Products related to Spatial:
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Spatial Information Technology for Sustainable Development Goals
This textbook aims to develop a scientific knowledge base on spatial information technology to communicate the United Nations' Sustainable Development Goals (SDGs) among students, researchers, professionals and laymen.The book improves understanding of the spatial database and explains how to extract information from this for planning purposes.To enhance the knowledge of geoscientists and environmentalists, the book describes the basic fundamental concepts to advance techniques for spatial data management and analysis and discusses the methodology.The Geographic Information System (GIS), remote sensing and Global Positioning System (GPS) are presented in an integrated manner for the planning of resources and infrastructure.The management of these systems is discussed in a very lucid way to develop the reader's skills.The proper procedure for map making and spatial analysis are included along with case studies to the reader.Where thefirst part of the book discusses the conceptual background, the second part deals with case studies using these applications in different disciplines.The presented case studies include land use, agriculture, flood, watershed characterization and infrastructure assessment for the Sustainable Development Goals.
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Spatial Data Science
Spatial Data Science will show GIS scientists and practitioners how to add and use new analytical methods from data science in their existing GIS platforms.By explaining how the spatial domain can provide many of the building blocks, it's critical for transforming data into information, knowledge, and solutions. This book is for those using or studying GIS and the computer scientists, engineers, statisticians, and information and library scientists leading the development and deployment of data science.
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12pcs Spatial 3D Building Blocks Montessori Brain Development Spatial Reasoning Education Puzzle
12pcs Spatial 3D Building Blocks Montessori Brain Development Spatial Reasoning Education Puzzle
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An Introduction to Spatial Data Science with GeoDa : Volume 2: Clustering Spatial Data
This book is the second in a two-volume series that introduces the field of spatial data science.It moves beyond pure data exploration to the organization of observations into meaningful groups, i.e., spatial clustering.This constitutes an important component of so-called unsupervised learning, a major aspect of modern machine learning. The distinctive aspects of the book are both to explore ways to spatialize classic clustering methods through linked maps and graphs, as well as the explicit introduction of spatial contiguity constraints into clustering algorithms.Leveraging a large number of real-world empirical illustrations, readers will gain an understanding of the main concepts and techniques and their relative advantages and disadvantages.The book also constitutes the definitive user’s guide for these methods as implemented in the GeoDa open source software for spatial analysis. It is organized into three major parts, dealing with dimension reduction (principal components, multidimensional scaling, stochastic network embedding), classic clustering methods (hierarchical clustering, k-means, k-medians, k-medoids and spectral clustering), and spatially constrained clustering methods (both hierarchical and partitioning).It closes with an assessment of spatial and non-spatial cluster properties. The book is intended for readers interested in going beyond simple mapping of geographical data to gain insight into interesting patterns as expressed in spatial clusters of observations.Familiarity with the material in Volume 1 is assumed, especially the analysis of local spatial autocorrelation and the full range of visualization methods.
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Can missing spatial vision be compensated for by spatial imagination?
While spatial imagination can help individuals navigate and understand their surroundings to some extent, it may not fully compensate for missing spatial vision. Spatial imagination relies on mental imagery and memory, which may not always accurately represent the physical environment. Missing spatial vision can impact an individual's ability to perceive depth, distance, and obstacles in their surroundings, which may not be fully compensated for by imagination alone. However, individuals can develop strategies and adaptive skills to enhance their spatial awareness and compensate for their visual impairment to some degree.
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What is the difference between spatial planning and spatial planning?
Spatial planning and urban planning are closely related but have different focuses. Spatial planning is a broader concept that encompasses the organization and management of land use and resources at a regional, national, or even global scale. It involves the strategic allocation of land for various purposes such as housing, transportation, agriculture, and conservation. On the other hand, urban planning specifically deals with the development and organization of urban areas, including the design of infrastructure, public spaces, and buildings within cities and towns. While spatial planning considers a larger geographical area, urban planning is more focused on the specific needs and challenges of urban environments.
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What effect does the spatial representation or spatial arrangement have?
The spatial representation or spatial arrangement of objects can have a significant impact on how we perceive and interact with our environment. It can influence our sense of orientation, navigation, and wayfinding, as well as our understanding of the relationships between objects and spaces. Additionally, spatial arrangement can affect the flow of movement and the distribution of resources within a given space. Overall, the spatial representation or arrangement plays a crucial role in shaping our experiences and interactions within physical and virtual environments.
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What is spatial vision?
Spatial vision refers to the ability of the visual system to perceive and interpret the spatial relationships between objects in the environment. It allows us to understand the size, shape, distance, and location of objects in our surroundings. Spatial vision is essential for tasks such as navigating through space, interacting with objects, and judging depth and perspective. It is a complex process that involves the integration of visual information from both eyes to create a coherent representation of the three-dimensional world.
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An Introduction to Spatial Data Science with GeoDa : Volume 1: Exploring Spatial Data
This book is the first in a two-volume series that introduces the field of spatial data science.It offers an accessible overview of the methodology of exploratory spatial data analysis.It also constitutes the definitive user’s guide for the widely adopted GeoDa open-source software for spatial analysis.Leveraging a large number of real-world empirical illustrations, readers will gain an understanding of the main concepts and techniques, using dynamic graphics for thematic mapping, statistical graphing, and, most centrally, the analysis of spatial autocorrelation.Key to this analysis is the concept of local indicators of spatial association, pioneered by the author and recently extended to the analysis of multivariate data. The focus of the book is on intuitive methods to discover interesting patterns in spatial data.It offers a progression from basic data manipulation through description and exploration to the identification of clusters and outliers by means of local spatial autocorrelation analysis.A distinctive approach is to spatialize intrinsically non-spatial methods by means of linking and brushing with a range of map representations, including several that are unique to the GeoDa software.The book also represents the most in-depth treatment of local spatial autocorrelation and its visualization and interpretation by means of GeoDa. The book is intended for readers interested in going beyond simple mapping of geographical data to gain insight into interesting patterns.Some basic familiarity with statistical concepts is assumed, but no previous knowledge of GIS or mapping is required. Key Features:• Includes spatial perspectives on cluster analysis• Focuses on exploring spatial data• Supplemented by extensive support with sample data sets and examples on the GeoDaCenter websiteThis book is both useful as a reference for the software and as a text for students and researchers of spatial data science.
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Spatial Data Science : With Applications in R
Spatial Data Science introduces fundamental aspects of spatial data that every data scientist should know before they start working with spatial data.These aspects include how geometries are represented, coordinate reference systems (projections, datums), the fact that the Earth is round and its consequences for analysis, and how attributes of geometries can relate to geometries.In the second part of the book, these concepts are illustrated with data science examples using the R language.In the third part, statistical modelling approaches are demonstrated using real world data examples.After reading this book, the reader will be well equipped to avoid a number of major spatial data analysis errors. The book gives a detailed explanation of the core spatial software packages for R: sf for simple feature access, and stars for raster and vector data cubes – array data with spatial and temporal dimensions.It also shows how geometrical operations change when going from a flat space to the surface of a sphere, which is what sf and stars use when coordinates are not projected (degrees longitude/latitude).Separate chapters detail a variety of plotting approaches for spatial maps using R, and different ways of handling very large vector or raster (imagery) datasets, locally, in databases, or in the cloud.The data used and all code examples are freely available online from https://r-spatial.org/book/.The solutions to the exercises can be found here: https://edzer.github.io/sdsr_exercises/.
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Spatial Analysis
SPATIAL ANALYSIS Explore the foundations and latest developments in spatial statistical analysis In Spatial Analysis, two distinguished authors deliver a practical and insightful exploration of the statistical investigation of the interdependence of random variables as a function of their spatial proximity.The book expertly blends theory and application, offering numerous worked examples and exercises at the end of each chapter.Increasingly relevant to fields as diverse as epidemiology, geography, geology, image analysis, and machine learning, spatial statistics is becoming more important to a wide range of specialists and professionals.The book includes: Thorough introduction to stationary random fields, intrinsic and generalized random fields, and stochastic modelsComprehensive exploration of the estimation of spatial structurePractical discussion of kriging and the spatial linear model Spatial Analysis is an invaluable resource for advanced undergraduate and postgraduate students in statistics, data science, digital imaging, geostatistics, and agriculture.It’s also an accessible reference for professionals who are required to use spatial models in their work.
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Spatial Violence
This book poses spatial violence as a constitutive dimension of architecture and its epistemologies, as well as a method for theoretical and historical inquiry intrinsic to architecture; and thereby offers an alternative to predominant readings of spatial violence as a topic, event, fact, or other empirical form that may be illustrated by architecture.Exploring histories of and through architecture at sites across the globe, the chapters in the book blur the purportedly distinctive borders between war and peace, framing violence as a form of social, political, and economic order rather than its exceptional interruption.Regarding space and violence as co-constitutive, the book’s collected essays critique modernization and capitalist accumulation as naturalized modes for the extraction of violence from everyday life.Focusing on the mediation of violence through architectural registers of construction, destruction, design, use, representation, theory, and history, the book suggests that violence is not only something inflicted upon architecture, but also something that architecture inflicts.In keeping with Walter Benjamin’s formulation that there is no document of civilization that is not also a document of barbarism, the book offers "spatial violence" as another name for "architecture" itself.This book was previously published as a special issue of Architectural Theory Review.
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What is spatial thinking?
Spatial thinking is the ability to understand and interpret the world in terms of space and location. It involves the mental manipulation and organization of spatial information, such as maps, diagrams, and geometric shapes. Spatial thinking allows individuals to visualize and navigate through physical and abstract spaces, and to solve problems related to spatial relationships and patterns. It is a fundamental skill in fields such as geography, architecture, engineering, and urban planning.
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What is spatial reasoning?
Spatial reasoning is the ability to understand and manipulate visual information about objects and their relationships in space. It involves skills such as mental rotation, visualization, and understanding of spatial patterns. People with strong spatial reasoning skills can easily interpret and create visual representations, understand maps and diagrams, and solve problems involving spatial relationships. This ability is important in fields such as mathematics, engineering, architecture, and design.
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What is spatial music?
Spatial music is a type of music composition and performance that takes into consideration the physical space in which it is being presented. It involves the manipulation of sound in three-dimensional space, often using multiple speakers or surround sound systems to create an immersive listening experience. Spatial music can involve the movement of sound sources, the placement of speakers throughout a performance space, and the use of technology to control the spatial distribution of sound. This approach allows for a more dynamic and interactive relationship between the music and the listener, as the spatial elements can enhance the emotional impact and create a sense of envelopment.
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What is spatial bridging?
Spatial bridging refers to the process of connecting different geographical areas or spaces in order to facilitate communication, interaction, and exchange of resources. This can involve physical infrastructure such as roads, bridges, and transportation networks, as well as digital infrastructure such as internet connectivity and communication technologies. Spatial bridging is important for promoting economic development, social integration, and cultural exchange between different regions and communities. It helps to overcome geographical barriers and create a more interconnected and accessible world.
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