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Dr. Andrei Dornik
West University of Timisoara

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0 Environmental Science
0 Physical Geography
0 Remote Sensing
0 Geographical information systems
0 Digital Soil Mapping

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Journal article
Published: 20 August 2021 in Water
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One of the most critical challenges in species distribution modelling is testing and validating various digitally derived environmental predictors (e.g., remote-sensing variables, topographic variables) by field data. Therefore, here we aimed to explore the value of soil properties in the spatial distribution of four European indigenous crayfish species. A database with 473 presence and absence locations in Romania for Austropotamobius bihariensis, A. torrentium, Astacus astacus and Pontastacus leptodactylus was used in relation to eight digitalised soil properties. Using random forest modelling, we found a preference for dense soils with lower coarse fragments content together with deeper sediment cover and higher clay values for A. astacus and P. leptodactylus. These descriptors trigger the need for cohesive soil river banks as the microenvironment for building their burrows. Conversely, species that can use banks with higher coarse fragments content, the highland species A. bihariensis and A. torrentium, prefer soils with slightly thinner sediment cover and lower density while not influenced by clay/sand content. Of all species, A. astacus was found related with higher erosive soils. The value of these soil-related digital descriptors may reside in the improvement of approaches in crayfish species distribution modelling to gain adequate conservation measures.

ACS Style

Andrei Dornik; Mihaela Constanța Ion; Marinela Adriana Chețan; Lucian Pârvulescu. Soil-Related Predictors for Distribution Modelling of Four European Crayfish Species. Water 2021, 13, 2280 .

AMA Style

Andrei Dornik, Mihaela Constanța Ion, Marinela Adriana Chețan, Lucian Pârvulescu. Soil-Related Predictors for Distribution Modelling of Four European Crayfish Species. Water. 2021; 13 (16):2280.

Chicago/Turabian Style

Andrei Dornik; Mihaela Constanța Ion; Marinela Adriana Chețan; Lucian Pârvulescu. 2021. "Soil-Related Predictors for Distribution Modelling of Four European Crayfish Species." Water 13, no. 16: 2280.

Journal article
Published: 07 December 2020 in Remote Sensing
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Our study highlights the usefulness of very high resolution (VHR) images to detect various types of disturbances over permafrost areas using three example regions in different permafrost zones. The study focuses on detecting subtle changes in land cover classes, thermokarst water bodies, river dynamics, retrogressive thaw slumps (RTS) and infrastructure in the Yamal Peninsula, Urengoy and Pechora regions. Very high-resolution optical imagery (sub-meter) derived from WorldView, QuickBird and GeoEye in conjunction with declassified Corona images were involved in the analyses. The comparison of very high-resolution images acquired in 2003/2004 and 2016/2017 indicates a pronounced increase in the extent of tundra and a slight increase of land covered by water. The number of water bodies increased in all three regions, especially in discontinuous permafrost, where 14.86% of new lakes and ponds were initiated between 2003 and 2017. The analysis of the evolution of two river channels in Yamal and Urengoy indicates the dominance of erosion during the last two decades. An increase of both rivers’ lengths and a significant widening of the river channels were also observed. The number and total surface of RTS in the Yamal Peninsula strongly increased between 2004 and 2016. A mean annual headwall retreat rate of 1.86 m/year was calculated. Extensive networks of infrastructure occurred in the Yamal Peninsula in the last two decades, stimulating the initiation of new thermokarst features. The significant warming and seasonal variations of the hydrologic cycle, in particular, increased snow water equivalent acted in favor of deepening of the active layer; thus, an increasing number of thermokarst lake formations.

ACS Style

Florina Ardelean; Alexandru Onaca; Marinela-Adriana Chețan; Andrei Dornik; Goran Georgievski; Stefan Hagemann; Fabian Timofte; Oana Berzescu. Assessment of Spatio-Temporal Landscape Changes from VHR Images in Three Different Permafrost Areas in the Western Russian Arctic. Remote Sensing 2020, 12, 3999 .

AMA Style

Florina Ardelean, Alexandru Onaca, Marinela-Adriana Chețan, Andrei Dornik, Goran Georgievski, Stefan Hagemann, Fabian Timofte, Oana Berzescu. Assessment of Spatio-Temporal Landscape Changes from VHR Images in Three Different Permafrost Areas in the Western Russian Arctic. Remote Sensing. 2020; 12 (23):3999.

Chicago/Turabian Style

Florina Ardelean; Alexandru Onaca; Marinela-Adriana Chețan; Andrei Dornik; Goran Georgievski; Stefan Hagemann; Fabian Timofte; Oana Berzescu. 2020. "Assessment of Spatio-Temporal Landscape Changes from VHR Images in Three Different Permafrost Areas in the Western Russian Arctic." Remote Sensing 12, no. 23: 3999.

Journal article
Published: 07 December 2020 in Journal of Environmental Management
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The world's largest network of protected areas (PAs), Natura 2000, is facing different types of disturbances and pressures, however, it still remains unclear the impact they have on the conservation status of sites. Remote sensing big data analysis and satellite data were used to quantify dynamics of the dominant land cover category, landscape structure, and vegetation greenness, as indicators of conservation status, as well as drivers of change, between 2000 and 2018, within each Natura 2000 protected area, across the entire European Union. Our results show that the majority of sites are ‘favourable’ on natural land cover range and areas, but heading to ‘unfavourable’ status regarding the landscape structure, while an alarmingly high number of sites experience both net loss of the dominant land cover type and degradation of landscape structure, labeled consequently as having an ‘unfavourable’ conservation status. The results also showed high differences between biogeographic regions and countries, with an extremely low number of sites suffering dramatic changes to other dominant land cover types, mainly among grasslands. Mediterranean region showed a high net forest increase (mainly extension of existing forests) as well as insignificant changes of landscape fragmentation and diversity (predominantly in Greece, Spain and, Italy), related to the intensification of forest planting, and to a high loss of grassland area and cropland (land abandonment). High net forest gain, but increasing landscape fragmentation, was observed in the Continental region (mainly in Bulgaria, Poland, Germany and, Italy), suggesting that forest developed in numerous new smaller patches, due to the development of invasive species through natural processes (agricultural land abandonment) and natural system modifications. The Alpine region also showed a low positive net forest change, but with significant dynamics of gains due to reducing of agricultural activities and human disturbances, and losses due to natural catastrophes such as natural fires, storms, avalanches or landslides. Contrarily, the Boreal and Atlantic regions recorded considerable net forest loss during the analyzed period, caused mainly by the occurrence of natural catastrophes, natural biotic and abiotic processes (erosion, parasitism, diseases), and the increase of forestry clearance. These results show the high potential of moderate resolution remote sensing big data in assessing PAs, even more as higher spatial and temporal resolution satellite data are continuously emerging.

ACS Style

Marinela Adriana Cheţan; Andrei Dornik. 20 years of landscape dynamics within the world's largest multinational network of protected areas. Journal of Environmental Management 2020, 280, 111712 .

AMA Style

Marinela Adriana Cheţan, Andrei Dornik. 20 years of landscape dynamics within the world's largest multinational network of protected areas. Journal of Environmental Management. 2020; 280 ():111712.

Chicago/Turabian Style

Marinela Adriana Cheţan; Andrei Dornik. 2020. "20 years of landscape dynamics within the world's largest multinational network of protected areas." Journal of Environmental Management 280, no. : 111712.

Journal article
Published: 09 June 2020 in Remote Sensing
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High-latitude regions are a hot spot of global warming, but the scarce availability of observations often limits the investigation of climate change impacts over these regions. However, the utilization of satellite-based remote sensing data offers new possibilities for such investigations. In the present study, vegetation greening, vegetation moisture and lake distribution derived from medium-resolution satellite imagery were analyzed over the Pechora catchment for the last 35 years. Here, we considered the entire Pechora catchment and the Pechora Delta region, located in the northern part of European Russia, and we investigated the vegetation and lake dynamics over different permafrost zones and across the two major biomes, taiga, and tundra. We also evaluated climate data records from meteorological stations and re-analysis data to find relations between these dynamics and climatic behavior. Considering the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Moisture Index (NDMI) in the summer, we found a general greening and moistening of the vegetation. While vegetation greenness follows the evolution of summer air temperature with a delay of one year, the vegetation moisture dynamics seems to better concur with annual total precipitation rather than summer precipitation, and also with annual snow water equivalent without lag. Both NDVI and NDMI show a much higher variability across discontinuous permafrost terrain compared to other types. Moreover, the analyses yielded an overall decrease in the area of permanent lakes and a noticeable increase in the area of seasonal lakes. While the first might be related to permafrost thawing, the latter seems to be connected to an increase of annual snow water equivalent. The general consistency between the indices of vegetation greenness and moisture based on satellite imagery and the climate data highlights the efficacy and reliability of combining Landsat satellite data, ERA-Interim reanalysis and meteorological data to monitor temporal dynamics of the land surface in Arctic areas.

ACS Style

Marinela-Adriana Cheţan; Andrei Dornik; Florina Ardelean; Goran Georgievski; Stefan Hagemann; Vladimir Romanovsky; Alexandru Onaca; Dmitry Drozdov. 35 Years of Vegetation and Lake Dynamics in the Pechora Catchment, Russian European Arctic. Remote Sensing 2020, 12, 1863 .

AMA Style

Marinela-Adriana Cheţan, Andrei Dornik, Florina Ardelean, Goran Georgievski, Stefan Hagemann, Vladimir Romanovsky, Alexandru Onaca, Dmitry Drozdov. 35 Years of Vegetation and Lake Dynamics in the Pechora Catchment, Russian European Arctic. Remote Sensing. 2020; 12 (11):1863.

Chicago/Turabian Style

Marinela-Adriana Cheţan; Andrei Dornik; Florina Ardelean; Goran Georgievski; Stefan Hagemann; Vladimir Romanovsky; Alexandru Onaca; Dmitry Drozdov. 2020. "35 Years of Vegetation and Lake Dynamics in the Pechora Catchment, Russian European Arctic." Remote Sensing 12, no. 11: 1863.

Journal article
Published: 01 December 2018 in Pedosphere
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ACS Style

Andrei Dornik; Lucian Dragut; Petru Urdea. Classification of Soil Types Using Geographic Object-Based Image Analysis and Random Forests. Pedosphere 2018, 28, 913 -925.

AMA Style

Andrei Dornik, Lucian Dragut, Petru Urdea. Classification of Soil Types Using Geographic Object-Based Image Analysis and Random Forests. Pedosphere. 2018; 28 (6):913-925.

Chicago/Turabian Style

Andrei Dornik; Lucian Dragut; Petru Urdea. 2018. "Classification of Soil Types Using Geographic Object-Based Image Analysis and Random Forests." Pedosphere 28, no. 6: 913-925.

Journal article
Published: 01 August 2018 in Applied Geography
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ACS Style

Marinela Adriana Cheţan; Andrei Dornik; Petru Urdea. Analysis of recent changes in natural habitat types in the Apuseni Mountains (Romania), using multi-temporal Landsat satellite imagery (1986–2015). Applied Geography 2018, 97, 161 -175.

AMA Style

Marinela Adriana Cheţan, Andrei Dornik, Petru Urdea. Analysis of recent changes in natural habitat types in the Apuseni Mountains (Romania), using multi-temporal Landsat satellite imagery (1986–2015). Applied Geography. 2018; 97 ():161-175.

Chicago/Turabian Style

Marinela Adriana Cheţan; Andrei Dornik; Petru Urdea. 2018. "Analysis of recent changes in natural habitat types in the Apuseni Mountains (Romania), using multi-temporal Landsat satellite imagery (1986–2015)." Applied Geography 97, no. : 161-175.

Articles
Published: 12 January 2016 in International Journal of Geographical Information Science
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Sampling efforts are constrained by limited availability of resources. Therefore, methods to reduce the number of samples, while still achieving reasonable accuracy are needed. Land-surface segmentation (LSS) has proven a powerful technique to partition digital elevation models (DEMs) and their derivatives into relatively homogeneous areas, which can be further employed as support in soil sampling. Though topography is one of the main soil forming factors, a robust assessment of the potential of this technique to digital soil mapping (DSM) is still missing. In this study, we aimed at evaluating the potential of LSS in stratifying a landscape into relatively homogeneous areas, which can be used as strata for guiding the selection of sampling points in DSM. The experiments were carried out in two study areas where soil samples were available. Land-surface derivatives were derived from DEMs and segmented with a tool based on the multiresolution segmentation algorithm, into objects considered as homogeneous soil-landscape divisions. Thus, one sample was randomly selected within each segment from the existing sample data, based on which predictions of soil classes/sub-orders and properties, i.e. soil texture and A-horizon thickness, were made. Results were compared with predictions based on simple random sampling (SRS) and conditioned Latin hypercube (cLHS). The segmentation-based sampling (SBS) scheme performed better than SRS and cLHS schemes in predicting the A-horizon thickness, soil texture fractions and soil classes, showing a high potential of LSS in stratifying a landscape for the purposes of DSM. The novelty of this study is in the way strata are constructed, rather than in the sampling design itself. Further research is needed to demonstrate the value of a SBS design for practical use. The analyses presented here further highlight the importance of considering locally adaptive techniques in optimization of sampling schemes and predictions of soil properties.

ACS Style

Lucian Drăguţ; Andrei Dornik. Land-surface segmentation as a method to create strata for spatial sampling and its potential for digital soil mapping. International Journal of Geographical Information Science 2016, 30, 1359 -1376.

AMA Style

Lucian Drăguţ, Andrei Dornik. Land-surface segmentation as a method to create strata for spatial sampling and its potential for digital soil mapping. International Journal of Geographical Information Science. 2016; 30 (7):1359-1376.

Chicago/Turabian Style

Lucian Drăguţ; Andrei Dornik. 2016. "Land-surface segmentation as a method to create strata for spatial sampling and its potential for digital soil mapping." International Journal of Geographical Information Science 30, no. 7: 1359-1376.

Journal article
Published: 01 January 2016 in Soil Research
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Soil information covering regional, continental, or even global scales is needed for modelling, prediction, or estimation of environmental risks, crop yield estimation, carbon stock estimation, or research on climate change. This study aims to evaluate the extent to which geographic object-based image analysis and expert-knowledge, using digital maps of climate, topography, vegetation, and geology as soil covariates (GEOBIA approach), might model and reproduce a conventional soil map at a scale 1:1000000 in the south-west of Romania. The environmental variables were segmented with a region-growing algorithm, the resulting objects being subsequently classified into soil types using expert-knowledge fuzzy classification rules. To assess the geographical support of classification for the modelling of a conventional soil map, we quantitatively evaluated a pixel-based soil map produced using the same expert-knowledge classification rules, as an alternative to an object-based approach. To evaluate the source of soil information, we quantitatively assessed the map of the World Reference Base soil groups produced by the data-driven global soil information system, SoilGrids, as an alternative to expert-knowledge rules. The digital soil maps were quantitatively compared with the conventional soil map. Evidence was provided that the similarity of soil types with the conventional soil map was higher when the modelling was conducted through GEOBIA approach (general similarity of 65% and fuzzy kappa index of 0.58) than the pixel-based approach and SoilGrids. Furthermore, the results showed that the SoilGrids map achieved higher similarity to conventional soil map than the pixel-based soil map. When tested in another area, without modification to the knowledge-based methodologies, the same conclusions could be drawn, although the two maps recorded lower similarity values. The overall reduction in similarity values is explained by a high variability of some soil types under different environmental conditions.

ACS Style

Andrei Dornik; Lucian Drăguţ; Petru Urdea. Knowledge-based soil type classification using terrain segmentation. Soil Research 2016, 54, 809 -823.

AMA Style

Andrei Dornik, Lucian Drăguţ, Petru Urdea. Knowledge-based soil type classification using terrain segmentation. Soil Research. 2016; 54 (7):809-823.

Chicago/Turabian Style

Andrei Dornik; Lucian Drăguţ; Petru Urdea. 2016. "Knowledge-based soil type classification using terrain segmentation." Soil Research 54, no. 7: 809-823.