affected by changes. part – particularly the southeast (Dobrudja) is the home of both Last but not least, according to the FAO classification, most intensive and extensive development. The opposite transitional mountain forests are situated on cambisol (Fig. 5). dynamic is the abandonment of agriculture (Figs. 12–14). The particular case of urban growth is discussed below. In Figure 12 shows the raw distribution, while figures 13–14 the this study, a distinction was made between the growth (sprawl) kriging-based generalized distributions for 1990-2000 (Fig. 13) of cities, involving a transformation of other LC into urban, and and 2000–2006 (Fig. 14). The three images indicate that the restructuring, involving a LU change within the ‘urban/ built up’ south of Romania was mostly affected in all periods. Again, the class. Out of the two, only urban growth appeared to have been study carried out by Bălteanu et al. (2013) provides a reliable a significant transitional dynamic. Fig. 6 shows the overall distri- explanation: after the property restitution, land was fragmented, bution of areas affected by urban growth, exaggerating the size and many farmers were able at most to practice subsistence of parcels for a better visualization. The particular distributions agriculture. As a result, parcels were abandoned, and given the during 1990–2000 and 2000–2006, obtained by generalizing the fact that the area is prone to aridity (Prăvălie et al. 2013, 2014), phenomenon through spatial interpolation via ordinary kriging, significant land use and cover changes occurred. are shown in Fig. 7, respectively Fig. 8. Both images pinpoint Similarly, two antagonistic phenomena affected forests the same pattern; the south of the country was mostly affected (Fig. 15–26). The growth of forests was attributed to the two by urban growth, including the seaside and area around Bucha- transitional dynamics discussed by Dutcă and Abrudan (2010): rest (more evident during the first period – Fig. 7). Both figures afforestation and reforestation. Unfortunately, without field clearly indicate a center situated in the southwest of Romania data, this study was unable to ascertain the particular influence (Oltenia). This center might look strange at a first glance, par- of each of them. The joint raw distribution is shown in Fig. 15 ticularly because the area was affected by the de-urbanization (mapped against elevation) and Fig. 16 (mapped against the of former mining cities that lost their industrial function (Ianoş protected areas), and the kriging-based generalized distributions 2000). However, other authors provide possible explanations: are displayed in Figs. 17–18 (mapped against elevation for the Bălteanu et al. (2013) suggest that the post-communist restitu- periods 1990–2000 and 2000–2006) and 19–20 (mapped against tion of properties resulted in this area into an excessive frag- the protected areas for the periods 1990–2000 and 2000–2006). mentation of land, increasing the number of individual farms The images indicate that the phenomena acted mainly in the practicing subsistence agriculture. On the other hand, Bădiţă Carpathians and the eastern part (Moldavian plateau), and (2013) shows that many large cities of the region sprawled, and around the protected areas. However, the generalized distribu- the phenomenon was expanded even over the adjacent rural tions show a concentration in the southeast, especially during settlements. the second period. This is most likely a spurious result and must The agriculture was affected by two antagonistic phenom- be correlated with the findings about the agricultural areas; it is ena (Figs. 9–14). The development of agriculture (Figs. 9–11) very likely that abandoned agricultural lands were colonized by was visible only during 1990–2000; in this study, two different forest vegetation, as indicated by other studies (Agnoletti et al. constituents were distinguished: the extensive development of 2011; Blakesley 2006; Van Uytvanck 2009). While the interpreta- agriculture was defined as a LC indicating the expansion of tion of afforestation and reforestation is arguable, this study pro- agricultural land over other categories, and the intensive devel- vided clear evidence for deforestation (Figs. 21–26). Figs. 21–22 opment, as a LU change indicating an improvement in the status show the raw distribution mapped against elevation (Fig. 21) of agricultural parcels. The distribution of the two is shown in and protected areas (Fig. 22), while the kriging-based general- Fig. 9, and kriging-based generalizations are shown in Fig. 10 ized distributions are displayed in Figs. 23–24 (mapped against (intensive development) and 11 (extensive development). The elevation for the periods 1990–2000 and 2000–2006) and 25–26 figures indicate that agriculture developed in the plain areas (mapped against the protected areas for the periods 1990–2000

35 and 2000–2006). The images indicate that most deforestation References occurred in the eastern Carpathians, in the Danube Delta, in the central sub-Carpathians and in the south and north of Romania, AGNOLETTI, M., CARGNELLO, G., GARDIN, L., SANTORO, A., BAZZOFFI, P., SANSONE, L., PEZZA, L., BELFIORE, N. (2011): Traditional landscape even within and around the protected areas (even after their dec- and rural development: comparative study in three terraced areas in north- laration – Fig. 26). The massif deforestations in Romania have ern, central and southern Italy to evaluate the efficacy of GAEC standard been documented by Roman (2009), who showed that the forest 4.4 of cross compliance, Italian Journal of Agronomy 6(1): 121–139. restitution of 1990’s to private owners was the beginning point BĂDIŢĂ, A. (2013): Urban territorial dynamics and socio-economic changes of cuts resulting into the loss of 130,000 ha of forests within the in Craiova city, Forum geographic 12(2): 171–177. last decade (Măliguţa et al. 2009). BĂLTEANU, D., DRAGOTĂ, C.-S., POPOVICI, A., DUMITRAŞCU, M., KUCSI- There are two main limitations of the methodology used in CSA, G., GRIGORESCU, I. (2013): Land use and crop dynamics related to climate change signals during the post-communist period in the south this study. Oltenia, Romania, Proceedings of the Romanian Academy Series B 15(3): 1. The correct classification of the typology of transitional dynam- 265–278. ics varies based on the interest of the researcher. Sometimes, BLAKESLEY, D. (2006): Woodland Creation for Wildlife: a guide to creat- phenomena are clearly-cut (e.g., transformation of any class ing new woodland for wildlife in Kent and East Sussex, East Malling into a built up or urban area indicates the urbanization), but Research, Kent, UK. in other situations a transformation A → B can be arbitrarily DALE, V.H., EFROYMNSON, R.A., KLINE, K.L. (2011): The land use–climate classified depending on the biased focus on A or B; e.g., a change–energy nexus, Landscape Ecology 26(6): 755–773. DE LIMA, M.V.N. (2005): IMAGE2000 and CLC2000 Products and Methods, transformation of a forest into agricultural land can be seen Land Management Unit, Joint Research Centre, Institute for Environment as a deforestation, if the focus is set on the forest, or develop- and Sustainability, Ispra, Italy, 150 pp. ment of the agriculture, if the focus is set on the endpoint. DUTCĂ, I., ABRUDAN, I.V. (2010): Estimation of forest land-cover change in Furthermore, the exact status of a transformation cannot be Romania, between 1990 and 2006, Bulletin of the Transylvania Univer- always inferred from a desk study, and field work might be sity of Braşov Series II: Forestry, Wood Industry, and Agricultural Food needed to determine the correct classification; a transfor- Engineering 52: 33–36. mation of agricultural land into forest can occur because a IANOŞ, I. (2000): Romanian towns: from extensive industrialisation to rurali- sation?, The Geographical Journal of Korea 34: 125–136. forest was planted of because the forest vegetation naturally IANOŞ, I., PETRIŞOR, A.-I., STOICA, I.V., SÂRBU, C.N., ZAMFIR, D., CER- colonized an abandoned agricultural land. CLEUX, A.L. (2011): The different consuming of primary eco-energies and 2. The kriging technique creates generalizing areas from their degradation in territorial systems, Carpathian Journal of Earth and point data, artificially creating the illusion of a continuum. Environmental Sciences 6(2): 251–260. Moreover, the limits of these surfaces do not have a precise JANSEN, L.J.M. (2007): Harmonization of land use class sets to facilitate geographical relevance, as no one could see them as true compatibility and comparability of data across space and time, Journal boundaries in the field (Petrişor et al. 2010, 2014). of Land Use Science 1(2-4): 127–156. JENSEN, J.R. (2000): Remote Sensing of the Environment. An Earth Resource 3. Last but not least, other limitations of using CORINE data Perspective, Prentice Hall, Upper Saddle River, New Jersey, 544 pp. have been pointed out by studies carried by Jansen (2007), MĂLIGUŢA, S.A., CÎRJA, L., BĂGHINĂ, N. (2009): The consequences of defor- Pelorosso et al. (2009), Verburg et al. (2011), and Petrişor et al. estation on the environment, Research Journal of Agricultural Science (2014). Some of the changes could be a spurious consequence 41(3): 92–95. of misclassification or changing classification schemes or PANAGOS, P., VAN LIEDEKERKE, M., JONES, A., MONTANARELLA, L. resolutions in the process of producing the data from satellite (2012): European Soil Data Centre: Response to European policy support images. and public data requirements, Land Use Policy 29(2): 329–338. PELOROSSO, R., LEONE, A., BOCCIA, L. (2009): Land cover and land use change in the Italian central Apennines: A comparison of assessment methods, Applied Geography 29(1): 35–48. 4. Conclusions PETRIŞOR, A.-I., GRIGOROVSCHI, M., MEIŢĂ, V., SIMION-MELINTE, C.-P. (2014): Long-term environmental changes analysis using CORINE data, This study employed the Geographical Information Systems and Environmental Engineering and Management Journal 13(4): 847–860. geostatistical approaches to look at the spatial distribution of land PETRIŞOR, A.-I. (2012a): Dynamics of the environmental transformation use and cover changes in post-communist Romania, correlating processes during 1990–2006 in Romania reflected by land cover and use changes, Present Environment and Sustainable Development 6(1): them with other spatial information. The results indicate that the 353–365. most prominent transitional dynamics were the abandonment of PETRIŞOR, A.-I. (2012b): Land cover and land use analysis of urban growth agriculture, deforestation, afforestation or reforestation, urban in Romania, Human Geographies 6(1): 47–51. growth or sprawl and urban restructuring during 1990–2006, PETRIŞOR, A.-I., IANOŞ, I., TĂLÂNGĂ, C. (2010): Land cover and use changes and intensive and extensive development of agriculture during focused on the urbanization processes in Romania, Environmental Engi- 1990–2000. These phenomena affected especially the mountain neering and Management Journal 9(6): 765–771. areas, including natural protected areas, and the agricultural PRĂVĂLIE, R., PEPTENATU, D., SÎRODOEV, I. (2013): The impact of climate change on the dynamics of agricultural systems in South-Western sector of economy, and are generally characteristic to transition Romania, Carpathian Journal of Earth and Environmental Sciences 8(3): economies. In the southern part of Romania, their effects can 175–186. be aggravated by the natural aridity characteristic to the area. PRĂVĂLIE, R., SÎRODOEV, I., PEPTENATU, D. (2014): Changes in the forest ecosystems in areas impacted by aridization in South-Western Romania, Journal of Environmental Health Science and Engineering 12(1): 2. ROMAN, T. (2009): The Forest of Romania: a Social-Economic’s Dramma, Theoretical and Applied Economics 6: 57–64. VAN UYTVANCK, J., (2009): The role of large herbivores in woodland regeneration patterns, mechanisms and processes, Research Institute for Nature and Forest, Brussels, Belgium. VERBURG, P.H., NEUMANN, K., NOLL, L. (2011): Challenges in using land use and land cover data for global change studies, Global Change Biology 17(2): 974–989.