Urban Tree Detection in Historical Aerial Imagery of Sweden

Urban trees are a key component of the urban environment. In Sweden, ambitious goals have been expressed by authorities regarding the retention and increase of urban tree cover, aiming to mitigate climate change and provide a healthy, livable urban environment in a highly contested space. Tracking urban tree cover through remote sensing serves as an indicator of how past urban planning has succeeded in retaining trees as part of the urban fabric, and historical imagery spanning back decades for such analysis is widely available. This short study examines the viability of automated detection using open-source Deep Learning methods for long-term change detection in urban tree cover, aiming to evaluate past practices in urban planning. Results indicate that preprocessing of old imagery is necessary to enhance the detection and segmentation of urban tree cover, as the currently available training models were found to be severely lacking upon visual inspection

From AI with Love: Reading Big Data Poetry through Gilbert Simondon’s Theory of Transduction

Computation initiated a far-reaching re-imagination of language, not just as an information tool, but as a social, bio-physical activity in general. Modern lexicology provides an important overview of the ongoing development of textual documentation and its applications in relation to language and linguistics. At the same time, the evolution of lexical tools from the first dictionaries and graphs to algorithmically generated scatter plots of live online interaction patterns has been surprisingly swift. Modern communication and information studies from Norbert Weiner to the present-day support direct parallels between coding and linguistic systems. However, most theories of computation as a model of language use remain highly indefinite and open-ended, at times purposefully ambiguous. Comparing the use of computation and semantic technologies ranging from Christopher Strachey’s early love letter templates to David Jhave Johnson’s more recent experiments with artificial neural networks (ANNs), this paper proposes the philosopher Gilbert Simondon’s theory of transduction and metastable systems as a suitable framework for understanding various ontological and epistemological ramifications in our increasingly complex and intimate interactions with machine learning. Such developments are especially clear, I argue, in the poetic reimagining of language as a space of cybernetic hybridity. initiated a far-reaching re-imagination of language, not just as an information tool, but as a social, bio-physical activity in general. Modern lexicology provides an important overview of the ongoing development of textual documentation and its applications in relation to language and linguistics. At the same time, the evolution of lexical tools from the first dictionaries and graphs to algorithmically generated scatter plots of live online interaction patterns has been surprisingly swift. Modern communication and information studies from Norbert Weiner to the present-day support direct parallels between coding and linguistic systems. However, most theories of computation as a model of language use remain highly indefinite and open-ended, at times purposefully ambiguous. Comparing the use of computation and semantic technologies ranging from Christopher Strachey’s early love letter templates to David Jhave Johnson’s more recent experiments with artificial neural networks (ANNs), this paper proposes the philosopher Gilbert Simondon’s theory of transduction and metastable systems as a suitable framework for understanding various ontological and epistemological ramifications in our increasingly complex and intimate interactions with machine learning. Such developments are especially clear, I argue, in the poetic reimagining of language as a space of cybernetic hybridity. Keywords: Artificial Intelligence, Poetics, Neural Networks, Information Studies, Computation, Linguistics, Transduction, Philosoph

Competitive Interactions between Appalachian Hardwoods and Different Groundcovers on Reclaimed Mine Sites

Coal mining is a significant industry in Appalachia. Herbaceous groundcovers are commonly planted to reduce soil erosion and protect water quality during mine reclamation, but many groundcovers may be too competitive to be compatible with trees. The objectives of this research were to investigate the performance of trees planted within different groundcovers and to measure how different groundcovers influence resource availability, specifically soil moisture and light Two studies were performed; one in a greenhouse and the other on 3 mine sites in east Tennessee where seedlings were planted and grown in competition with different groundcovers. Growth, biomass, leaf area, and foliar transpiration of tree seedlings, percent cover of groundcovers, percent volumetric soil moisture, and photosynthetically active radiation (PAR) were measured. In the greenhouse, root-to-shoot ratios of northern red oak seedlings in the presence of competition from switchgrass and in bare treatments were found to be greater than in alfalfa and annual rye treatments. Specific leaf area of seedlings in the annual rye treatment was found to be lower than the other treatments. Seedlings in the bare and switchgrass treatments were found to have greater transpiration rates than in the annual rye and alfalfa treatments. On the mine sites, growth and transpiration of northern red oak, American chestnut, black cherry, and shagbark hickory seedlings did not differ among groundcover treatments. In both studies, percent soil moisture was found to be greatest in the bare and switchgrass treatments, and percent full PAR at 14 cm was found to be greatest in the bare treatment. In the greenhouse, percent full PAR was lowest in the switchgrass treatment and was lowest in the alfalfa treatment in the field. Many factors may explain differences in seedling growth and performance between the greenhouse study and the field study such as tremendous variability in substrates and percent groundcover in the field, micro-site influence, and other unknown factors. Results from this study suggest that of the groundcover species studied, switchgrass may be the most compatible with the hardwoods studied, but more research is warranted to definitively determine the competitive interactions between the tree and groundcover species studied