From 35effdaa34f540769236cf74f734e6d1b533130f Mon Sep 17 00:00:00 2001 From: robinlovelace Date: Wed, 25 Sep 2024 10:07:51 +0100 Subject: [PATCH] earth -> Earth --- 01-introduction.Rmd | 2 +- 02-spatial-data.Rmd | 10 +++++----- 07-reproj.Rmd | 2 +- code/chapters/01-introduction.R | 2 +- geocompr.bib | 2 +- 5 files changed, 9 insertions(+), 9 deletions(-) diff --git a/01-introduction.Rmd b/01-introduction.Rmd index bf9e77621..201d6eb10 100644 --- a/01-introduction.Rmd +++ b/01-introduction.Rmd @@ -173,7 +173,7 @@ leaflet() |> popup = popup) ``` -```{r interactive, fig.cap="The blue markers indicate where the authors are from. The basemap is a tiled image of the earth at night provided by NASA. Interact with the online version at r.geocompx.org, for example by zooming in and clicking on the pop-ups.", out.width="100%", fig.scap="Where the authors are from.", echo=FALSE} +```{r interactive, fig.cap="The blue markers indicate where the authors are from. The basemap is a tiled image of the Earthat night provided by NASA. Interact with the online version at r.geocompx.org, for example by zooming in and clicking on the pop-ups.", out.width="100%", fig.scap="Where the authors are from.", echo=FALSE} if (knitr::is_latex_output()){ knitr::include_graphics("images/interactive.png") } else if (knitr::is_html_output()){ diff --git a/02-spatial-data.Rmd b/02-spatial-data.Rmd index 1fcd3ffe9..d67bc0f82 100644 --- a/02-spatial-data.Rmd +++ b/02-spatial-data.Rmd @@ -1051,7 +1051,7 @@ In these cases, there are two main possible solutions: (1) use of the `wrap()` f \index{CRS!introduction} Vector and raster spatial data types share concepts intrinsic to spatial data. -Perhaps the most fundamental of these is the Coordinate Reference System (CRS), which defines how the spatial elements of the data relate to the surface of the earth (or other bodies). +Perhaps the most fundamental of these is the Coordinate Reference System (CRS), which defines how the spatial elements of the data relate to the surface of the Earth (or other bodies). CRSs are either geographic or projected, as introduced at the beginning of this chapter (see Figure \@ref(fig:vectorplots)). This section explains each type, laying the foundations for Chapter \@ref(reproj-geo-data), which provides a deep dive into setting, transforming and querying CRSs. @@ -1064,10 +1064,10 @@ Geographic coordinate reference systems identify any location on the earth's sur Distances in geographic CRSs are therefore not measured in meters. This has important consequences, as demonstrated in Section \@ref(reproj-geo-data). -The surface of the earth in geographic coordinate reference systems is represented by a spherical or ellipsoidal surface. -Spherical models assume that the earth is a perfect sphere of a given radius -- they have the advantage of simplicity but, at the same time, they are inaccurate as the earth is not exactly a sphere. +The surface of the Earth in geographic coordinate reference systems is represented by a spherical or ellipsoidal surface. +Spherical models assume that the Earth is a perfect sphere of a given radius -- they have the advantage of simplicity but, at the same time, they are inaccurate as the Earth is not exactly a sphere. Ellipsoidal models are slightly more accurate, and are defined by two parameters: the equatorial radius and the polar radius. -These are suitable because the earth is compressed: the equatorial radius is around 11.5 km longer than the polar radius [@maling_coordinate_1992].^[ +These are suitable because the Earth is compressed: the equatorial radius is around 11.5 km longer than the polar radius [@maling_coordinate_1992].^[ The degree of compression is often referred to as *flattening*, defined in terms of the equatorial radius ($a$) and polar radius ($b$) as follows: $f = (a - b) / a$. The terms *ellipticity* and *compression* can also be used. Because $f$ is a rather small value, digital ellipsoid models use the 'inverse flattening' ($rf = 1/f$) to define the earth's compression. Values of $a$ and $rf$ in various ellipsoidal models can be seen by executing `sf_proj_info(type = "ellps")`. @@ -1092,7 +1092,7 @@ knitr::include_graphics("images/02_datum_fig.png") ### Projected coordinate reference systems \index{CRS!projected} -All projected CRSs are based on a geographic CRS, described in the previous section, and rely on map projections to convert the three-dimensional surface of the earth into Easting and Northing (x and y) values in a projected CRS. +All projected CRSs are based on a geographic CRS, described in the previous section, and rely on map projections to convert the three-dimensional surface of the Earth into Easting and Northing (x and y) values in a projected CRS. Projected CRSs are based on Cartesian coordinates on an implicitly flat surface (Figure \@ref(fig:vector-crs), right panel). They have an origin, x and y axes, and a linear unit of measurement such as meters. diff --git a/07-reproj.Rmd b/07-reproj.Rmd index 96bb1e0d8..441687bcd 100644 --- a/07-reproj.Rmd +++ b/07-reproj.Rmd @@ -434,7 +434,7 @@ This means that when working with local data sources, it is likely preferable to The example of London was easy to answer because (a) the British National Grid (with its associated EPSG code 27700) is well known and (b) the original dataset (`london`) already had that CRS. \index{UTM} -A commonly used default is Universal Transverse Mercator ([UTM](https://en.wikipedia.org/wiki/Universal_Transverse_Mercator_coordinate_system)), a set of CRSs that divides the earth into 60 longitudinal wedges and 20 latitudinal segments. +A commonly used default is Universal Transverse Mercator ([UTM](https://en.wikipedia.org/wiki/Universal_Transverse_Mercator_coordinate_system)), a set of CRSs that divides the Earth into 60 longitudinal wedges and 20 latitudinal segments. Almost every place on Earth has a UTM code, such as "60H" which refers to northern New Zealand where R was invented. UTM EPSG codes run sequentially from 32601 to 32660 for northern hemisphere locations and from 32701 to 32760 for southern hemisphere locations. diff --git a/code/chapters/01-introduction.R b/code/chapters/01-introduction.R index b97cc2fa6..87290c7ff 100644 --- a/code/chapters/01-introduction.R +++ b/code/chapters/01-introduction.R @@ -37,7 +37,7 @@ knitr::kable(x = d, ## popup = popup) -## ----interactive, fig.cap="The blue markers indicate where the authors are from. The basemap is a tiled image of the earth at night provided by NASA. Interact with the online version at geocompr.robinlovelace.net, for example by zooming in and clicking on the pop-ups.", out.width="100%", fig.scap="Where the authors are from.", echo=FALSE---- +## ----interactive, fig.cap="The blue markers indicate where the authors are from. The basemap is a tiled image of the Earth at night provided by NASA. Interact with the online version at geocompr.robinlovelace.net, for example by zooming in and clicking on the pop-ups.", out.width="100%", fig.scap="Where the authors are from.", echo=FALSE---- if (knitr::is_latex_output()){ knitr::include_graphics("images/interactive.png") } else if (knitr::is_html_output()){ diff --git a/geocompr.bib b/geocompr.bib index 85305b5c9..59503f8b3 100644 --- a/geocompr.bib +++ b/geocompr.bib @@ -1673,7 +1673,7 @@ @book{openshaw_geocomputation_2000 month = may, publisher = {CRC Press}, address = {London ; New York}, - abstract = {Geocomputation is essentially the follow-on revolution from Geographic Information Science and is expected to gather speed and momentum in the first decade of the 21st century. It comes into use once a GIS database has been set up, with a digital data library, and expanded and linked to a global geographical two or three dimensional co-ordinate system. It exploits developments in IT and new data gathering and earth observing technologies, and takes the notion of GIS beyond data and towards its analysis, modelling, and use in problem solving. This book provides pointers on how to harness these technologies in tandem and in the context of multiple different subjects and problem areas. It seeks to establish the principles and set the foundations for subsequent growth.L}, + abstract = {Geocomputation is essentially the follow-on revolution from Geographic Information Science and is expected to gather speed and momentum in the first decade of the 21st century. It comes into use once a GIS database has been set up, with a digital data library, and expanded and linked to a global geographical two or three dimensional co-ordinate system. It exploits developments in IT and new data gathering and Earth observing technologies, and takes the notion of GIS beyond data and towards its analysis, modelling, and use in problem solving. This book provides pointers on how to harness these technologies in tandem and in the context of multiple different subjects and problem areas. It seeks to establish the principles and set the foundations for subsequent growth.L}, isbn = {978-0-7484-0900-6}, langid = {english} }