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In our work, we sought to answer whether we find differences among the various zones of an oxbow lake with different land uses based on physico-chemical variables and dominant algal plankton species. The two ends of the oxbow lake are bordered by settlements, and near them there are open water areas where fishing is the major utilization form. Between the two open water areas we find a protected area with a large aquatic plant coverage and two transition zones towards the open water areas. The oxbow lake receives periodic water replenishment only at one end from one of the open water areas. During summer—due to the lack of rain—the water of the oxbow lake is used for irrigation in the surrounding arable land, so the water level fluctuation can be significant in the riverbed. Our study was performed within a vegetation period of spring, early summer, mid-summer, and fall. In connection with the ecological classification of a smaller water body, studies on the physical and chemical properties of the water and the composition of the algal plankton are usually carried out in few places and relatively infrequently. The characteristics of a water body are also influenced by seasonal changes, which can be the changes in the extent of vegetation coverage, the way land is used and the possibility of water replenishment, to which the algal community usually responds with changes. Based on our study, it can be said that even in a relatively small water body, we found a large differences based on the chemical and physical properties of the water and the characteristic algal species. Open water zones, areas with large macrovegetation coverage, and the transition zones were separated from each other.
Majd Muwafaq Yaqoob; Csaba Berta; László József Szabó; György Dévai; Szilárd Szabó; Sándor Alex Nagy; István Bácsi; Alexandra Simon; János Nagy; Imre Somlyai; Éva Ács; István Grigorszky. Changes in Algal Plankton Composition and Physico-Chemical Variables in a Shallow Oxbow Lake. Water 2021, 13, 2339 .
AMA StyleMajd Muwafaq Yaqoob, Csaba Berta, László József Szabó, György Dévai, Szilárd Szabó, Sándor Alex Nagy, István Bácsi, Alexandra Simon, János Nagy, Imre Somlyai, Éva Ács, István Grigorszky. Changes in Algal Plankton Composition and Physico-Chemical Variables in a Shallow Oxbow Lake. Water. 2021; 13 (17):2339.
Chicago/Turabian StyleMajd Muwafaq Yaqoob; Csaba Berta; László József Szabó; György Dévai; Szilárd Szabó; Sándor Alex Nagy; István Bácsi; Alexandra Simon; János Nagy; Imre Somlyai; Éva Ács; István Grigorszky. 2021. "Changes in Algal Plankton Composition and Physico-Chemical Variables in a Shallow Oxbow Lake." Water 13, no. 17: 2339.
The availability of aerial and satellite imageries has greatly reduced the costs and time associated with gully mapping, especially in remote locations. Regardless, accurate identification of gullies from satellite images remains an open issue despite the amount of literature addressing this problem. The main objective of this work was to investigate the performance of support vector machines (SVM) and random forest (RF) algorithms in extracting gullies based on two resampling methods: bootstrapping and k-fold cross-validation (CV). In order to achieve this objective, we used PlanetScope data, acquired during the wet and dry seasons. Using the Normalized Difference Vegetation Index (NDVI) and multispectral bands, we also explored the potential of the PlanetScope image in discriminating gullies from the surrounding land cover. Results revealed that gullies had significantly different (p< 0.001) spectral profiles from any other land cover class regarding all bands of the PlanetScope image, both in the wet and dry seasons. However, NDVI was not efficient in gully discrimination. Based on the overall accuracies, RF’s performance was better with CV, particularly in the dry season, where its performance was up to 4% better than the SVM’s. Nevertheless, class level metrics (omission error: 11.8%; commission error: 19%) showed that SVM combined with CV was more successful in gully extraction in the wet season. On the contrary, RF combined with bootstrapping had relatively low omission (16.4%) and commission errors (10.4%), making it the most efficient algorithm in the dry season. The estimated gully area was 88 ± 14.4 ha in the dry season and 57.2 ± 18.8 ha in the wet season. Based on the standard error (8.2 ha), the wet season was more appropriate in gully identification than the dry season, which had a slightly higher standard error (8.6 ha). For the first time, this study sheds light on the influence of these resampling techniques on the accuracy of satellite-based gully mapping. More importantly, this study provides the basis for further investigations into the accuracy of such resampling techniques, especially when using different satellite images other than the PlanetScope data.
Kwanele Phinzi; Dávid Abriha; Szilárd Szabó. Classification Efficacy Using K-Fold Cross-Validation and Bootstrapping Resampling Techniques on the Example of Mapping Complex Gully Systems. Remote Sensing 2021, 13, 2980 .
AMA StyleKwanele Phinzi, Dávid Abriha, Szilárd Szabó. Classification Efficacy Using K-Fold Cross-Validation and Bootstrapping Resampling Techniques on the Example of Mapping Complex Gully Systems. Remote Sensing. 2021; 13 (15):2980.
Chicago/Turabian StyleKwanele Phinzi; Dávid Abriha; Szilárd Szabó. 2021. "Classification Efficacy Using K-Fold Cross-Validation and Bootstrapping Resampling Techniques on the Example of Mapping Complex Gully Systems." Remote Sensing 13, no. 15: 2980.
Irrigation is a key factor for different physiological aspects of fruit trees. Therefore, such irrigation protocols that can save water consumption during irrigation and maintain fruit trees productivity are an essential goal especially under semiarid climate conditions. The aim of this 3-year apricot study was to investigate the effect of four deficit irrigation (DI) treatments (control, moderate regulated deficit irrigation: RDIm, severe RDI: RDIs and continuous DI: CDI) on 15 tree physiological properties (chilling requirement—CR, heat requirement—HR, days from end—dormancy until fruit harvest—DEDFH, sum of growing degree days—sGDD, total number of buds—TNB, number of flower buds—NFB, number of vegetative buds—NVB, starting date of flowering—SDF, number of opened flower buds—NOFB, flower bud abscission—FBA, fruit set—FS, seasonal vegetative growth—SVG, fruit number per tree—FNT, fruit weight—FW, fruit yield—FY), and on two tree chemical properties (total soluble carbohydrates—TSC and total proline content—TPC) on apricot cultivars ‘Ninfa’ and ‘Canino’ in Egypt. Results showed that both DI treatments and cultivars significantly influenced the values of CR, HR, TNB, SDF, NOFB, FS, SVG, FNT, FY, TSC, and TPC. Values of FBA were significantly affected by years and DI treatments, while sGDD by years and cultivars. Values of DEDFH, NFB, and FW were significantly influenced only by cultivars, while NVB only by DI treatments. The RDIm treatment gave the most acceptable values for most measured properties compared to the fully irrigated control treatment. Prediction based model analysis demonstrated that generalized linear models (GLMs) can be predictors for the measured tree properties in the DI treatments. The best goodness-of-fit of the predicted GLMs was reached for HR, NOFB, FS, SVG, FNT, TSC, and TPC. In all the four DI treatments, 22 pair-variables (TNB versus (vs.) NFB, TNB vs. NOFB, TNB vs. NOFB, NFB vs. NOFB, NFB vs. FNT, NFB vs. FY, NFB vs. FW, NOFB vs. SVG, NOFB vs. FNT, NOFB vs. FY, FS vs. FNT, FS vs. FY, SVG vs. FNT, SVG vs. FY, SVG vs. TSC, FNT vs. FY, FY vs. FW, CR vs. TSC, HR vs. TNB, HR vs. NFB, HR vs. FNT, HR vs. FY, and NOFB vs. FBA) correlated significantly in Pearson correlation and regression analyses. Principal component analyses explained 82% of the total variance and PC1, PC2, and PC3 explained 23, 21, and 15% of the total variance and correlated with the HR, TNB, FS, FNT and FY; FBA, SVG, TSC, and TPC; and NFB, NVB and NOFB, respectively, indicating strong connections among tree physiological and chemical properties. In conclusion, DI techniques using moderate water deficits can be managed successfully in apricot production under semiarid Mediterranean climate conditions such as the one in Egypt.
Ahmed Ezzat; Abdel-Moety Salama; Szilárd Szabó; Arshad Yaseen; Bianka Molnár; Imre Holb. Deficit Irrigation Strategies on Tree Physiological and Chemical Properties: Treatment Effects, Prediction Based Model Analyses and Inter-Correlations. Agronomy 2021, 11, 1361 .
AMA StyleAhmed Ezzat, Abdel-Moety Salama, Szilárd Szabó, Arshad Yaseen, Bianka Molnár, Imre Holb. Deficit Irrigation Strategies on Tree Physiological and Chemical Properties: Treatment Effects, Prediction Based Model Analyses and Inter-Correlations. Agronomy. 2021; 11 (7):1361.
Chicago/Turabian StyleAhmed Ezzat; Abdel-Moety Salama; Szilárd Szabó; Arshad Yaseen; Bianka Molnár; Imre Holb. 2021. "Deficit Irrigation Strategies on Tree Physiological and Chemical Properties: Treatment Effects, Prediction Based Model Analyses and Inter-Correlations." Agronomy 11, no. 7: 1361.
In both arid and semiarid regions, erosion by wind is a significant threat against sustainability of natural resources. The objective of this work was to investigate the direct impact of various soil moisture levels with soil texture and organic matter on soil crust formation and evaporation. Eighty soil samples with different texture (sand: 19, loamy sand: 21, sandy loam: 26, loam: 8, and silty loam: 6 samples) were collected from the Nyírség region (Eastern Hungary). A wind tunnel experiment was conducted on four simulated irrigation rates (0.5, l.0, 2.0, and 5.0 mm) and four levels of wind speeds (4.5, 7.8, 9.2, and 15.5 m s−1). Results showed that watering with a quantity equal to 5 mm rainfall, with the exception of sandy soils, provided about 5–6 h protection against wind erosion, even in case of a wind velocity as high as 15.5 m s−1. An exponential connection was revealed between wind velocities and the times of evaporation (R2 = 0.88–0.99). Notably, a two-way ANOVA test revealed that both wind velocity (p < 0.001) and soil texture (p < 0.01) had a significant effect on the rate of evaporation, but their interaction was not significant (p = 0.26). In terms of surface crusts, silty loamy soils resulted in harder and more solid crusts in comparison with other textures. In contrast, crust formation in sandy soils was almost negligible, increasing their susceptibility to wind erosion risk. These results can support local municipalities in the development of a local plan against wind erosion phenomena in agricultural areas.
Gábor Négyesi; Szilárd Szabó; Botond Buró; Safwan Mohammed; József Lóki; Kálmán Rajkai; Imre Holb. Influence of Soil Moisture and Crust Formation on Soil Evaporation Rate: A Wind Tunnel Experiment in Hungary. Agronomy 2021, 11, 935 .
AMA StyleGábor Négyesi, Szilárd Szabó, Botond Buró, Safwan Mohammed, József Lóki, Kálmán Rajkai, Imre Holb. Influence of Soil Moisture and Crust Formation on Soil Evaporation Rate: A Wind Tunnel Experiment in Hungary. Agronomy. 2021; 11 (5):935.
Chicago/Turabian StyleGábor Négyesi; Szilárd Szabó; Botond Buró; Safwan Mohammed; József Lóki; Kálmán Rajkai; Imre Holb. 2021. "Influence of Soil Moisture and Crust Formation on Soil Evaporation Rate: A Wind Tunnel Experiment in Hungary." Agronomy 11, no. 5: 935.
Monilinia laxa causes serious postharvest damage on apricot fruits under shelf-life storage conditions. Plant elicitors of methyl jasmonate (MeJA) and salicylic acid (SA) can reduce this damage, and their research can explain the background of the plant defense physiological processes in M. laxa-infected fruits. The aims of this study were: (i) to evaluate the effect of various concentrations of MeJA and SA on brown rot incidence (BRI) and lesion diameter (LD) of apricot fruits; (ii) to measure the temporal patterns for the effect of 0.4 mmol L−1 MeJA and 2 mmol L−1 SA treatments on BRI, LD and seven fruit measures (fruit firmness (FF), lignin content (LC), total soluble phenol content (TSPC), total antioxidant capacity (TAC) and enzyme activities of PAL, POD and SOD) in treatments of M. laxa-inoculated versus (vs.) non-inoculated fruits over an eight-day shelf-life storage period; and (iii) to determine inter-correlations among the seven fruit measures for MeJA and SA treatments. Both MeJA and SA significantly reduced BRI and LD. LC, FF, TAC, TSPC, as well as SOD and PAL activities in the MeJA and SA treatments were higher than the water-treated control in most assessment days and both inoculation treatments. In both inoculation treatments, the activity of POD in the SA-treated fruits was higher than MeJA-treated and control fruits at all dates. In MeJA vs. SA and inoculated vs. non-inoculated treatments, six variable pairs (FF vs. TSPC, FF vs. TAC, TAC vs. PAL, PAL vs. POD, PAL vs. SOD, and POD vs. SOD) showed significant inter-correlation values. Principal component analyses explained 96% and 93% of the total variance for inoculated and non-inoculated treatments, respectively. In inoculated treatments, both PC1 and PC2 explained 41% of the total variance and correlated with FF, TSPC and TAC and with PAL, SOD and POD, respectively. In non-inoculated treatments, PC1 and PC2 explained 49% and 44% of the total variance and correlated with LC, PAL, POD and SOD and with FF, TSPC and TAC, respectively. It can be concluded that MeJA and SA are useful in the practice to enhance the plant defense system against brown rot by reducing fungal growth and by improving physical and antioxidant attributes (FF, LC, TAC and TSPC) and the activity of defense-related enzymes (PAL, POD and SOD) in apricot fruits during shelf-life storage conditions.
Ahmed Ezzat; Szilárd Szabó; Zoltán Szabó; Attila Hegedűs; Dorina Berényi; Imre Holb. Temporal Patterns and Inter-Correlations among Physical and Antioxidant Attributes and Enzyme Activities of Apricot Fruit Inoculated with Monilinia laxa under Salicylic Acid and Methyl Jasmonate Treatments under Shelf-Life Conditions. Journal of Fungi 2021, 7, 341 .
AMA StyleAhmed Ezzat, Szilárd Szabó, Zoltán Szabó, Attila Hegedűs, Dorina Berényi, Imre Holb. Temporal Patterns and Inter-Correlations among Physical and Antioxidant Attributes and Enzyme Activities of Apricot Fruit Inoculated with Monilinia laxa under Salicylic Acid and Methyl Jasmonate Treatments under Shelf-Life Conditions. Journal of Fungi. 2021; 7 (5):341.
Chicago/Turabian StyleAhmed Ezzat; Szilárd Szabó; Zoltán Szabó; Attila Hegedűs; Dorina Berényi; Imre Holb. 2021. "Temporal Patterns and Inter-Correlations among Physical and Antioxidant Attributes and Enzyme Activities of Apricot Fruit Inoculated with Monilinia laxa under Salicylic Acid and Methyl Jasmonate Treatments under Shelf-Life Conditions." Journal of Fungi 7, no. 5: 341.
Following the rediscovery after 200 years of Ablepharus kitaibelii fitzingeri in 2017, we carried out data collection its habitats regarding vegetation, microclimate, and soil on two prominent dolomite hills of the Eastern Bakony. Data collections were carried out in habitat mosaics (xerothermic forest edges on the plateaus, karst shrub forests in south-facing exposure, dry grasslands among forest patches on the plateaus, rocky grasslands in south-facing exposure) of three sampling blocks. Vegetation was examined by phytosociological relevés, microclimate from April to November continuously by TMS-2 dataloggers, and soil by laboratory analyses focused mainly on percentage of different fractions. According to our results a) shrub forests with a south-facing exposure provide a cooler microclimate with temperated fluctuation in the spring–early summer and late summer–early autumn periods; b) plateau grasslands and shrubs are characterised by looser soil structure. Based on our results, heterogeneous habitat character of forest–grassland mosaics of the Pannonicum can mitigate the expected negative effects of climate change on reptiles.
Zoltán Kenyeres; Norbert Bauer; Judit Cservenka; Szilárd Szabó; Sándor Tóth. Basic characteristics of microhabitats of snake-eyed skink (Ablepharus kitaibelii) in Western Hungary. Hacquetia 2021, 20, 189 -196.
AMA StyleZoltán Kenyeres, Norbert Bauer, Judit Cservenka, Szilárd Szabó, Sándor Tóth. Basic characteristics of microhabitats of snake-eyed skink (Ablepharus kitaibelii) in Western Hungary. Hacquetia. 2021; 20 (1):189-196.
Chicago/Turabian StyleZoltán Kenyeres; Norbert Bauer; Judit Cservenka; Szilárd Szabó; Sándor Tóth. 2021. "Basic characteristics of microhabitats of snake-eyed skink (Ablepharus kitaibelii) in Western Hungary." Hacquetia 20, no. 1: 189-196.
We analyzed the Corine Land Cover 2018 (CLC2018) dataset to reveal the correspondence between land cover categories of the CLC and the spectral information of Landsat-8, Sentinel-2 and PlanetScope images. Level 1 categories of the CLC2018 were analyzed in a 25 km × 25 km study area in Hungary. Spectral data were summarized by land cover polygons, and the dataset was evaluated with statistical tests. We then performed Linear Discriminant Analysis (LDA) and Random Forest classifications to reveal if CLC L1 level categories were confirmed by spectral values. Wetlands and water bodies were the most likely to be confused with other categories. The least mixture was observed when we applied the median to quantify the pixel variance of CLC polygons. RF outperformed the LDA’s accuracy, and PlanetScope’s data were the most accurate. Analysis of class level accuracies showed that agricultural areas and wetlands had the most issues with misclassification. We proved the representativeness of the results with a repeated randomized test, and only PlanetScope seemed to be ungeneralizable. Results showed that CLC polygons, as basic units of land cover, can ensure 71.1–78.5% OAs for the three satellite sensors; higher geometric resolution resulted in better accuracy. These results justified CLC polygons, in spite of visual interpretation, can hold relevant information about land cover considering the surface reflectance values of satellites. However, using CLC as ground truth data for land cover classifications can be questionable, at least in the L1 nomenclature.
Orsolya Varga; Zoltán Kovács; László Bekő; Péter Burai; Zsuzsanna Csatáriné Szabó; Imre Holb; Sarawut Ninsawat; Szilárd Szabó. Validation of Visually Interpreted Corine Land Cover Classes with Spectral Values of Satellite Images and Machine Learning. Remote Sensing 2021, 13, 857 .
AMA StyleOrsolya Varga, Zoltán Kovács, László Bekő, Péter Burai, Zsuzsanna Csatáriné Szabó, Imre Holb, Sarawut Ninsawat, Szilárd Szabó. Validation of Visually Interpreted Corine Land Cover Classes with Spectral Values of Satellite Images and Machine Learning. Remote Sensing. 2021; 13 (5):857.
Chicago/Turabian StyleOrsolya Varga; Zoltán Kovács; László Bekő; Péter Burai; Zsuzsanna Csatáriné Szabó; Imre Holb; Sarawut Ninsawat; Szilárd Szabó. 2021. "Validation of Visually Interpreted Corine Land Cover Classes with Spectral Values of Satellite Images and Machine Learning." Remote Sensing 13, no. 5: 857.
Gullies are responsible for detaching massive volumes of productive soil, dissecting natural landscape and causing damages to infrastructure. Despite existing research, the gravity of the gully erosion problem underscores the urgent need for accurate mapping of gullies, a first but essential step toward sustainable management of soil resources. This study aims to obtain the spatial distribution of gullies through comparing various classifiers: k-dimensional tree K-Nearest Neighbor (k-d tree KNN), Minimum Distance (MD), Maximum Likelihood (ML), and Random Forest (RF). Results indicated that all the classifiers, with the exception of ML, achieved an overall accuracy (OA) of at least 0.85. RF had the highest OA (0.94), although it was outperformed in gully identification by MD (0% commission), but the omission error was 20% (MD). Accordingly, RF was considered as the best algorithm, having 13% error in both adding (commission) and omitting pixels as gullies. Thus, RF ensured a reliable outcome to map the spatial distribution of gullies. RF-derived gully density map reflected the agricultural areas most exposed to gully erosion. Our approach of using satellite imagery has certain limitations, and can be used only in arid or semiarid regions where gullies are not covered by dense vegetation as the vegetation biases the extracted gullies. The approach also provides a solution to the lack of laser scanned data, especially in the context of the study area, providing better accuracy and wider application possibilities.
Kwanele Phinzi; Imre Holb; Szilárd Szabó. Mapping Permanent Gullies in an Agricultural Area Using Satellite Images: Efficacy of Machine Learning Algorithms. Agronomy 2021, 11, 333 .
AMA StyleKwanele Phinzi, Imre Holb, Szilárd Szabó. Mapping Permanent Gullies in an Agricultural Area Using Satellite Images: Efficacy of Machine Learning Algorithms. Agronomy. 2021; 11 (2):333.
Chicago/Turabian StyleKwanele Phinzi; Imre Holb; Szilárd Szabó. 2021. "Mapping Permanent Gullies in an Agricultural Area Using Satellite Images: Efficacy of Machine Learning Algorithms." Agronomy 11, no. 2: 333.
Temporal and spatial variability of annual and seasonal precipitation from 71 stations located in Western Balkan (WB) countries (Serbia, Bosnia and Herzegovina, and Montenegro) and their correlations with nine atmospheric circulation patterns was examined for the period 1950-2016. Annual precipitation increased significantly throughout the WB (from 2% to 8% per decade) on 20% of stations located mainly in the mountainous western Serbia and eastern Bosnia and Herzegovina. Winter was characterized by non?significant precipitation changes in most of the studied area, with only a few stations characterized by significant precipitation increase (up to 12% per decade) in the mountainous area of WB, and a few stations characterized by significant decrease (up to -6% per decade) in the Pannonian plain. Significant precipitation increase was noticed on 15% of the stations in spring, while it was noticed on 17% of the stations in autumn. Summer precipitation decreased significantly (up to -5% per decade) on a limited area of northern Serbia (6% of the stations), while the majority of stations showed non?significant increase. The strongest influences on annual precipitation in WB region are of the Arctic Oscillation (AO) and Mediterranean Oscillation (MO), leading to the precipitation decrease during their positive phases. Winter precipitation is significantly negatively correlated with AO, East Atlantic/Western Russia oscillation (EA/WR), and North Atlantic Oscillation (NAO) and has a significant positive correlation with Western Mediterranean Oscillation (WeMO) on the majority of stations. MO has the strongest influence on summer precipitation in WB region leading to precipitation decrease, while AO has the dominant influence on precipitation in the region during autumn.
Dragan Milosevic; Rastislav Stojsavljevic; Szilárd Szabó; Ugljesa Stankov; Stevan Savic; Luka Mitrovic. Spatio-temporal variability of precipitation over the Western Balkan countries and its links with the atmospheric circulation patterns. Journal of the Geographical Institute Jovan Cvijic, SASA 2021, 71, 29 -42.
AMA StyleDragan Milosevic, Rastislav Stojsavljevic, Szilárd Szabó, Ugljesa Stankov, Stevan Savic, Luka Mitrovic. Spatio-temporal variability of precipitation over the Western Balkan countries and its links with the atmospheric circulation patterns. Journal of the Geographical Institute Jovan Cvijic, SASA. 2021; 71 (1):29-42.
Chicago/Turabian StyleDragan Milosevic; Rastislav Stojsavljevic; Szilárd Szabó; Ugljesa Stankov; Stevan Savic; Luka Mitrovic. 2021. "Spatio-temporal variability of precipitation over the Western Balkan countries and its links with the atmospheric circulation patterns." Journal of the Geographical Institute Jovan Cvijic, SASA 71, no. 1: 29-42.
Monitoring air pollution and environmental health are crucial to ensure viable cities. We assessed the usefulness of the Air Pollution Tolerance Index (APTI) as a composite index of environmental health. Fine and coarse dust amount and elemental concentrations of Celtis occidentalis and Tilia × europaea leaves were measured in June and September at three sampling sites (urban, industrial, and rural) in Debrecen city (Hungary) to assess the usefulness of APTI. The correlation between APTI values and dust amount and elemental concentrations was also studied. Fine dust, total chlorophyll, and elemental concentrations were the most sensitive indicators of pollution. Based on the high chlorophyll and low elemental concentration of tree leaves, the rural site was the least disturbed by anthropogenic activities, as expected. We demonstrated that fine and coarse dust amount and elemental concentrations of urban tree leaves are especially useful for urban air quality monitoring. Correlations between APTI and other measured parameters were also found. Both C. occidentalis and T. europaea were sensitive to air pollution based on their APTI values. Thus, the APTI of tree leaves is an especially useful proxy measure of air pollution, as well as environmental health.
Vanda Éva Molnár; Dávid Tőzsér; Szilárd Szabó; Béla Tóthmérész; Edina Simon. Use of Leaves as Bioindicator to Assess Air Pollution Based on Composite Proxy Measure (APTI), Dust Amount and Elemental Concentration of Metals. Plants 2020, 9, 1743 .
AMA StyleVanda Éva Molnár, Dávid Tőzsér, Szilárd Szabó, Béla Tóthmérész, Edina Simon. Use of Leaves as Bioindicator to Assess Air Pollution Based on Composite Proxy Measure (APTI), Dust Amount and Elemental Concentration of Metals. Plants. 2020; 9 (12):1743.
Chicago/Turabian StyleVanda Éva Molnár; Dávid Tőzsér; Szilárd Szabó; Béla Tóthmérész; Edina Simon. 2020. "Use of Leaves as Bioindicator to Assess Air Pollution Based on Composite Proxy Measure (APTI), Dust Amount and Elemental Concentration of Metals." Plants 9, no. 12: 1743.
The apricot storability is one of the largest challenges, which the apricot industry has to face all over the world; therefore, finding options for prolonging fruit quality during cold storage (CS) and shelf-life (SL) will help to decrease postharvest losses of apricot. The aim of this apricot fruit work was to study the temporal changes and correlations of 10 quality parameters (quality losses, antioxidant properties and enzyme activities) in the postharvest treatments of methyl jasmonate (MeJA) and salicylic acid (SA) under 1 °C CS (7, 14 and 21 days) and 25 °C SL (4 and 8 days after the 21-day CS) treatments. MeJA and SA significantly decreased the quality loss of chilling injury (CI) and fruit decay (FD) at all dates for both storage conditions. MeJA- and SA-treated fruits increased total antioxidant capacity (TAC), total soluble phenolic compounds (TSPC) and carotenoids contents (TCC) at all dates of both storage treatments. In contrast, the ascorbic acid content (AAC) increased only until days 14 and 4 in the CS and SL treatments, respectively. Among enzyme activity parameters, the activities of phenylalanine ammonia-lyase (PAL), peroxidase and superoxide dismutase (SOD) were significantly increased in the MeJA and SA treatments in all dates of both storage treatments. Catalase (CAT) activity increased in the SA and control treatments, while it decreased in the MeJA treatment in both storage conditions. In both the MeJA and the SA treatments, six pair-variables (FD vs. CI, PAL vs. CAT, PAL vs. SOD, TAC vs. SOD, TAC vs. FD, and AAC vs. CI) were significant in Pearson correlation and regression analyses among the 45 parameters pairs. Principal component analyses explained 89.3% of the total variance and PC1 accounted for 55.6% of the variance and correlated with the CI, FD, TAC, TSPC, TCC, PAL and SOD, indicating strong connections among most parameters. In conclusion, MeJA and SA are practically useful and inexpensive techniques to maintain quality attributes of CI, FD, TAC, TSPC, TCC, PAL, POD and SOD in apricot fruit during both CS and SL conditions.
Ahmed Ezzat; Attila Hegedűs; Szilárd Szabó; Amin Ammar; Zoltán Szabó; József Nyéki; Bianka Molnár; Imre J. Holb. Temporal Changes and Correlations between Quality Loss Parameters, Antioxidant Properties and Enzyme Activities in Apricot Fruit Treated with Methyl Jasmonate and Salicylic Acid during Cold Storage and Shelf-Life. Applied Sciences 2020, 10, 8071 .
AMA StyleAhmed Ezzat, Attila Hegedűs, Szilárd Szabó, Amin Ammar, Zoltán Szabó, József Nyéki, Bianka Molnár, Imre J. Holb. Temporal Changes and Correlations between Quality Loss Parameters, Antioxidant Properties and Enzyme Activities in Apricot Fruit Treated with Methyl Jasmonate and Salicylic Acid during Cold Storage and Shelf-Life. Applied Sciences. 2020; 10 (22):8071.
Chicago/Turabian StyleAhmed Ezzat; Attila Hegedűs; Szilárd Szabó; Amin Ammar; Zoltán Szabó; József Nyéki; Bianka Molnár; Imre J. Holb. 2020. "Temporal Changes and Correlations between Quality Loss Parameters, Antioxidant Properties and Enzyme Activities in Apricot Fruit Treated with Methyl Jasmonate and Salicylic Acid during Cold Storage and Shelf-Life." Applied Sciences 10, no. 22: 8071.
Floodplains are valuable scenes of water management and nature conservation. A better understanding of their geomorphological characteristic helps to understand the main processes involved. We performed a classification of floodplain forms in a naturally developed area in Hungary using a Digital Terrain Model (DTM) of aerial laser scanning. We derived 60 geomorphometric variables from the DTM and prepared a geomorphological map of 265 forms (crevasse channels, point bars, swales, levees). Random Forest classification was conducted with Recursive Feature Elimination (RFE) on the objects (mean pixel values by forms) and on the pixels of the variables. We also evaluated the classification probabilities (CP), the spatial uncertainties (SU), and the overfitting in the function of the number of the variables. We found that the object-based method had a better performance (95%) than the pixel-based method (78%). RFE helped to identify the most important 13–20 variables, maintaining the high model performance and reducing the overfitting. However, CP and SU were not efficient measures of classification accuracy as they were not in accordance with the class level accuracy metric. Our results help to understand classification results and the specific limits of laser scanned DTMs. This methodology can be useful in geomorphologic mapping.
Zsuzsanna Csatáriné Szabó; Tomáš Mikita; Gábor Négyesi; Orsolya Varga; Péter Burai; László Takács-Szilágyi; Szilárd Szabó. Uncertainty and Overfitting in Fluvial Landform Classification Using Laser Scanned Data and Machine Learning: A Comparison of Pixel and Object-Based Approaches. Remote Sensing 2020, 12, 3652 .
AMA StyleZsuzsanna Csatáriné Szabó, Tomáš Mikita, Gábor Négyesi, Orsolya Varga, Péter Burai, László Takács-Szilágyi, Szilárd Szabó. Uncertainty and Overfitting in Fluvial Landform Classification Using Laser Scanned Data and Machine Learning: A Comparison of Pixel and Object-Based Approaches. Remote Sensing. 2020; 12 (21):3652.
Chicago/Turabian StyleZsuzsanna Csatáriné Szabó; Tomáš Mikita; Gábor Négyesi; Orsolya Varga; Péter Burai; László Takács-Szilágyi; Szilárd Szabó. 2020. "Uncertainty and Overfitting in Fluvial Landform Classification Using Laser Scanned Data and Machine Learning: A Comparison of Pixel and Object-Based Approaches." Remote Sensing 12, no. 21: 3652.
Soils in the coastal region of Syria (CRoS) are one of the most fragile components of natural ecosystems. However, they are adversely affected by water erosion processes after extreme land cover modifications such as wildfires or intensive agricultural activities. The main goal of this research was to clarify the dynamic interaction between erosion processes and different ecosystem components (inclination, land cover/land use, and rainy storms) along with the vulnerable territory of the CRoS. Experiments were carried out in five different locations using a total of 15 erosion plots. Soil loss and runoff were quantified in each experimental plot, considering different inclinations and land uses (agricultural land (AG), burnt forest (BF), forest/control plot (F)). Observed runoff and soil loss varied greatly according to both inclination and land cover after 750 mm of rainfall (26 events). In the cultivated areas, the average soil water erosion ranged between 0.14 ± 0.07 and 0.74 ± 0.33 kg/m2; in the BF plots, mean soil erosion ranged between 0.03 ± 0.01 and 0.24 ± 0.10 kg/m2. The lowest amount of erosion was recorded in the F plots where the erosion ranged between 0.1 ± 0.001 and 0.07 ± 0.03 kg/m2. Interestingly, the General Linear Model revealed that all factors (i.e., inclination, rainfall and land use) had a significant (p < 0.001) effect on the soil loss. We concluded that human activities greatly influenced soil erosion rates, being higher in the AG lands, followed by BF and F. Therefore, the current study could be very useful to policymakers and planners for proposing immediate conservation or restoration plans in a less studied area which has been shown to be vulnerable to soil erosion processes.
Safwan Mohammed; Hazem G. Abdo; Szilard Szabo; Quoc Bao Pham; Imre J. Holb; Nguyen Thi Thuy Linh; Duong Tran Anh; Karam Alsafadi; Ali Mokhtar; Issa Kbibo; Jihad Ibrahim; Jesus Rodrigo-Comino. Estimating Human Impacts on Soil Erosion Considering Different Hillslope Inclinations and Land Uses in the Coastal Region of Syria. Water 2020, 12, 2786 .
AMA StyleSafwan Mohammed, Hazem G. Abdo, Szilard Szabo, Quoc Bao Pham, Imre J. Holb, Nguyen Thi Thuy Linh, Duong Tran Anh, Karam Alsafadi, Ali Mokhtar, Issa Kbibo, Jihad Ibrahim, Jesus Rodrigo-Comino. Estimating Human Impacts on Soil Erosion Considering Different Hillslope Inclinations and Land Uses in the Coastal Region of Syria. Water. 2020; 12 (10):2786.
Chicago/Turabian StyleSafwan Mohammed; Hazem G. Abdo; Szilard Szabo; Quoc Bao Pham; Imre J. Holb; Nguyen Thi Thuy Linh; Duong Tran Anh; Karam Alsafadi; Ali Mokhtar; Issa Kbibo; Jihad Ibrahim; Jesus Rodrigo-Comino. 2020. "Estimating Human Impacts on Soil Erosion Considering Different Hillslope Inclinations and Land Uses in the Coastal Region of Syria." Water 12, no. 10: 2786.
The Mediterranean part of Syria is affected by soil water erosion due to poor land management. Within this context, the main aim of this research was to track soil erosion and runoff after each rainy storm between September 2013 and April 2014 (rainy season), on two slopes with different gradients (4.7%; 10.3%), under three soil cover types (SCTs): bare soil (BS), metal sieve cover (MC), and strip cropping (SC), in Central Syria. Two statistical multivariate models, the general linear model (GLM), and the random forest regression (RFR) were applied to reveal the importance of SCTs. Our results reveal that higher erosion rate, as well as runoff, were recorded in BS followed by MC, and SC. Accordingly, soil cover had a significant effect (p < 0.001) on soil erosion, and no significant difference was detected between MC and SC. Different combinations of slopes and soil cover had no effect on erosion, at least in this experiment. RFR performed better than GLM in predictions. GLM’s median of mean absolute error was 21% worse than RFR. Nonetheless, 25 repetitions of 2-fold cross-validation ensured the highest available prediction accuracy for RFR. In conclusion, we revealed that runoff, rain intensity and soil cover were the most important factors in erosion.
Safwan Mohammed; Ali Al-Ebraheem; Imre Holb; Karam Alsafadi; Mohammad Dikkeh; Quoc Pham; Nguyen Linh; Szilard Szabo. Soil Management Effects on Soil Water Erosion and Runoff in Central Syria—A Comparative Evaluation of General Linear Model and Random Forest Regression. Water 2020, 12, 2529 .
AMA StyleSafwan Mohammed, Ali Al-Ebraheem, Imre Holb, Karam Alsafadi, Mohammad Dikkeh, Quoc Pham, Nguyen Linh, Szilard Szabo. Soil Management Effects on Soil Water Erosion and Runoff in Central Syria—A Comparative Evaluation of General Linear Model and Random Forest Regression. Water. 2020; 12 (9):2529.
Chicago/Turabian StyleSafwan Mohammed; Ali Al-Ebraheem; Imre Holb; Karam Alsafadi; Mohammad Dikkeh; Quoc Pham; Nguyen Linh; Szilard Szabo. 2020. "Soil Management Effects on Soil Water Erosion and Runoff in Central Syria—A Comparative Evaluation of General Linear Model and Random Forest Regression." Water 12, no. 9: 2529.
Urban sprawl related increase of built-in areas requires reliable monitoring methods and remote sensing can be an efficient technique. Aerial surveys, with high spatial resolution, provide detailed data for building monitoring, but archive images usually have only visible bands. We aimed to reveal the efficiency of visible orthophotographs and photogrammetric dense point clouds in building detection with segmentation-based machine learning (with five algorithms) using visible bands, texture information, and spectral and morphometric indices in different variable sets. Usually random forest (RF) had the best (99.8%) and partial least squares the worst overall accuracy (~60%). We found that >95% accuracy can be gained even in class level. Recursive feature elimination (RFE) was an efficient variable selection tool, its result with six variables was like when we applied all the available 31 variables. Morphometric indices had 82% producer’s and 85% user’s Accuracy (PA and UA, respectively) and combining them with spectral and texture indices, it had the largest contribution in the improvement. However, morphometric indices are not always available but by adding texture and spectral indices to red-green-blue (RGB) bands the PA improved with 12% and the UA with 6%. Building extraction from visual aerial surveys can be accurate, and archive images can be involved in the time series of a monitoring.
Aletta Schlosser; Gergely Szabó; László Bertalan; Zsolt Varga; Péter Enyedi; Szilárd Szabó. Building Extraction Using Orthophotos and Dense Point Cloud Derived from Visual Band Aerial Imagery Based on Machine Learning and Segmentation. Remote Sensing 2020, 12, 2397 .
AMA StyleAletta Schlosser, Gergely Szabó, László Bertalan, Zsolt Varga, Péter Enyedi, Szilárd Szabó. Building Extraction Using Orthophotos and Dense Point Cloud Derived from Visual Band Aerial Imagery Based on Machine Learning and Segmentation. Remote Sensing. 2020; 12 (15):2397.
Chicago/Turabian StyleAletta Schlosser; Gergely Szabó; László Bertalan; Zsolt Varga; Péter Enyedi; Szilárd Szabó. 2020. "Building Extraction Using Orthophotos and Dense Point Cloud Derived from Visual Band Aerial Imagery Based on Machine Learning and Segmentation." Remote Sensing 12, no. 15: 2397.
Atmospheric aerosol particles containing heavy metal contaminants deposit on the surface of plant leaves and the topsoil. Our aim was to reveal the pollution along an industrial–urban–rural gradient (IURG) in the central provinces of Thailand. Leaf samples from Ficus religiosa and Mimusops elengi were collected along with topsoil samples under the selected trees. Al, Ba, Ca, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, and Zn concentrations were determined by ICP-OES in soil and plant samples. Soils were not polluted according to the critical value; furthermore, the elemental composition did not differ among the sampling sites of the IURG. The rural site was also polluted due to heavy amounts of untreated wastewater of the adjacent Chao Phraya River. Bioaccumulation factors of Ba, Cu, and Mn was higher than 1, suggesting active accumulation of these elements in plant tissue. Our findings proved that the deposition of air pollutants and the resistance to air pollutants in the case of plant leaves were different and that humus materials of the soils had relevant role in bioaccumulation of Al, Ba, and Cu. At the same time, the geochemical background, the source of pollution, and the local plant species greatly influence the metal content of any given environmental compartment.
Vanda Éva Molnár; Edina Simon; Sarawut Ninsawat; Béla Tóthmérész; Szilárd Szabó. Pollution Assessment Based on Element Concentration of Tree Leaves and Topsoil in Ayutthaya Province, Thailand. International Journal of Environmental Research and Public Health 2020, 17, 5165 .
AMA StyleVanda Éva Molnár, Edina Simon, Sarawut Ninsawat, Béla Tóthmérész, Szilárd Szabó. Pollution Assessment Based on Element Concentration of Tree Leaves and Topsoil in Ayutthaya Province, Thailand. International Journal of Environmental Research and Public Health. 2020; 17 (14):5165.
Chicago/Turabian StyleVanda Éva Molnár; Edina Simon; Sarawut Ninsawat; Béla Tóthmérész; Szilárd Szabó. 2020. "Pollution Assessment Based on Element Concentration of Tree Leaves and Topsoil in Ayutthaya Province, Thailand." International Journal of Environmental Research and Public Health 17, no. 14: 5165.
Soil moisture is essential for water resources management, yet accurate information of soil moisture has been a challenge. The major goal was to parametrize the Modified Water Cloud Model (MWCM). The Sentinel-1A data of winter wheat crop was collected for two weeks. Concurrently, in-situ soil moisture data was collected using Time Domain Reflectometer (TDR). A parametric scheme was used for the retrieval of the VV polarization of Sentinel-1A. The effect of NDVI as a vegetation descriptors (V1 and V2) on total VV backscatter (σ 0) was analyzed. The calibration showed NDVI has the potential to influence Water Cloud Model (WCM) and vegetation descriptors; hence it is recommended to calibrate the MWCM. The coefficient of determination (R2 = 0.83) showed a good agreement between observed and estimated soil moisture. Therefore, this approach help improve soil moisture prediction, and can be applied to determine soil moisture more accurately for winter crops, grasses, and pasture lands.
Kishan Singh Rawat; Sudhir Kumar Singh; Ram L. Ray; Szilard Szabo. Parameterization of the modified water cloud model (MWCM) using normalized difference vegetation index (NDVI) for winter wheat crop: a case study from Punjab, India. Geocarto International 2020, 1 -14.
AMA StyleKishan Singh Rawat, Sudhir Kumar Singh, Ram L. Ray, Szilard Szabo. Parameterization of the modified water cloud model (MWCM) using normalized difference vegetation index (NDVI) for winter wheat crop: a case study from Punjab, India. Geocarto International. 2020; ():1-14.
Chicago/Turabian StyleKishan Singh Rawat; Sudhir Kumar Singh; Ram L. Ray; Szilard Szabo. 2020. "Parameterization of the modified water cloud model (MWCM) using normalized difference vegetation index (NDVI) for winter wheat crop: a case study from Punjab, India." Geocarto International , no. : 1-14.
Trees are especially useful biological indicators. We tested the suitability of tree leaves (Common Lime) to assess PM5 and PM10 deposition in the three summer months of 2018 in Debrecen city, Hungary. We also tested the usefulness of the cheap and simple gravimetric method to assess the PM deposition, and compared to the expensive, but standard laser diffraction method. We found significant differences between the concentrations of PM10 deposited on tree leaves, and on dust traps. A significant difference was found in the concentration of PM5 only in July. A significant difference was also found in the concentration of PM10 among months based on leaves and dust traps. For PM5 there was a significant difference among months based on leaves deposition. We found a significant positive correlation between the PM10 concentration deposited on leaves and on dust traps. A positive correlation was found between the concentration of PM based on the gravimetric and laser diffraction measurement methods. Our findings pointed out the particulate material’s washing by rain from leaves; thus, dust deposition on the surface of leaves is limited. Our results demonstrated that trees play an important role in the mitigation of air pollution, and they are a useful indicator of PM deposition for biomonitoring studies.
Edina Simon; Vanda Éva Molnár; Béla Tóthmérész; Szilárd Szabó. Ecological Assessment of Particulate Material (PM5 and PM10) in Urban Habitats. Atmosphere 2020, 11, 559 .
AMA StyleEdina Simon, Vanda Éva Molnár, Béla Tóthmérész, Szilárd Szabó. Ecological Assessment of Particulate Material (PM5 and PM10) in Urban Habitats. Atmosphere. 2020; 11 (6):559.
Chicago/Turabian StyleEdina Simon; Vanda Éva Molnár; Béla Tóthmérész; Szilárd Szabó. 2020. "Ecological Assessment of Particulate Material (PM5 and PM10) in Urban Habitats." Atmosphere 11, no. 6: 559.
Observing wetland areas and monitoring changes are crucial to understand hydrological and ecological processes. Sedimentation-induced vegetation spread is a typical process in the succession of lakes endangering these habitats. We aimed to survey the tendencies of vegetation spread of a Hungarian lake using satellite images, and to develop a method to identify the areas of risk. Accordingly, we performed a 33-year long vegetation spread monitoring survey. We used the Normalized Difference Vegetation Index (NDVI) and the Modified Normalized Difference Water Index (MNDWI) to assess vegetation and open water characteristics of the basins. We used these spectral indices to evaluate sedimentation risk of water basins combined with the fact that the most abundant plant species of the basins was the water caltrop (Trapa natans) indicating shallow water. We proposed a 12-scale Level of Sedimentation Risk Index (LoSRI) composed from vegetation cover data derived from satellite images to determine sedimentation risk within any given water basin. We validated our results with average water basin water depth values, which showed an r = 0.6 (p < 0.05) correlation. We also pointed on the most endangered locations of these sedimentation-threatened areas, which can provide crucial information for management planning of water directorates and management organizations.
Loránd Szabó; Balázs Deák; Tibor Bíró; Gareth J. Dyke; Szilárd Szabó. NDVI as a Proxy for Estimating Sedimentation and Vegetation Spread in Artificial Lakes—Monitoring of Spatial and Temporal Changes by Using Satellite Images Overarching Three Decades. Remote Sensing 2020, 12, 1468 .
AMA StyleLoránd Szabó, Balázs Deák, Tibor Bíró, Gareth J. Dyke, Szilárd Szabó. NDVI as a Proxy for Estimating Sedimentation and Vegetation Spread in Artificial Lakes—Monitoring of Spatial and Temporal Changes by Using Satellite Images Overarching Three Decades. Remote Sensing. 2020; 12 (9):1468.
Chicago/Turabian StyleLoránd Szabó; Balázs Deák; Tibor Bíró; Gareth J. Dyke; Szilárd Szabó. 2020. "NDVI as a Proxy for Estimating Sedimentation and Vegetation Spread in Artificial Lakes—Monitoring of Spatial and Temporal Changes by Using Satellite Images Overarching Three Decades." Remote Sensing 12, no. 9: 1468.
Several factors influence the performance of land change simulation models. One potentially important factor is land category aggregation, which reduces the number of categories while having the potential to reduce also the size of apparent land change in the data. Our article compares how four methods to aggregate Corine Land Cover categories influence the size of land changes in various spatial extents and consequently influence the performance of 114 Cellular Automata-Markov simulation model runs. We calculated the reference change during the calibration interval, the reference change during the validation interval and the simulation change during the validation interval, along with five metrics of simulation performance, Figure of Merit and its four components: Misses, Hits, Wrong Hits and False Alarms. The Corine Standard Level 1 category aggregation reduced change more than any of the other aggregation methods. The model runs that used the Corine Standard Level 1 aggregation method tended to return lower sizes of changing areas and lower values of Misses, Hits, Wrong Hits and False Alarms, where Hits are correctly simulated changes. The behavior-based aggregation method maintained the most change while using fewer categories compared to the other aggregation methods. We recommend an aggregation method that maintains the size of the reference change during the calibration and validation intervals while reducing the number of categories, so the model uses the largest size of change while using fewer than the original number of categories.
Orsolya Gyöngyi Varga; Robert Gilmore Pontius Jr; Zsuzsanna Szabó; Szilárd Szabó. Effects of Category Aggregation on Land Change Simulation Based on Corine Land Cover Data. Remote Sensing 2020, 12, 1314 .
AMA StyleOrsolya Gyöngyi Varga, Robert Gilmore Pontius Jr, Zsuzsanna Szabó, Szilárd Szabó. Effects of Category Aggregation on Land Change Simulation Based on Corine Land Cover Data. Remote Sensing. 2020; 12 (8):1314.
Chicago/Turabian StyleOrsolya Gyöngyi Varga; Robert Gilmore Pontius Jr; Zsuzsanna Szabó; Szilárd Szabó. 2020. "Effects of Category Aggregation on Land Change Simulation Based on Corine Land Cover Data." Remote Sensing 12, no. 8: 1314.