Browsing by Person "Schmieder, Klaus"

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Analysis of phytosociological composition and spatial structure of the central zone of Lake Baikal Eastern coast vegetation
(2018) Brianskaia, Elena; Schmieder, Klaus
The object of this study is the terrestrial ecosystem of Lake Baikal enlisted by UNESCO as the World Heritage Site. The analysis of spatial and phytosociological structures of the vegetation can reveal important stages of its formation and future dynamics. Today, the present flora and vegetation of the complex Baikal Siberian ecosystem is reflected in studies of many Russian and international phytosociologists. However, despite the huge amount of data, the phytosociological vegetation structure and its spatial distribution of the central zone of Lake Baikal eastern coast has not been studied. By this thesis, we provide the first results about the flora, phytosociological composition of the vegetation and the soil diversity of the central zone of Lake Baikal eastern coast. Selecting the area to study, we hypothesize that this complex territory can be considered as a model biome that adjoins Lake Baikal central zone in the east. The major landscape of the studied area is composed of forests complicated by the bogged valleys of the rivers Cheremshanka, Talovka and Bezymyanka. The Katkovskaya and Chernaya Griva mountains range stretches from the northto the east. 167 relevés were performed by standard methods of the Braun-Blanquet approach. To reveal the phytosociological composition of the vegetation supervised k-means classification was performed in JUICE program. By comparing the vegetation data from the studied area (167 relevés) with data from the adjacent territories of Lake Baikal, Svyatoi Nos Peninsula and the Barguzin mountain range (589 relevés) was obtained the final prodromus of the vegetation. The soil identification was performed according to Russian soil classification. The vegetation mapping was performed in ArcGIS 10.3.1 by the supervised image classification of multispectral panchromatic imagery SPOT 6. The vegetation of the territory under study is represented by four classes. The dominant type of the vegetation is represented by forests which are classified into Vaccinio-Piceetea Br.-Bl. in Br.-Bl. et al. 1939 class. The wetland vegetation includes two classes Scheuchzerio-Caricetea nigrae (Nordh. 1936) Тх. 1937 and Oxycocco-Sphagnetea Br.-Bl et R. Tx. 1943. The vegetation of shifting sands of the coastal line is classified into Brometea korotkyi Hilbig et Korolyuk 2000 class. For all phytosociological vegetation units are identified seven soil types, such as, Lithozems, Brown soil, Soddy Brown Forest soil and Rzhavozems, Fen Peat, and Peat Gleyzem. The soil distribution demonstrates its contingence with an altitudinal gradient; however, transitioning from mountain to plain areas, a hydrological regime becomes crucial. Despite a relatively small territory under study (approx. 500 km2), the vegetation is relatively diverse. Location of the studied area within the zonal forest belt contributes to the leading position of the forest communities. The close ground water occurrence creates suitable conditions for wetland vegetation formation. Lake Baikal coastal line is considered as a refugium of the unique ancient Miocene-Pliocene xerophytic vegetation and flora. Thus, Lake Baikal water body, mountain landform and close ground water occurrence contribute to the formation of diverse vegetation communities. We suggest that the vegetation of this relatively small territory can be considered as a model within the central zone of Lake Baikal eastern coast.
Automatic classification of submerged macrophytes at Lake Constance using laser bathymetry point clouds
(2024) Wagner, Nike; Franke, Gunnar; Schmieder, Klaus; Mandlburger, Gottfried; Wagner, Nike; Department of Geodesy and Geoinformation, TU Wien, Wiedner Hauptstr. 8-10, 1040 Vienna, Austria;; Franke, Gunnar; Institute of Landscape and Plant Ecology (320), University of Hohenheim, Ottilie-Zeller-Weg 2, 70599 Stuttgart, Germany; (G.F.); (K.S.); Schmieder, Klaus; Institute of Landscape and Plant Ecology (320), University of Hohenheim, Ottilie-Zeller-Weg 2, 70599 Stuttgart, Germany; (G.F.); (K.S.); Mandlburger, Gottfried; Department of Geodesy and Geoinformation, TU Wien, Wiedner Hauptstr. 8-10, 1040 Vienna, Austria;; Stateczny, Andrzej
Submerged aquatic vegetation, also referred to as submerged macrophytes, provides important habitats and serves as a significant ecological indicator for assessing the condition of water bodies and for gaining insights into the impacts of climate change. In this study, we introduce a novel approach for the classification of submerged vegetation captured with bathymetric LiDAR (Light Detection And Ranging) as a basis for monitoring their state and change, and we validated the results against established monitoring techniques. Employing full-waveform airborne laser scanning, which is routinely used for topographic mapping and forestry applications on dry land, we extended its application to the detection of underwater vegetation in Lake Constance. The primary focus of this research lies in the automatic classification of bathymetric 3D LiDAR point clouds using a decision-based approach, distinguishing the three vegetation classes, (i) Low Vegetation, (ii) High Vegetation, and (iii) Vegetation Canopy, based on their height and other properties like local point density. The results reveal detailed 3D representations of submerged vegetation, enabling the identification of vegetation structures and the inference of vegetation types with reference to pre-existing knowledge. While the results within the training areas demonstrate high precision and alignment with the comparison data, the findings in independent test areas exhibit certain deficiencies that are likely addressable through corrective measures in the future.
Development of assessment tools for Lake Sevan (Armenia) by the application of remote sensing data and geographic information systems (GIS) techniques
(2011) Agyemang, Thomas Kwaku; Schmieder, Klaus
Lake Sevan is the biggest source of water in Armenia. Its littoral zone, in addition to being a food source and a substrate for macrophytes, algae and invertebrates, provide refuge and spawning habitats for both young & old organisms especially fishes. Between 1933 and 1960s, the lake level had been lowered by 20 m below the original level by increasing the lake outflow intermittently for irrigation and electricity generation. This evidently had ecological and economical consequences on the lake ecosystem. The importance of assessing the accuracy of spatial data classifications derived from remote sensing methods and used in geographic information system (GIS) analyses has been regarded as a critical component of many projects. In this project, supervised classified QuickBird satellite imageries of both submersed macrophytes and landcover types (emersed vegetation) of the Gavaraget, Tsovazard and Masrik Regions of the study area were validated in a GIS environment. The results of these assessments were represented by error matrices presenting the overall accuracy, the user and producer accuracies in each category, as well as the kappa coefficients. For submersed macrophytes at the vegetation level, the overall accuracy ranging between 77-88% was achieved in all the investigation years. Alga blooms in the different years impacted on the accuracy of the classification. However, even through severe algal blooms user accuracies between 55% and 95% were achieved. On the other hand, at the growth type level, the overall accuracy was as high as over 70% and as low as below 49%. For emersed vegetation types, predominantly high overall accuracies of more than 70% were obtained in 2 of the investigation years. Above all, in 2008, only slight overall accuracy could be obtained. For reeds areas, high user accuracies of more than 78% could be obtained, while for shrubs, trees, no vegetation and grasses in the different years, very different classification accuracies were attained. Two habitat suitability models (one for fishes and one for birds) were built in a GIS environment in this project. While the Crucian Carp (Carassius auratus Gibelio Bloch) was chosen as lead species for the fish habitat, the Common Coot (Fulica atra) and the Great Crested Grebe (Podiceps cristatus) were chosen for the bird habitat models based on expert knowledge on Lake Sevan. Five fish habitat suitability classes were assigned in the model. There was a similar trend in the fish habitat areas in all the landscapes in Gavaraget, Tsovazard and Masrik regions. The habitat areas increased in 2007 and decreased in 2008. The increases in all the regions were the same (around 43%) while the highest reduction occurred in Gavaraget (47%) followed by Masrik (38%) and Tsovazard (25%) respectively. Apart from the reductions in habitat areas in 2008, there were severe decreases in the quality of the habitat areas in all the regions of interests. The increases and decreases were as a result of interannual fluctuations due to water level fluctuations and algal blooms of Lake Sevan. Also, for the bird habitat model, five classes were assigned. Tsovazard and Masrik had a similar trend in habitat areas with an initial increase in 2007 followed by a decrease in 2008. However, Gavaraget had reductions in 2007 and 2008. Again, in addition to the severe reductions in the habitat areas in 2008, there were severe decreases in the quality of the habitat areas in all the regions of interests. The changes in emersed macrophyte vegetations and the lake water level fluctuations effected the different changes in the bird habitat areas.
Fernerkundungsgestützte Analyse und Bewertung ökologischer Auswirkungen des Anbaus von Bioenergiepflanzen auf die Agro-Biodiversität anhand der Modellierung der Habitatansprüche der Feldlerche (Alauda arvensis)
(2017) Schlager, Patric; Schmieder, Klaus
For the first time in 2002, the transformation of the conventional energy system into a system based on renewable energies was politically and legally decided in Germany. On the regional level numerous communities and municipalities followed this decision by voicing their own political resolutions, addressing the coverage of energy consumption with renewable energies. Their implementation is accompanied by a spatial expansion of bioenergy crops which lead to a controversial discussion about food safety, biodiversity and landscape change. Framed by the above mentioned discussion, this study assesses potential changes of skylark (Alauda arvensis) occurrence caused by a spatial expansion of bioenergy crops in the municipality of Schwäbisch Hall, Germany. The skylark was selected due to the comprehensive state of research about skylarks, their endangerment (“Red list of German breeding birds”), and the status as umbrella species for open agricultural landscapes (skylarks typically avoid vertical structures like hedges or edges of forests). The latter emphasizes their role as representatives for other species which are potentially affected by an expansion of bioenergy crops. This study is based on a stratified bird monitoring scheme of Baden-Württemberg, which was developed during a project that aimed to set up an indicator for species richness and was financed by the Bundesministerium für Ernährung, Landwirtschaft und Verbraucherschutz (BMELV). From the bird monitoring scheme, the stratum, which covers the municipality of Schwäbisch Hall, was extracted and served as a base for the development of a Generalized Linear Habitat Model of the skylark. In order to assess potential habitat changes caused by an expansion of bioenergy crops, Schwäbisch Hall was mapped with an airborne remote sensing technology in 2011. The resulting aerial images were transformed into orthophotos and later classified (focusing on agricultural areas) with an object oriented image analysis approach. Based on the outcomes of the habitat association model and the land use classification, skylark territories were predicted for 1 km² plots covering Schwäbisch Hall. For an in-depth understanding of ecological impacts from expanded bioenergy cropping, a bioenergy scenario was developed considering § 17 BBodSchG (national soil protection act) and regional food security. Based on the scenario, skylark territories were predicted for 1 km² plots covering Schwäbisch Hall. The most reasonable habitat association model resulted in a negative binomial Generalized Linear Model with the predictors winter sown crops and mean patch size per plot. Model performance was assessed by Wald z-statistics with p-values, ANOVA, explained variance, theta, residuals, AIC, and independent field data. Field data was only available for one plot. Therefore, the field data only indicate model performance. The comparison of the model predictions with the field data resulted in an accuracy of 92.21%. The land use classification resulted in the following five classes: 1. winter sown crops (33985.78 ha), 2. maize (9621.36 ha), rapeseed (2952.36 ha), unidentified crops (7244.18 ha), and grassland (30720.88 ha). Grasslands were not mapped by remote sensing techniques, but taken from a digital landscape model. Accuracy assessment showed an overall accuracy of 89.16 % and 0.78 kappa statistics. Prediction of skylark territories based on the land use classification of 2011 resulted in 46269 territories, or a mean density of 8.4 territories per 10 ha on agricultural areas and 5.4 territories per 10 ha on agricultural and grassland combined areas. The scenario assumed a three partite crop rotation (maize, rapeseed, winter sown crops) and a mean value of 0.17 ha per inhabitant for food security. Areas for fodder production were considered in course of the calculation of food security because Schwäbisch Hall is characterized by many livestock farms, which made it necessary to avoid conflicts between potential bioenergy sites and areas for fodder production. Considering the above mentioned assumptions, Schwäbisch Hall has a bioenergy potential of 5955 ha for maize and 15033 ha for rapeseed cropping. The results of the bioenergy scenario were randomly distributed to the land use polygons which resulted from the remote sensing analysis. With that, prediction of skylark territories based on the bioenergy scenario was feasible. Skylark territories for the bioenergy scenario resulted in 36472 territories, or a mean value of 6.8 territories per 10 ha on agricultural areas and 4.3 territories per 10 ha on agricultural and grassland combined areas. Considering both land use options, skylark territories declined by 8797 in total numbers or by 19.43 % in relative numbers. In addition to the land use options described above, landscape structure and territory distribution were analyzed based on six landscape units (Naturräumliche Haupteinheiten) covering the municipality of Schwäbisch Hall. The analysis revealed an agriculturally dominated northwestern part, with high numbers and mean values of skylark territories, and a grassland/forest dominated southeastern part, with lower numbers and mean values of skylark territories. The relative decline of these territories between the two land use options within the landscape units resulted approximately in 22 % in the northwestern and approximately 11-15 % in the southeastern part. The results indicate that an expansion of bioenergy crops will have negative effects on breeding birds in open agricultural landscapes which already suffer from degraded habitat conditions. Based on the assumptions of this study, skylark territories will decline by approximately 20 % in comparison to 2011. Yet, considering the results of the indicator report of the German National Strategy on Biodiversity (BMU 2010) and the European Bird Census Council the baseline of 2011 already represents a degraded situation in terms of habitat quality for agricultural breeding birds.