Monograph10.53061/HCED6492
An Introduction to Spatial Data Analysis
Martin Wegmann,Jakob Schwalb-Willmann,Stefan Dech +2 more
- 07 Sep 2020
122
TL;DR: An Introduction to Spatial Data Analysis introduces spatial data handling using the open source software Quantum GIS (QGIS) and R, empowering the reader to turn data acquired in the field into actual spatial data.
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Abstract: This is a book about how ecologists can integrate remote sensing and GIS in their research. It will allow readers to get started with the application of remote sensing and to understand its potential and limitations. Using practical examples, the book covers all necessary steps from planning field campaigns to deriving ecologically relevant information through remote sensing and modelling of species distributions. An Introduction to Spatial Data Analysis introduces spatial data handling using the open source software Quantum GIS (QGIS). In addition, readers will be guided through their first steps in the R programming language. The authors explain the fundamentals of spatial data handling and analysis, empowering the reader to turn data acquired in the field into actual spatial data. Readers will learn to process and analyse spatial data of different types and interpret the data and results. After finishing this book, readers will be able to address questions such as “What is the distance to the border of the protected area?”, “Which points are located close to a road?”, “Which fraction of land cover types exist in my study area?” using different software and techniques. This book is for novice spatial data users and does not assume any prior knowledge of spatial data itself or practical experience working with such data sets. Readers will likely include student and professional ecologists, geographers and any environmental scientists or practitioners who need to collect, visualize and analyse spatial data. The software used is the widely applied open source scientific programs QGIS and R. All scripts and data sets used in the book will be provided online at book.ecosens.org. This book covers specific methods including: what to consider before collecting in situ data how to work with spatial data collected in situ the difference between raster and vector data how to acquire further vector and raster data how to create relevant environmental information how to combine and analyse in situ and remote sensing data how to create useful maps for field work and presentations how to use QGIS and R for spatial analysis how to develop analysis scripts
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Citations
Urban and air pollution: a multi-city study of long-term effects of urban landscape patterns on air quality trends.
TL;DR: This empirical study identifies the key urban form determinants of decadal-long fine particulate matter (PM2.5) trends in all 626 Chinese cities at the county level and above and suggests that, depending on the city’s developmental stage, different aspects of the urban form should be emphasized to achieve long-term clean air goals.
Spatiotemporal pattern of COVID-19 and government response in South Korea (as of May 31, 2020).
Sun Kim,Marcia C. Castro +1 more
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120
COVID-19 no município do Rio de Janeiro: análise espacial da ocorrência dos primeiros casos e óbitos confirmados
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Vineyard Variability Analysis through UAV-Based Vigour Maps to Assess Climate Change Impacts
Luís Pádua,Pedro Marques,Telmo Adão,Nathalie Guimarães,António Sousa,Emanuel Peres,Joaquim J. Sousa +6 more
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65
Remote sensing and GIS techniques for reconstructing the military fort system on the Roman boundary (Tunisian section) and identifying archaeological sites
TL;DR: In this paper, the authors combined high-resolution remote sensing (RS) imagery with in situ investigations to assess the suspected archaeological sites detected using satellite data and historical documentation, according to the geometric features of the sites as they appeared in the remotely sensed imagery these sites had not been detected during earlier field investigations.
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TL;DR: In this paper, a simplified computational scheme is given and extended to mixed regressive-autoregressive models for spatial interaction, and the ML estimator is compared with several alternatives.
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The Moran scatterplot as an ESDA tool to assess local instability in spatial association
Luc Anselin
- 13 Mar 2019
TL;DR: The Moran scatterplot as mentioned in this paper is a simple tool to visualise and examine the degree of spatial instability in spatial association by means of Moran's I.I.D., which is used for exploratory spatial data analysis, in the sense of spatial dependence and spatial heterogeneity.
566
Interactive Techniques and Exploratory Spatial Data Analysis
Luc Anselin
- 01 Jan 1996
Abstract: This chapter reviews the ideas behind interactive and exploratory spatial data analysis and their relation to GIS. Three important aspects are considered. First, an overview is presented of the principles behind interactive spatial data analysis, based on
Spatial Analysis and GIS
TL;DR: The integration of GIS Reference Record with Geographic Information System (GIS) Reference Record is described in detail in the second part of this presentation.
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