英文:
R - ggplot mapping data on international country
问题
我尝试在坦桑尼亚的Mwanihana森林中绘制一个缩放视图。
我已经查看了在R中绘制纬度和经度点，但无法使其适用于我的数据集。
数据如下：
date forestsite primaryinterface secondaryinterface<chr> <chr> <chr> <chr>8.27.13 UMNP-HQ ecotourism forest use/PD8.28.13 UMNP-campsite3 ecotourism forest use8.28.13 UMNP-campsite3 ecotourism forest use8.28.13 UMNP-hondohondoa ecotourism forest use/PD8.28.13 UMNP-hondohondob ecotourism forest use/PD/crop-raiding8.29.13 UMNP-njokamoni ecotourism forest use8.29.13 UMNP-mangabey ecotourism forest useanthrochange species geometry<chr> <chr> <S3: sfc_POINT>small trails, snares BWC <S3: sfc_POINT>roads, buildings RC <S3: sfc_POINT>roads, campsite RC <S3: sfc_POINT>roads, campsite BWC <S3: sfc_POINT>none SY <S3: sfc_POINT>clearcut road, houses, crops YB <S3: sfc_POINT>trail to njokamoni RC <S3: sfc_POINT>small trails, habituated troop SM <S3: sfc_POINT>
地图数据和ggplot尝试如下：
library(elevatr)library(rgdal)se.elevations <- get_elev_raster(locations = world, z = 7, clip = "locations")se.elevation.df <- raster::as.data.frame(se.elevations, xy = TRUE) %>%rename(elevation = 3) %>%na.omit() %>%filter(elevation >= 0)xlimit <- c(36.85, 37)ylimit <- c(-7.76, -7.88)ggplot() +geom_tile(data = se.elevation.df, aes(x = x, y = y, fill = elevation)) +scale_fill_gradientn(colours= c("gray", "black")) +geom_sf(data = world, fill = NA) +xlim(xlimit) +ylim(ylimit) +geom_sf(data = data, aes(color = forestsite, shape = primaryinterface), size = 3) +coord_sf(xlim = c(36.85, 37), ylim = c(-7.76, -7.88), expand = FALSE)
我能够得到这张地图：
从以下代码：
ggplot() +geom_sf(data = data, aes(color = species, shape = primaryinterface), size = 3) +coord_sf(xlim = c(36.85, 37), ylim = c(-7.76, -7.88), expand = FALSE) -> ggplottt
但每当我尝试添加我的地图数据以包括坦桑尼亚的纬度和经度时，我会收到各种错误消息。
任何建议都将不胜感激。
Deput
英文:
I am trying to map a zoomed-in view along the Mwanihana forest in Tanzania.
I have looked into Plotting latitude and longitude points in r, but can't get it to work for my dataset.
Data <-
date forestsite primaryinterface secondaryinterface<chr> <chr> <chr> <chr>8.27.13 UMNP-HQ ecotourism forest use/PD8.28.13 UMNP-campsite3 ecotourism forest use8.28.13 UMNP-campsite3 ecotourism forest use8.28.13 UMNP-hondohondoa ecotourism forest use/PD8.28.13 UMNP-hondohondob ecotourism forest use/PD/crop-raiding8.29.13 UMNP-njokamoni ecotourism forest use8.29.13 UMNP-mangabey ecotourism forest useanthrochange species geometry<chr> <chr> <S3: sfc_POINT>small trails, snares BWC <S3: sfc_POINT>roads, buildings RC <S3: sfc_POINT>roads, campsite RC <S3: sfc_POINT>roads, campsite BWC <S3: sfc_POINT>none SY <S3: sfc_POINT>clearcut road, houses, crops YB <S3: sfc_POINT>trail to njokamoni RC <S3: sfc_POINT>small trails, habituated troop SM <S3: sfc_POINT>
Map data and ggplot attempt
library(elevatr)library(rgdal)se.elevations <- get_elev_raster(locations = world, z = 7, clip = "locations")se.elevation.df <- raster::as.data.frame(se.elevations, xy = TRUE) %>%rename(elevation = 3) %>%na.omit() %>%filter(elevation >= 0)xlimit <- c(36.85, 37)ylimit <- c(-7.76, -7.88)ggplot()+geom_tile(data = se.elevation.df, aes(x = x, y = y, fill = elevation))+scale_fill_gradientn(colours= c("gray", "black"))+geom_sf(data = world, fill = NA)+xlim(xlimit)+ylim(ylimit)+geom_sf(data = data, aes(color = forestsite, shape = primaryinterface), size = 3) +coord_sf(xlim = c(36.85, 37), ylim = c(-7.76, -7.88), expand = FALSE)
I am able to get this map -
from this code
ggplot() +geom_sf(data = data, aes(color = species, shape = primaryinterface), size = 3) +coord_sf(xlim = c(36.85, 37), ylim = c(-7.76, -7.88), expand = FALSE) -> ggplottt
but anytime I try to add the mymap data to include the Tanzanian lat, long, I get various error messages.
Any advice is greatly appreciated.
Deput
structure(list(date = c("8.27.13", "8.28.13", "8.28.13", "8.28.13","8.28.13", "8.29.13", "8.29.13"), forestsite = c("UMNP-HQ", "UMNP-campsite3","UMNP-campsite3", "UMNP-hondohondoa", "UMNP-hondohondob", "UMNP-njokamoni","UMNP-mangabey"), primaryinterface = c("ecotourism", "ecotourism","ecotourism", "ecotourism", "ecotourism", "ecotourism", "ecotourism"), secondaryinterface = c("forest use/PD", "forest use", "forest use","forest use/PD", "forest use/PD/crop-raiding", "forest use","forest use"), anthrochange = c("roads, buildings", "roads, campsite","roads, campsite", "none", "clearcut road, houses, crops", "trail to njokamoni","small trails, habituated troop"), species = c("RC", "RC", "BWC","SY", "YB", "RC", "SM"), geometry = structure(list(structure(c(36.883988,-7.844929), class = c("XY", "POINT", "sfg")), structure(c(36.884545,-7.849439), class = c("XY", "POINT", "sfg")), structure(c(36.884545,-7.849439), class = c("XY", "POINT", "sfg")), structure(c(36.887065,-7.833501), class = c("XY", "POINT", "sfg")), structure(c(36.891369,-7.832091), class = c("XY", "POINT", "sfg")), structure(c(36.878388,-7.82738), class = c("XY", "POINT", "sfg")), structure(c(36.87753,-7.8232), class = c("XY", "POINT", "sfg"))), class = c("sfc_POINT","sfc"), precision = 0, bbox = structure(c(xmin = 36.87753, ymin = -7.849439,xmax = 36.891369, ymax = -7.8232), class = "bbox"), crs = structure(list(input = "EPSG:4326", wkt = "GEOGCRS[\"WGS 84\",\n ENSEMBLE[\"World Geodetic System 1984 ensemble\",\n MEMBER[\"World Geodetic System 1984 (Transit)\"],\n MEMBER[\"World Geodetic System 1984 (G730)\"],\n MEMBER[\"World Geodetic System 1984 (G873)\"],\n MEMBER[\"World Geodetic System 1984 (G1150)\"],\n MEMBER[\"World Geodetic System 1984 (G1674)\"],\n MEMBER[\"World Geodetic System 1984 (G1762)\"],\n MEMBER[\"World Geodetic System 1984 (G2139)\"],\n ELLIPSOID[\"WGS 84\",6378137,298.257223563,\n LENGTHUNIT[\"metre\",1]],\n ENSEMBLEACCURACY[2.0]],\n PRIMEM[\"Greenwich\",0,\n ANGLEUNIT[\"degree\",0.0174532925199433]],\n CS[ellipsoidal,2],\n AXIS[\"geodetic latitude (Lat)\",north,\n ORDER[1],\n ANGLEUNIT[\"degree\",0.0174532925199433]],\n AXIS[\"geodetic longitude (Lon)\",east,\n ORDER[2],\n ANGLEUNIT[\"degree\",0.0174532925199433]],\n USAGE[\n SCOPE[\"Horizontal component of 3D system.\"],\n AREA[\"World.\"],\n BBOX[-90,-180,90,180]],\n ID[\"EPSG\",4326]]"), class = "crs"), n_empty = 0L)), row.names = c(NA,-7L), sf_column = "geometry", agr = structure(c(date = NA_integer_,forestsite = NA_integer_, primaryinterface = NA_integer_, secondaryinterface = NA_integer_,anthrochange = NA_integer_, species = NA_integer_), .Label = c("constant","aggregate", "identity"), class = "factor"), class = c("sf","tbl_df", "tbl", "data.frame"))
答案1
得分: 2
我认为最好使用交互地图。数据是df。你需要以良好的格式获取坐标，因为你的对象是sfc_POINT。
我与你一起使用dput()
library(sf)library(leaflet)library(raster)library(sp)# 提取坐标df$latitudes <- st_coordinates(df$geometry)[, 2]df$longitudes <- st_coordinates(df$geometry)[, 1]adm <- getData('GADM', country='TZA', level=1)popup <- paste0("<strong>人口： </strong>",adm$NAME_1)# 坦桑尼亚交互地图TZA_MAP <- leaflet() %>%addTiles() %>%addPolygons(data=adm, weight = 2, col = 'blue', fillColor = "#FEF800", popup=popup,fillOpacity = 0.1) |addCircles(data = df ,lat= df$latitudes , lng= df$longitudes,label = c(df$primaryinterface, df$secondaryinterface), labelOptions =labelOptions(noHide = T, direction = "bottom"),group = c(df$primaryinterface, df$secondaryinterface)) |addLayersControl(overlayGroup= c(df$primaryinterface, df$secondaryinterface),options = layersControlOptions(collapsed=F))TZA_MAP
你可以选择primaryinterface和secondaryinterface来进行筛选，但你可以在函数中更改你想要做的操作。
英文:
I think that is better an interactive map. The data is df. You need get the coordinate in a good format because your object is a sfc_POINT.
I'm work with you dput()
library(sf)library(leaflet)library(raster)library(sp)# Extract coordinatesdf$latitudes <- st_coordinates(df$geometry)[, 2]df$longitudes <- st_coordinates(df$geometry)[, 1]adm <- getData('GADM', country='TZA', level=1)popup <- paste0("<strong>POPULATION: </strong>",adm$NAME_1)# Tanzania interactive mapTZA_MAP <- leaflet() %>%addTiles() %>%addPolygons(data=adm, weight = 2, col = 'blue', fillColor = "#FEF800", popup=popup,fillOpacity = 0.1) |>addCircles(data = df ,lat= df$latitudes , lng= df$longitudes,label = c(df$primaryinterface, df$secondaryinterface), labelOptions =labelOptions(noHide = T, direction = "bottom"),group = c(df$primaryinterface, df$secondaryinterface)) |>addLayersControl(overlayGroup= c(df$primaryinterface, df$secondaryinterface),options = layersControlOptions(collapsed=F))TZA_MAP
You could select for filter primaryinterface and secondaryinterface, but you can change in function what you want to do.
通过集体智慧和协作来改善编程学习和解决问题的方式。致力于成为全球开发者共同参与的知识库，让每个人都能够通过互相帮助和分享经验来进步。
评论