Daftar Judul Ebook Springer Earth Environment Science

File ini berisi daftar judul ebook & link donwload terbitan Springer International Publishing Tahun 2018 yang sudah dibeli oleh Universitas Andala

Big Data Computing for Geospatial Applications

The convergence of big data and geospatial computing has brought forth challenges and opportunities to Geographic Information Science with regard to geospatial data management, processing, analysis, modeling, and visualization. This book highlights recent advancements in integrating new computing approaches, spatial methods, and data management strategies to tackle geospatial big data challenges and meanwhile demonstrates opportunities for using big data for geospatial applications. Crucial to the advancements highlighted in this book is the integration of computational thinking and spatial thinking and the transformation of abstract ideas and models to concrete data structures and algorithms

Cloud-based Virtual Reality Technology for Representing Design Guideline of Urban Residential Environment

13301甲第4156号博士（学術）金沢大学博士論文本文Ful

The Possibility of Big Data Spatio-Temporal Analytics for Understanding Human Behavior and Their Spatial Patterns in Urban Area

13301甲第4630号博士（学術）金沢大学博士論文本文Ful

The Spatiotemporal Variation Characteristics of Urban Sustainability Based on the SDGs in Yangtze River Delta, China

At present, most developing countries need to improve the quality of the built environment by means of large-scale infrastructure construction, thereby promoting rapid urbanization. The quality of the built environment ((Formula presented.)) and its environmental pressure ((Formula presented.)) have become our primary focus to achieve a globally acknowledged vision of the Sustainable Development Goals (SDGs). In this study, we proposed an overall workflow by combining the proven urban sustainability ((Formula presented.)) assessment tool with the evaluation process and the analysis of the spatiotemporal dimension to investigate the urban characteristics of the 41 cities in the Yangtze River Delta. Our results showed an upward trend of urban sustainability from 2010 to 2018, but there are still 19 cities with unsustainable urbanization processes. The megalopolis is rapidly progressing toward an imbalanced state. Specifically, the urban sustainability of the southern region performs better than the northern region, coastal cities perform better than the inland cities, and the regional peripheral cities perform better than the inner cities. Across the 41 cities in the delta, five different relational trends between (Formula presented.) and (Formula presented.) have been found to predict their future development. The results of this research will help decision-makers to coordinate the future development of regional integration between cities and to target the alleviation of the adverse chain reaction brought about by the situation of imbalance or further improving urban sustainability

Application of Cloud-based Virtual Reality Integrated Automatic Presentation Script for Understanding Urban Design Concepts

13301甲第4483号博士（学術）金沢大学博士論文本文Full 以下に掲載：International Review for Spatial Planning and Sustainable Development 3(2) pp.53-67 2015. International Community of Spatial Planning and Sustainable Development. 共著者：Yuanyi Zhang, Zhang Ying, Zhenjiang Shen, Tatsuya Nishino, Xiaojuan Che

Spatial Distribution of Urban Territories at a Regional Scale: Modeling the Changjiang Delta’s Urban Network

The formation of ‘Urban Networks’ has become a wide-spread phenomenon around the world. In the study of metropolitan regions, there are competing or diverging views about management and control of environmental and land-use factors. Especially in China, these matters, regulatory aspects, infrastructure applications, and resource allocations, are important due to population concentrations and the overlapping of urban areas with other land resources. On the other hand, the increasing sophistication of models operating on iterative computational power and widely-available spatial information and techniques make it possible to investigate the spatial distribution of urban territories at a regional scale. This thesis applies a Scenario Cellular Automata (SCA) model to the case study of the Changjiang Delta Region, which produces useful and predictive scenario-based projections within the region, using quantitative methods and baseline conditions that address issues of regional urban development. The contribution of the research includes the improvement of computer simulation of urban growth, the application of urban form and other indices to evaluate complex urban conditions, and a heightened understanding of the performance of an urban network in the Changjiang Delta Region composed of big, medium, and small-sized cities and towns

Extracting Computational Representations of Place with Social Sensing

Place-based GIS are at the forefront of GIScience research and characterized by textual descriptions, human conceptualizations as well as the spatial-semantic relationships among places. The concepts of places are difficult to handle in geographic information science and systems because of their intrinsic vagueness. They arise from the complex interaction of individuals, society, and the environment. The exact delineation of vague regions is challenging as their borders are vague and the membership within a region varies non-monotonically and as a function of context. Consequently, vague regions are difficult to handle computationally, e.g., in spatial analysis, cartography, geographic information retrieval, and GIS workflows in general. The emergence of big data brings new opportunities for us to understand the place semantics from large-scale volunteered geographic information and data streams, such as geotags, texts, activity streams, and GPS trajectories. The term "social sensing" describes such individual-level big geospatial data and the associated analysis methods. In this dissertation, I present a generalizable, data-driven framework that complements classical top-down approaches by extracting the representations of vague cognitive regions and function regions from bottom-up approaches using spatial statistics and machine learning techniques with various social sensing sources. I demonstrate how to derive crisp boundaries for cognitive and functional regions from points of interest data, and show how natural language processing techniques can enrich our understanding of places and form a foundation for the semantic characterization of place types and the generalization of regions. This work makes contributions to the development of computational methodologies for extracting vague cognitive regions and functional regions using data-driven approaches as well as the novel semantic generalization processing technique

マルチスケールの視点からみた中国における都市開発と人口移動の関係に関する研究

Development is the main problem facing cities in the world today. Urban development is inseparable from the support of labor. The population movement between regions provides a guarantee for the sustainable development of the city. Therefore, the interactive relationship between urban development and population mobility needs more in-depth research. This research combines official statistics and emerging big data to study the interactive relationship between urban development and population mobility from the macro, meso and micro levels. In addition, with the help of exploratory spatial data analysis methods, the spatial effects between urban development and population mobility can be captured, including spatial dependence and spatial heterogeneity. The use of spatial econometric models reveals the driving forces that affect population mobility. The results of the empirical analysis can provide a theoretical reference for the future development of China’s urbanization.北九州市立大