geographical/geospatial 地图与 maps() - R
geographical/geospatial map with maps() - R
我已经经历了很多问题和文档，并且由于您需要付费才能使用 ggmaps()（因为 google 云服务）我开始寻找替代方案。我找到了 maps()，我正在尝试调整 解决方案：
data %>%
rename(x = longitud, y = latitud) %>%
ggplot() +
geom_polygon(aes(x = long, y = lat), data = map_data("world")) +
geom_point(aes(x = x, y = y))
但是，我遇到了一些问题：
- 如果你绘制上面的代码，你会得到正确的绘图点（智利），但是世界地图打印错误（见上图）。
- 我不需要灰色地图或彩色地图。我只需要用一种正常的格式绘制国家智利（例如，google 地图卫星）。坐标是 lakes/mountains 的流，我想看看是否可以按某些视觉扇区对它们进行聚类。
- 我只需要一张智利的地图，但由于我没有找到，所以我正在使用这张世界地图。有没有办法在不丢失与地图坐标的连接的情况下切割它？
这是数据：
data <- structure(list(latitud = c(-30.6833000183105, -41.4000015258789,
-43.8189010620117, -34.2731018066406, -47.0666999816895, -40.3166999816895,
-43.4491996765137, -35.7543983459473, -47.1413993835449, -36.6260986328125,
-54.0410995483398, -37.2118988037109, -33.3086013793945, -37.2792015075684,
-35.4524993896484, -36.5856018066406, -18.5832996368408, -18.2325000762939,
-36.4668998718262, -44.75, -44.6591987609863, -44.5936012268066,
-28.4647006988525, -28.6996994018555, -28.5118999481201, -28.6718997955322,
-28.7306003570557, -30.5902996063232, -30.6667003631592, -35.1730995178223,
-48.1591987609863, -48.377498626709, -45.4000015258789, -45.7832984924316,
-29.94580078125, -38.8652992248535, -30.4386005401611, -31.6646995544434,
-51.2000007629395, -51.3328018188477, -51.25, -45.5666999816895,
-45.551700592041, -45.8372001647949, -39.0144004821777, -28.9414005279541,
-28.7502994537354, -38.6081008911133, -34.9844017028809, -32.8403015136719,
-29.9953002929688, -18.3999996185303, -35.9000015258789, -35.6169013977051,
-35.9085998535156, -35.8166999816895, -33.7346992492676, -45.38330078125,
-35.4068984985352, -32.7571983337402, -32.8502998352051, -33.5938987731934,
-36.8386001586914, -33.4961013793945, -20.1119003295898, -27.8043994903564,
-37.7332992553711, -30.9986000061035, -30.8006000518799, -21.9368991851807,
-22.3652992248535, -22.273099899292, -22.0277996063232, -21.9755992889404,
-22.289400100708, -22.2791996002197, -38.4303016662598, -38.6866989135742,
-45.4057998657227, -38.7799987792969, -37.5503005981445, -37.6018981933594,
-37.8997001647949, -38.0368995666504, -37.9897003173828, -37.7047004699707,
-37.7963981628418, -37.7092018127441, -31.5835990905762, -27.3635997772217,
-27.3194007873535, -29.8931007385254, -30.9242000579834, -21.4246997833252,
-36.5703010559082, -38.2008018493652, -38.0661010742188, -38.4333000183105,
-31.7422008514404, -31.6881008148193, -31.8117008209229, -31.7714004516602,
-27.86669921875, -27.5160999298096, -27.9747009277344, -30.7047004699707,
-36.8499984741211, -36.6500015258789, -36.86669921875, -35.3736000061035,
-40.5167007446289, -33.4782981872559, -33.198299407959, -36.0499992370605,
-35.9667015075684, -36.2332992553711, -34.4921989440918, -34.6581001281738,
-32.8166999816895, -47.3499984741211, -47.5, -29.9811000823975,
-32.4413986206055, -22.3922004699707, -22.3430995941162, -21.7124996185303,
-22.4582996368408, -22.4419002532959, -22.4468994140625, -22.5060997009277,
-33.7219009399414, -33.6613998413086, -35.5574989318848), longitud = c(-71.0500030517578,
-73.2166976928711, -72.38330078125, -71.371696472168, -72.8000030517578,
-72.9666976928711, -72.1074981689453, -71.0864028930664, -72.7257995605469,
-72.4891967773438, -68.7975006103516, -72.3242034912109, -70.3572006225586,
-71.9847030639648, -71.7332992553711, -71.5255966186523, -69.0466995239258,
-69.331901550293, -72.6911010742188, -72.7166976928711, -71.8082962036133,
-71.5477981567383, -71.1782989501953, -70.5500030517578, -71.0064010620117,
-70.6464004516602, -70.5066986083984, -71.1714019775391, -71.5333023071289,
-71.0911026000977, -73.0888977050781, -72.9589004516602, -72.5999984741211,
-72.61669921875, -70.5327987670898, -71.7335968017578, -71.002197265625,
-71.2546997070312, -72.9332962036133, -73.1091995239258, -72.5167007446289,
-72.0832977294922, -72.0680999755859, -71.7769012451172, -73.0828018188477,
-70.2481002807617, -70.4828033447266, -72.8478012084961, -72.0100021362305,
-71.0255966186523, -70.5867004394531, -70.3000030517578, -71.5167007446289,
-71.7677993774414, -71.2981033325195, -71.8332977294922, -70.3007965087891,
-72.4666976928711, -72.2082977294922, -70.736701965332, -70.5093994140625,
-70.3792037963867, -73.061897277832, -70.8167037963867, -68.8407974243164,
-70.1268997192383, -72.61669921875, -71.0899963378906, -70.9697036743164,
-68.5330963134766, -68.6418991088867, -68.1438980102539, -68.6207962036133,
-68.6074981689453, -68.3447036743164, -68.2427978515625, -72.0105972290039,
-72.502799987793, -72.6231002807617, -72.9468994140625, -72.5903015136719,
-72.2782974243164, -71.6239013671875, -71.4781036376953, -71.5199966430664,
-71.7683029174805, -71.6988983154297, -71.823600769043, -71.4606018066406,
-70.3392028808594, -70.8380966186523, -71.2514038085938, -70.7731018066406,
-70.053596496582, -71.5547027587891, -71.2988967895508, -71.3497009277344,
-71.2332992553711, -71.1492004394531, -71.2658004760742, -70.9302978515625,
-71.0639038085938, -70.0667037963867, -70.2647018432617, -69.997802734375,
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-72.0832977294922, -72.0167007446289, -72, -71.3731002807617,
-71.3019027709961, -71, -72.8499984741211, -72.9749984741211,
-70.8981018066406, -71.3139038085938, -69.5299987792969, -69.5650024414062,
-69.5167007446289, -68.7363967895508, -68.8886032104492, -68.8775024414062,
-68.988899230957, -71.5550003051758, -71.3371963500977, -71.7067031860352
)), row.names = c(1L, 136L, 262L, 395L, 507L, 605L, 701L, 789L,
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1355030L, 1368899L, 1381979L, 1393175L), class = "data.frame")
以下代码使用简单要素 (sf) 库显示覆盖有提供的数据点的智利地图。边界框在参数中设置为 st_crop 并且可以根据需要进行调整而不会扭曲地图。代码使用 Admin 0 - Countries 形状文件，该文件位于 public 域，可以免费使用。
library(sf)
library(ggplot2)
library(dplyr);
library(magrittr);
# download world shapefile from
# https://www.naturalearthdata.com/downloads/
# 50m-cultural-vectors/50m-admin-0-countries-2/
# and extract zip file
world <- st_read(
# change below line to path of extracted shape file
'c:/path/to/ne_50m_admin_0_countries.shp'
);
world %<>% mutate(active = NAME_EN == 'Chile'); # used to highlight Chile
# convert the dataframe to a sf geometry object
dsf <- data %>%
rowwise %>%
mutate(geometry = list(st_point(c(longitud, latitud)))) %>%
st_as_sf(crs=st_crs(world));
# plot the map
world %>% st_crop(xmin=-90, xmax=-30, ymin=-60, ymax=-10) %>%
ggplot() +
geom_sf(aes(fill=active), show.legend=F) + # world map with Chile highlighted
geom_sf(data=dsf, color='#000000') + # point overlay
scale_fill_manual(values=c('#aaaa66', '#ffffcc')) + # country colors
scale_x_continuous(expand=c(0,0)) +
scale_y_continuous(expand=c(0,0)) +
theme_void() + # remove axis labels and gridlines
theme(panel.background=element_rect(fill='lightblue'))
输出如下所示。请注意，地图不会扭曲裁剪的区域。
补充说明
sf 包提供对简单特征 (sf) 几何的支持。简单要素提供了处理多边形和点等几何体的工具。有一个作弊 sheet here 提供了很好的概述。
绘制底图
从 3.0 版开始，ggplot2 提供了对可视化简单要素几何图形的原生支持。这允许我们写：
world <- st_read(
# change below line to path of extracted shape file
'c:/path/to/ne_50m_admin_0_countries.shp'
);
ggplot(world) + geom_sf()
简单的要素对象通常存储在包含描述几何的列的数据框中。这使我们能够像这样显示智利地图：
ggplot(world %>% filter(NAME_EN == 'Chile')) + geom_sf()
或突出显示智利的地图：
# create new geometry of world map
# cropped to (10°S, 60°S) and (90°W, 30°W)
chileregion <- world %>% st_crop(
xmin=-90,
xmax=-30,
ymin=-60,
ymax=-10)
# show region with Chile highlighted
ggplot(chileregion %>%
mutate(is.chile = factor(NAME_EN == 'Chile'))) +
geom_sf(aes(fill=is.chile), show.legend = F) +
scale_fill_manual(values=c('gray', 'red'))
绘制点
我们得到了一个包含两列的数据框，纬度和经度。
要转换为简单特征，我们首先使用 st_point 创建一个具有给定坐标值的新点：
dsf <- data %>% #begin with data
rowwise %>% # dplyr::rowwise applies mutation to each row individually
# create a geometry column that provides the point as a geometry
mutate(geometry = list(st_point(c(longitud, latitud))))
此时，dsf只是一个带有几何列的数据框；它还不是一个简单的特征对象。我们可以使用函数 st_as_sf 从数据框中创建一个 sf 对象。为此，我们还需要提供坐标参考系统 (CRS) 以允许 ggplot 将提供的坐标投影到地图渲染上。这里我们可以提供ESPG 4326作为CRS，直接将x和y坐标映射到lat/long:
# call st_as_sf to convert data frame to a simple geometry object.
dsf <- st_as_sf(crs=4326);
由于 dsf 现在是一个简单的几何图形，您可以这样绘制：
> ggplot(dsf) + geom_sf()
（请注意，您也可以简单地用 geom_point(data=data, aes(x=longitud, y=latitud)) 覆盖底图上的点，而无需先转换为 sf 对象。这将在这里起作用，因为底图的 CRS 也是 ESPG 4326，它将 x 和 y 分别直接映射到经度和纬度。但是，使用 geom_point 在对几何应用坐标变换时的一般情况下将不起作用。）
重叠
现在两个点都定义为几何图形，您可以简单地叠加：
ggplot() +
geom_sf(data=chileregion) +
geom_sf(data=dsf)
原始答案中的最终情节添加了一些额外的视觉美感（例如，蓝色背景）以生成最终地图输出。
这可能会有所帮助，您可以自己尝试一下：
world_map <- map_data("world")
Wmap <- data %>%
rename(x =longitud , y = latitud) %>%
ggplot() +
geom_polygon(aes(x = long, y = lat, group = group), data = world_map, fill = "grey21", color = "grey21") +
geom_point(aes(x = x, y = y, color = 'red')) +
scale_color_identity() +
coord_fixed() +
xlab("") +
ylab("")
Wmap
Chile_map <- map_data("world", region="Chile")
Cmap <- data %>%
rename(x =longitud , y = latitud) %>%
ggplot() +
geom_polygon(aes(x = long, y = lat, group = group), data = Chile_map, fill = "grey21", color = "grey21") +
geom_point(aes(x = x, y = y, color = 'red')) +
scale_color_identity() +
coord_fixed() +
xlab("") +
ylab("")
Cmap
dev.new()
windows.options(width=10, height=6)
vp_inset <- grid::viewport(width = 0.55, height = 0.45, x = -0.1, y = 0.60, just = c("left", "top"))
print(Wmap)
print(Cmap, vp = vp_inset)
注意： 群体审美决定了哪些案例连接在一起形成多边形。
我已经经历了很多问题和文档，并且由于您需要付费才能使用 ggmaps()（因为 google 云服务）我开始寻找替代方案。我找到了 maps()，我正在尝试调整
data %>%
rename(x = longitud, y = latitud) %>%
ggplot() +
geom_polygon(aes(x = long, y = lat), data = map_data("world")) +
geom_point(aes(x = x, y = y))
但是，我遇到了一些问题：
- 如果你绘制上面的代码，你会得到正确的绘图点（智利），但是世界地图打印错误（见上图）。
- 我不需要灰色地图或彩色地图。我只需要用一种正常的格式绘制国家智利（例如，google 地图卫星）。坐标是 lakes/mountains 的流，我想看看是否可以按某些视觉扇区对它们进行聚类。
- 我只需要一张智利的地图，但由于我没有找到，所以我正在使用这张世界地图。有没有办法在不丢失与地图坐标的连接的情况下切割它？
这是数据：
data <- structure(list(latitud = c(-30.6833000183105, -41.4000015258789,
-43.8189010620117, -34.2731018066406, -47.0666999816895, -40.3166999816895,
-43.4491996765137, -35.7543983459473, -47.1413993835449, -36.6260986328125,
-54.0410995483398, -37.2118988037109, -33.3086013793945, -37.2792015075684,
-35.4524993896484, -36.5856018066406, -18.5832996368408, -18.2325000762939,
-36.4668998718262, -44.75, -44.6591987609863, -44.5936012268066,
-28.4647006988525, -28.6996994018555, -28.5118999481201, -28.6718997955322,
-28.7306003570557, -30.5902996063232, -30.6667003631592, -35.1730995178223,
-48.1591987609863, -48.377498626709, -45.4000015258789, -45.7832984924316,
-29.94580078125, -38.8652992248535, -30.4386005401611, -31.6646995544434,
-51.2000007629395, -51.3328018188477, -51.25, -45.5666999816895,
-45.551700592041, -45.8372001647949, -39.0144004821777, -28.9414005279541,
-28.7502994537354, -38.6081008911133, -34.9844017028809, -32.8403015136719,
-29.9953002929688, -18.3999996185303, -35.9000015258789, -35.6169013977051,
-35.9085998535156, -35.8166999816895, -33.7346992492676, -45.38330078125,
-35.4068984985352, -32.7571983337402, -32.8502998352051, -33.5938987731934,
-36.8386001586914, -33.4961013793945, -20.1119003295898, -27.8043994903564,
-37.7332992553711, -30.9986000061035, -30.8006000518799, -21.9368991851807,
-22.3652992248535, -22.273099899292, -22.0277996063232, -21.9755992889404,
-22.289400100708, -22.2791996002197, -38.4303016662598, -38.6866989135742,
-45.4057998657227, -38.7799987792969, -37.5503005981445, -37.6018981933594,
-37.8997001647949, -38.0368995666504, -37.9897003173828, -37.7047004699707,
-37.7963981628418, -37.7092018127441, -31.5835990905762, -27.3635997772217,
-27.3194007873535, -29.8931007385254, -30.9242000579834, -21.4246997833252,
-36.5703010559082, -38.2008018493652, -38.0661010742188, -38.4333000183105,
-31.7422008514404, -31.6881008148193, -31.8117008209229, -31.7714004516602,
-27.86669921875, -27.5160999298096, -27.9747009277344, -30.7047004699707,
-36.8499984741211, -36.6500015258789, -36.86669921875, -35.3736000061035,
-40.5167007446289, -33.4782981872559, -33.198299407959, -36.0499992370605,
-35.9667015075684, -36.2332992553711, -34.4921989440918, -34.6581001281738,
-32.8166999816895, -47.3499984741211, -47.5, -29.9811000823975,
-32.4413986206055, -22.3922004699707, -22.3430995941162, -21.7124996185303,
-22.4582996368408, -22.4419002532959, -22.4468994140625, -22.5060997009277,
-33.7219009399414, -33.6613998413086, -35.5574989318848), longitud = c(-71.0500030517578,
-73.2166976928711, -72.38330078125, -71.371696472168, -72.8000030517578,
-72.9666976928711, -72.1074981689453, -71.0864028930664, -72.7257995605469,
-72.4891967773438, -68.7975006103516, -72.3242034912109, -70.3572006225586,
-71.9847030639648, -71.7332992553711, -71.5255966186523, -69.0466995239258,
-69.331901550293, -72.6911010742188, -72.7166976928711, -71.8082962036133,
-71.5477981567383, -71.1782989501953, -70.5500030517578, -71.0064010620117,
-70.6464004516602, -70.5066986083984, -71.1714019775391, -71.5333023071289,
-71.0911026000977, -73.0888977050781, -72.9589004516602, -72.5999984741211,
-72.61669921875, -70.5327987670898, -71.7335968017578, -71.002197265625,
-71.2546997070312, -72.9332962036133, -73.1091995239258, -72.5167007446289,
-72.0832977294922, -72.0680999755859, -71.7769012451172, -73.0828018188477,
-70.2481002807617, -70.4828033447266, -72.8478012084961, -72.0100021362305,
-71.0255966186523, -70.5867004394531, -70.3000030517578, -71.5167007446289,
-71.7677993774414, -71.2981033325195, -71.8332977294922, -70.3007965087891,
-72.4666976928711, -72.2082977294922, -70.736701965332, -70.5093994140625,
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-70.1268997192383, -72.61669921875, -71.0899963378906, -70.9697036743164,
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以下代码使用简单要素 (sf) 库显示覆盖有提供的数据点的智利地图。边界框在参数中设置为 st_crop 并且可以根据需要进行调整而不会扭曲地图。代码使用 Admin 0 - Countries 形状文件，该文件位于 public 域，可以免费使用。
library(sf)
library(ggplot2)
library(dplyr);
library(magrittr);
# download world shapefile from
# https://www.naturalearthdata.com/downloads/
# 50m-cultural-vectors/50m-admin-0-countries-2/
# and extract zip file
world <- st_read(
# change below line to path of extracted shape file
'c:/path/to/ne_50m_admin_0_countries.shp'
);
world %<>% mutate(active = NAME_EN == 'Chile'); # used to highlight Chile
# convert the dataframe to a sf geometry object
dsf <- data %>%
rowwise %>%
mutate(geometry = list(st_point(c(longitud, latitud)))) %>%
st_as_sf(crs=st_crs(world));
# plot the map
world %>% st_crop(xmin=-90, xmax=-30, ymin=-60, ymax=-10) %>%
ggplot() +
geom_sf(aes(fill=active), show.legend=F) + # world map with Chile highlighted
geom_sf(data=dsf, color='#000000') + # point overlay
scale_fill_manual(values=c('#aaaa66', '#ffffcc')) + # country colors
scale_x_continuous(expand=c(0,0)) +
scale_y_continuous(expand=c(0,0)) +
theme_void() + # remove axis labels and gridlines
theme(panel.background=element_rect(fill='lightblue'))
输出如下所示。请注意，地图不会扭曲裁剪的区域。
补充说明
sf 包提供对简单特征 (sf) 几何的支持。简单要素提供了处理多边形和点等几何体的工具。有一个作弊 sheet here 提供了很好的概述。
绘制底图
从 3.0 版开始，ggplot2 提供了对可视化简单要素几何图形的原生支持。这允许我们写：
world <- st_read(
# change below line to path of extracted shape file
'c:/path/to/ne_50m_admin_0_countries.shp'
);
ggplot(world) + geom_sf()
简单的要素对象通常存储在包含描述几何的列的数据框中。这使我们能够像这样显示智利地图：
ggplot(world %>% filter(NAME_EN == 'Chile')) + geom_sf()
或突出显示智利的地图：
# create new geometry of world map
# cropped to (10°S, 60°S) and (90°W, 30°W)
chileregion <- world %>% st_crop(
xmin=-90,
xmax=-30,
ymin=-60,
ymax=-10)
# show region with Chile highlighted
ggplot(chileregion %>%
mutate(is.chile = factor(NAME_EN == 'Chile'))) +
geom_sf(aes(fill=is.chile), show.legend = F) +
scale_fill_manual(values=c('gray', 'red'))
绘制点
我们得到了一个包含两列的数据框，纬度和经度。
要转换为简单特征，我们首先使用 st_point 创建一个具有给定坐标值的新点：
dsf <- data %>% #begin with data
rowwise %>% # dplyr::rowwise applies mutation to each row individually
# create a geometry column that provides the point as a geometry
mutate(geometry = list(st_point(c(longitud, latitud))))
此时，dsf只是一个带有几何列的数据框；它还不是一个简单的特征对象。我们可以使用函数 st_as_sf 从数据框中创建一个 sf 对象。为此，我们还需要提供坐标参考系统 (CRS) 以允许 ggplot 将提供的坐标投影到地图渲染上。这里我们可以提供ESPG 4326作为CRS，直接将x和y坐标映射到lat/long:
# call st_as_sf to convert data frame to a simple geometry object.
dsf <- st_as_sf(crs=4326);
由于 dsf 现在是一个简单的几何图形，您可以这样绘制：
> ggplot(dsf) + geom_sf()
（请注意，您也可以简单地用 geom_point(data=data, aes(x=longitud, y=latitud)) 覆盖底图上的点，而无需先转换为 sf 对象。这将在这里起作用，因为底图的 CRS 也是 ESPG 4326，它将 x 和 y 分别直接映射到经度和纬度。但是，使用 geom_point 在对几何应用坐标变换时的一般情况下将不起作用。）
重叠
现在两个点都定义为几何图形，您可以简单地叠加：
ggplot() +
geom_sf(data=chileregion) +
geom_sf(data=dsf)
原始答案中的最终情节添加了一些额外的视觉美感（例如，蓝色背景）以生成最终地图输出。
这可能会有所帮助，您可以自己尝试一下：
world_map <- map_data("world")
Wmap <- data %>%
rename(x =longitud , y = latitud) %>%
ggplot() +
geom_polygon(aes(x = long, y = lat, group = group), data = world_map, fill = "grey21", color = "grey21") +
geom_point(aes(x = x, y = y, color = 'red')) +
scale_color_identity() +
coord_fixed() +
xlab("") +
ylab("")
Wmap
Chile_map <- map_data("world", region="Chile")
Cmap <- data %>%
rename(x =longitud , y = latitud) %>%
ggplot() +
geom_polygon(aes(x = long, y = lat, group = group), data = Chile_map, fill = "grey21", color = "grey21") +
geom_point(aes(x = x, y = y, color = 'red')) +
scale_color_identity() +
coord_fixed() +
xlab("") +
ylab("")
Cmap
dev.new()
windows.options(width=10, height=6)
vp_inset <- grid::viewport(width = 0.55, height = 0.45, x = -0.1, y = 0.60, just = c("left", "top"))
print(Wmap)
print(Cmap, vp = vp_inset)
注意： 群体审美决定了哪些案例连接在一起形成多边形。