Recent studies have shown that permafrost soils in the northern circumpolar region store almost twice as much carbon as the atmosphere. Since soil organic carbon (SOC) pools have large regional and landscape-level variability, detailed SOC inventories from across the northern permafrost region are needed to assess potential remobilization of SOC with permafrost degradation and to quantify the permafrost carbon-climate feedback on global warming. This thesis provides high-resolution data on SOC storage in five study areas located in undersampled regions of the continuous permafrost zone (Zackenberg in NE Greenland; Shalaurovo and Cherskiy in NE Siberia; Ary-Mas and Logata in Taymyr Peninsula). The emphasis throughout the five different study areas is put on SOC partitioning within the landscape and soil horizon levels as well as on soil forming processes under periglacial conditions. Our results indicate large differences in mean SOC 0–100 cm storage among study areas, ranging from 4.8 to 30.0 kg C m-2, highlighting the need to consider numerous factors as topography, geomorphology, land cover, soil texture, soil moisture, etc. in the assessment of landscape-level and regional SOC stock estimates. In the high arctic mountainous area of Zackenberg, the mean SOC storage is low due to the high proportion of bare grounds. The geomorphology based upscaling resulted in a c. 40% lower estimate compared to a land cover based upscaling (4.8 vs 8.3 kg C m-2, respectively). A landform approach provides a better tool for identifying hotspots of SOC burial in the landscape, which in this area corresponds to alluvial fan deposits in the foothills of the mountains. SOC burial by cryoturbation was much more limited and largely restricted to soils in the lower central valley. In the lowland permafrost study areas of Russia the mean SOC 0–100 cm storage ranged from 14.8 to 30.0 kg C m-2. Cryoturbation is the main burial process of SOC, storing on average c. 30% of the total landscape SOC 0–100 cm in deeper C-enriched pockets in all study areas. In Taymyr Peninsula, the mean SOC storage between the Ary-Mas and Logata study areas differed by c. 40% (14.8 vs 20.8 kg C m-2, respectively). We ascribe this mainly to the finer soil texture in the latter study area. Grain size analyses show that cryoturbation is most prominent in silt loam soils with high coarse silt to very fine sand fractions. However, in profiles and samples not affected by C-enrichment, C concentrations and densities were higher in silt loam soils with higher clay to medium silt fractions. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 3: Manuscript. Paper 4: Manuscript.</p>

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The thesis content study of land use in municipality Lelekovice and its connection with software for geographic information system. It describes processing data especially historical cadastre maps, archival aerial imagery and orthophotos which were used for analyzing of this area. Analysis were performed in software ArcGIS. Appendixes of thesis are graphs and visualization of development of study area.

Charles University in Prague Faculty of Science Department of Social Geography and Regional Development Robin Rašín The Landscape of the Czech-Austrian Borderland: Development and Heritage Summary Roztoky u Křivoklátu 2010 1 Landscape is a key geographical concept and geographical research on land change and land use has a tradition that can be dated back for almost a hundred years. The development of the subject orientation of land change science can be divided into two phases. (i) During the first phase (50's/60's of the 20th century) the description of landscape and its morphology (structure) were at the centre of research interest along with the research of the potential for agro-production. This particular type of study was motivated by the need to find a solution to the problem of the increasing inability to supply a growing (European) population with agricultural products. (ii) In the second phase (circa from 70's of the 20th century), the attention of scientists towards the accelerated rate of land change on a global scale that can be associated with: the increase of human population, changes in agricultural techniques, mining, environmental exploitation et cetera. There is an obvious need to solve the negative impacts of the human activities on the landscape at different scales (from local to...

>Magister Scientiae - MSc / Wetlands are unique ecosystems that are acknowledged among the world’s most productive and valuable ecosystems. They are recognized as being essential to sustainable development and human welfare due to their unique environmental and socio-economic value. These highly productive ecosystems provide functions such as recycling of nutrients, watershed protection and flood control as well as grazing resources. Wetlands provide the basis for human livelihoods in Africa through ecosystem services. However, these ecosystems are affected by internal and external factors within and outside their catchments, hence the importance of monitoring those changes around these wetlands. The aim of this study was to identify the major land use and land cover changes (LULC) from two selected wetlands (i.e. Makuleke and Nyslvei) and their impacts on water quality within the Limpopo Transboundary River Basin, South Africa. To achieve this aim, firstly the study assessed the impacts of LULC changes on these two wetlands between 2014 and 2018. Multi-date Landsat series data were used to map and estimate the rate of LULC changes in Makuleke and Nylsvlei wetland ecosystems during the study period. The results obtained showed that the spatial extent of Makuleke declined by 2% between 2014 and 2018, whereas the Nylsvlei wetland decreased by 3%. Some of the noticeable changes were that the coverage of natural vegetation tends to increase during the wet seasons. Secondly, Chlorophyll-a was predicted and mapped for Makuleke and Nysvlei between September 2018 and June 2019. Moderate resolution Landsat 8 images and in-situ field measurements were used to estimate and map chlorophyll-a concentrations from these two wetlands. Landsat-derived chlorophyll-a concentrations were validated using field-derived chlorophyll-a measurements. The results showed a variation of chl-a concentration in these two wetlands, with Makuleke wetlands concentrations ranging from 0 to 1.15 μg/L whereas for Nylsvlei wetland the ranges varied between 0 and 1.42μg/L. The finding of this study can be used in enforcing of wetland legislation and LULC management practices and highlights the relevance of remotely sensed data in assessing and routine monitoring wetland water quality.

<p>Tropical ecosystems play a key role in regulating the global climate and the carbon cycle thanks to the large amounts of water and carbon exchanged with the atmosphere. These biogeochemical fluxes are largely the result of high photosynthetic rates. Photosynthetic activity is highly dependent on climate and vegetation, and therefore can be easily modified along with changes in those two factors. A better understanding of what drives or alters photosynthetic activity in the tropics will lead to more accurate predictions of climate and subsequent effects on ecosystems. The seasonal pattern of photosynthetic activity is one of the main uncertainties that we still have about tropical ecosystems. However, this seasonality of tropical vegetation and its relationship to climate change and land cover is key to understanding how these ecosystems could be affected and have an effect on climate.</p><p>In this dissertation, I present three projects to improve our understanding about tropical ecosystems and how their photosynthetic activity is affected by climate and land cover change. The lack of field-based data has been one of the main limiting factors in our study of tropical ecosystems. Therefore, in these projects I extensively use remote sensing-derived data to analyze large scale and long term patterns. In the first study, I looked at the seasonal relationship between photosynthetic activity and climate, and how model simulations represent it. Vegetation in most of the tropics is either positively correlated with both water and light, or positively correlated with one of them and negatively with the other. Ecosystem models largely underestimate positive correlations with light and overestimate positive correlations with water. In the second study, I focus on the effect of land cover change in photosynthetic activity and transpiration in a highly deforested region in the Amazon. I find that land cover change decreases tropical forests photosynthetic activity and transpiration during the dry season. Also, land cover change increases the range of photosynthetic activity and transpiration in forests and shrublands. These effects are intensified with increasing land cover change. In the last project, I quantify the amount of change in evapotranspiration due to land cover change in the entire Amazon basin. Our remote sensing-derived estimates are well aligned with model predictions published in the past three decades. These results increase our confidence in climate models representation of evapotranspiration in the Amazon.</p><p>Findings from this dissertation highlight (1) the importance of the close relationship between climate and photosynthetic activity and (2) how land cover change is altering that relationship. We hope our results can build on our knowledge about tropical ecosystems and how they could change in the future. We also expect our analysis to be used for model benchmarking and tropical ecosystem monitoring.</p>

The creation and classification of segments for object based urban land cover mapping is the key goal of this master thesis. An algorithm based on region growing and merging was developed, implemented and tested. The synergy effects of a fused data set of SAR and optical imagery were evaluated based on the classification results. The testing was mainly performed with data of the city of Beijing China. The dataset consists of SAR and optical data and the classified land cover/use maps were evaluated using standard methods for accuracy assessment like confusion matrices, kappa values and overall accuracy. The classification for the testing consists of 9 classes which are low density buildup, high density buildup, road, park, water, golf course, forest, agricultural crop and airport. The development was performed in JAVA and a suitable graphical interface for user friendly interaction was created parallel to the development of the algorithm. This was really useful during the period of extensive testing of the parameter which easily could be entered through the dialogs of the interface. The algorithm itself treats the pixels as a connected graph of pixels which can always merge with their direct neighbors, meaning sharing an edge with those. There are three criteria that can be used in the current state of the algorithm, a mean based spectral homogeneity measure, a variance based textural homogeneity measure and fragmentation test as a shape measure. The algorithm has 3 key parameters which are the minimum and maximum segments size as well as a homogeneity threshold measure which is based on a weighted combination of relative change due to merging two segments. The growing and merging is divided into two phases the first one is based on mutual best partner merging and the second one on the homogeneity threshold. In both phases it is possible to use all three criteria for merging in arbitrary weighting constellations. A third step is the check for the fulfillment of minimum size which can be performed prior to or after the other two steps. The segments can then in a supervised manner be labeled interactively using once again the graphical user interface for creating a training sample set. This training set can be used to derive a support vector machine which is based on a radial base function kernel. The optimal settings for the required parameters of this SVM training process can be found from a cross-validation grid search process which is implemented within the program as well. The SVM algorithm is based on the LibSVM java implementation. Once training is completed the SVM can be used to predict the whole dataset to get a classified land-cover map. It can be exported in form of a vector dataset. The results yield that the incorporation of texture features already in the segmentation is superior to spectral information alone especially when working with unfiltered SAR data. The incorporation of the suggested shape feature however doesn’t seem to be of advantage, especially when taking the much longer processing time into account, when incorporating this criterion. From the classification results it is also evident, that the fusion of SAR and optical data is beneficial for urban land cover mapping. Especially the distinction of urban areas and agricultural crops has been improved greatly but also the confusion between high and low density could be reduced due to the fusion. / Dragon 2 Project

Seston is the complex of organic and inorganic particles suspended in the water column in stream ecosystems. This detrital pool is a significant vector of energy and nutrients from headwaters to the ocean. Many of the processes involved in seston generation in streams involve the terrestrial ecosystems they drain. My objective was to determine how land use influences seston quality. Seston was collected from 9 streams along a gradient of catchment forest cover, draining 3 land-use categories: forested, agricultural, and residential. Quality variations were determined through the physical composition (size classes and concentration), chemical composition (carbon, nitrogen, and phosphorous) and organic content of seston, as well as microbial respiration of associated assemblages and growth rates of Chironomus tentans fed seston. There was more seston in streams draining less forested catchments but proportionally that material was less organic. Ultrafine particles dominated seston size classes at all sites and was higher in streams with less catchment forest cover. Phosphorous content of seston, as a % of ash free dry mass, and dissolved P in the water were higher in more disturbed streams, and C:N and N:P ratios of seston were higher in forested streams. Microbial respiration and instantaneous growth rates of C. tentans were highest on residential seston, indicating seston from those streams was more bioavailable. These results indicate that the quality of seston in stream ecosystems is linked to terrestrial processes and influenced by land use. / Master of Science

The Chocó-Darien Global Ecoregion (CGE) in South America is one of 25 global biodiversity hotspots prioritized for conservation. I performed the first land-use and land-cover (LULC) change analysis for the entire CGE in this dissertation. There were three main objectives: 1) Select the best available imagery to build annual land-use and land-cover maps from 2001 to 2015 across the CGE. 2) Model LULC across the CGE to assess forest change trends from 2002 to 2015 and identify the effect of proximate causes of deforestation and reforestation. 3) Estimate the effects of underlying drivers on deforestation and reforestation across the CGE between 2002 and 2015. I developed annual LULC maps across the CGE from 2002 to 2015 using MODIS (Moderate Resolution Imaging Spectro radiometer) vegetation index products and random forest classification. The LULC maps resulted in high accuracies (Kappa = 0.87; SD = 0.008). We detected a gradual replacement of forested areas with agriculture and secondary vegetation (agriculture reverting to early regeneration of natural vegetation) across the CGE. Forest loss was higher between 2010-2015 when compared to 2002-2010. LULC change trends, proximate causes, and reforestation transitions varied according to administrative authority (countries: PanamanianCGE, Colombian CGE, and Ecuadorian CGE). Population growth and road density were underlying drivers of deforestation. Armed conflicts, Gross Domestic Product, and average annual rain were proximate causes and underlying drivers related reforestation.

The Image-based Change Estimation program (ICE) was developed by the US Forest Service Forest Inventory & Analysis (FIA) program and the Geospatial Technology Applications Center in response to the 2014 Farm Bill calling for more timely and accurate estimates of land cover and use change. ICE monitors change throughout the US on a state by state basis by assessing each FIA plot using high resolution imagery from two dates in time. In the western US, FIA measures 10% of the plots each year to report on status, trends, and sustainability of our Nation’s forests. However, this 10 year cycle misses disturbances because a temporal gap occurs from disturbance event to measurement. This study compares field- and image-based observations of land cover and use change to improve sampling procedures in Utah. Image-based data collected from 2011 and 2014 imagery and field-based plots measured between 2011 and 2016 are compared using three methods to compile the ICE data, termed hierarchical, majority, and point center, to determine a standardized system and better understand their relationships. Additionally, ICE change agents were compared with causes of tree mortality observed on FIA forest plots to assess how well ICE evaluates causes of change and the differences of change vs. mortality agents were explored by conducting a second review of the imagery to find trends in data discrepancies. This knowledge can help image interpreters better recognize and identify change.