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Chapter 9 Making maps with R | Geocomputation with R
Chapter 9 Making maps with R | Geocomputation with R
Prerequisites This chapter requires the following packages that we have already been using: library(sf) library(terra) library(dplyr) library(spData) library(spDataLarge) The main package used in...
·r.geocompx.org·
Chapter 9 Making maps with R | Geocomputation with R
Understanding Your Topographic Map Maker
Understanding Your Topographic Map Maker
The first-ever topographic maps were said to have been formed by the British in the late 18th century, and soon after, the US followed suit. Back then, the US had a department called the “Topographical Bureau of the Army,” which used these maps to plan tactical strategies during the War of 1812. However, even when the war ended, our interest in topography remained.
The term “topography” comes from a combination of two Greek words: “topo,” which means place, and “graphia,” which means writing. It is used to describe the study of a region’s forms and features, primarily to show their relative positions and elevations. Topography could refer to the forms and features themselves or a depiction of them (such as a map).
Unlike traditional maps which only represent the land horizontally, one made with a topographic map maker will represent the land vertically as well. These maps, also referred to as topo maps, show the form and elevation of an area, including the location and shape of hills, valleys, mountains, streams, and other natural or human-made features.
Contour Lines
Contour lines are the primary way in which topographic maps depict elevation. These imaginary lines connect points of equal elevation in order to present three-dimensional information on a two-dimensional map. This allows the viewer to visualize the height and shape of mountains, the depth of canyons, and the location of flat plains.  To determine the exact elevation of a location, you’ll need to know the contour interval – the difference in elevation between two contour lines. This will vary depending on the map, but regardless, you can calculate them yourself fairly easily. First, find the bolded contour lines that contain a number. These are the index contours, and the number is the elevation at the line.  Then, count the number of contour lines between each index contour, and divide the difference in elevation by that number. For instance, if you had one index contour with an elevation of 7,800 five contour lines apart from another index with an elevation of 8,000, the contour interval would be 40 ( (8,000 - 7,800) / 5 = 40 ).
The contour lines produced by your topographic map maker are often used to determine the slope or steepness of an area. The lines will be spaced farther apart when the slope is gentle, and closer together when the slope is steep. This is because, in steep areas, the elevation will increase at a greater frequency, so the lines will appear closer together. A completely flat meadow will have no contour lines, while a vertical cliff will have contour lines that are stacked on top of one another.
Features
You can also use contour lines to identify features of the land.  Peaks and Depressions: The innermost ring at the center of several other rings will typically represent a peak, but in some cases, it could represent a depression. Valleys: A valley is a type of depression in which water could flow down (if water is present), and they can be identified by their V or U shaped contour lines that point towards higher elevation (the peak). Cliffs: When two or more lines join together to form a single line, they represent a cliff. However, if the change in elevation isn’t great enough to call for another contour line, the cliff may not appear on the map. Ridges: A ridge is a chain of mountains or hills that create a continuous summit for an extended distance. These can be identified by V or U shaped contours that point towards lower elevation.  Saddles: A saddle is a low spot between two higher points of elevation, and on a topographic map, they appear as hourglass shaped contour lines.
·id.land·
Understanding Your Topographic Map Maker
Chapter 9 Use httptest2 | HTTP testing in R
Chapter 9 Use httptest2 | HTTP testing in R
In this chapter we aim at adding HTTP testing infrastructure to exemplighratia2 using httptest2. For this, we start from the initial state of exemplighratia2 again. Back to square one!...
·books.ropensci.org·
Chapter 9 Use httptest2 | HTTP testing in R
Intro to GIS and Spatial Analysis
Intro to GIS and Spatial Analysis
This is a compilation of lecture notes that accompany my Intro to GIS and Spatial Analysis course.
·mgimond.github.io·
Intro to GIS and Spatial Analysis
Welcome | Geocomputation with R
Welcome | Geocomputation with R
Welcome | Geocomputation with R is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization, and geospatial capabilities. The book equips you with the knowledge and skills to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. This book will interest people from many backgrounds, especially Geographic Information Systems (GIS) users interested in applying their domain-specific knowledge in a powerful open source language for data science, and R users interested in extending their skills to handle spatial data.
·r.geocompx.org·
Welcome | Geocomputation with R
Introduction | Engineering Production-Grade Shiny Apps
Introduction | Engineering Production-Grade Shiny Apps
A book about engineering shiny application that will later be sent to production. This book cover project management, structuring your project, building a solid testing suite, and optimizing your codebase. We describe in this book a specific workflow: design, prototype, build, strengthen and deploy.
·engineering-shiny.org·
Introduction | Engineering Production-Grade Shiny Apps
Writing R extensions
Writing R extensions
Writing R Extensions covers how to create your own packages, write R help files, and the foreign language (C, C++, Fortran, …) interfaces.
·colinfay.me·
Writing R extensions
R for Excel Users
R for Excel Users
This is a workshop for RStudio::conf(2020) in San Francisco, California
·rstudio-conf-2020.github.io·
R for Excel Users
Field Guide to the R Ecosystem
Field Guide to the R Ecosystem
This guide aims to introduce the reader to the main elements of the R ecosystem.
·fg2re.sellorm.com·
Field Guide to the R Ecosystem
Efficient R programming
Efficient R programming
Efficient R Programming is about increasing the amount of work you can do with R in a given amount of time. It’s about both computational and programmer efficiency.
·csgillespie.github.io·
Efficient R programming
Cookbook for R
Cookbook for R
This site is powered by knitr and Jekyll. If you find any errors, please email winston@stdout.org
·cookbook-r.com·
Cookbook for R
rOpenSci Packages: Development, Maintenance, and Peer Review
rOpenSci Packages: Development, Maintenance, and Peer Review
Extended version of the rOpenSci packaging guide. This book is a guide for authors, maintainers, reviewers and editors of rOpenSci. The first section of the book contains our guidelines for creating and testing R packages. The second section is dedicated to rOpenSci’s software peer review process: what it is, our policies, and specific guides for authors, editors and reviewers throughout the process. The third and last section features our best practice for nurturing your package once it has been onboarded: how to collaborate with other developers, how to document releases, how to promote your package and how to leverage GitHub as a development platform. The third section also features a chapter for anyone wishing to start contributing to rOpenSci packages.
·devguide.ropensci.org·
rOpenSci Packages: Development, Maintenance, and Peer Review