要获取大洲，您可以使用此答案中的worldmap修改coords2country函数的最后一行，以创建一个Coords2continental功能，如下所示。选择您想要的是6大陆模式还是7大陆模式。我将考虑将此代码放入worlddmap。

library(sp)
library(rworldmap)

# The single argument to this function, points, is a data.frame in which:
#   - column 1 contains the longitude in degrees
#   - column 2 contains the latitude in degrees
coords2continent = function(points)
{  
  countriesSP <- getMap(resolution='low')
  #countriesSP <- getMap(resolution='high') #you could use high res map from rworldxtra if you were concerned about detail

  # converting points to a SpatialPoints object
  # setting CRS directly to that from rworldmap
  pointsSP = SpatialPoints(points, proj4string=CRS(proj4string(countriesSP)))  


  # use 'over' to get indices of the Polygons object containing each point 
  indices = over(pointsSP, countriesSP)

  #indices$continent   # returns the continent (6 continent model)
  indices$REGION   # returns the continent (7 continent model)
  #indices$ADMIN  #returns country name
  #indices$ISO3 # returns the ISO3 code 
}

这是一个测试。

points = data.frame(lon=c(0, 90, -45, -100, 130), lat=c(52, 40, -10, 45, -30 ))

coords2continent(points)
#[1] Europe        Asia          South America North America Australia  
coords2country(points)
#[1] United Kingdom  China   Brazil   United States of America  Australia

因此，这是在Google上使用反向地理编码API的替代方法。此代码部分基于此引用。

在 df 上方调用数据帧，

reverseGeoCode <- function(latlng) {
  require("XML")
  require("httr")
  latlng    <- as.numeric(latlng)
  latlngStr <- gsub(' ','%20', paste(round(latlng,2), collapse=","))
  url   <- "http://maps.google.com"
  path  <- "/maps/api/geocode/xml"
  query <- list(sensor="false",latlng=latlngStr)
  response <- GET(url, path=path, query=query)
  if (response$status !=200) {
    print(paste("HTTP Error:",response$status),quote=F)
    return(c(NA,NA))
  }
  xml    <- xmlInternalTreeParse(content(response,type="text"))
  status <- xmlValue(getNodeSet(xml,"//status")[[1]])
  if (status != "OK"){
    print(paste("Query Failed:",status),quote=F)
    return(c(NA,NA))
  }
  xPath   <- '//result[1]/address_component[type="country"]/long_name[1]'
  country <- xmlValue(getNodeSet(xml,xPath)[[1]])
  xPath   <- '//result[1]/address_component[type="administrative_area_level_1"]/long_name[1]'
  state   <- xmlValue(getNodeSet(xml,xPath)[[1]])
  return(c(state=state,country=country))
}
st.cntry <- t(apply(df,1,function(x)reverseGeoCode(x[2:3])))
result   <- cbind(df,st.cntry)
result
#               Point_Name Longitude  Latitude         state       country
# 1 University of Arkansas  36.06783 -94.17365      Arkansas United States
# 2      Lehigh University  40.60146 -75.36006  Pennsylvania United States
# 3     Harvard University  42.37939 -71.11590 Massachusetts United States

在API定义中，“administrative_area_level_1”是国家以下的最高行政区域。在美国，这些是州。在其他国家，定义有所不同（例如，可能是省份）。

顺便说一句，我相当肯定你把纬度和经度弄反了。