SpatialPolygonsDataFrame中每个多边形的边界框R

Question

如何获得polys中每个多边形的bbox？

pp <- cbind(coordinates(polys),as.data.frame(polys)) 

给我只能lonlat，但我想获得lat1lat2和lon1lon2为每个多边形。

polys=new("SpatialPolygonsDataFrame" 
     , data = structure(list(NAMRB_EN = structure(c(6L, 45L, 2L, 41L, 31L, 
    3L, 40L, 14L, 42L, 7L, 26L, 12L, 38L, 25L, 36L, 9L, 39L, 27L, 
    32L, 19L, 43L, 21L, 15L, 22L, 20L, 9L, 17L, 11L, 33L, 44L, 37L, 
    13L, 8L, 5L, 18L, 30L, 16L, 10L, 1L, 29L, 34L, 23L, 24L, 28L, 
    4L, 35L), .Label = c("Albany", "Arctic Ocean Seaboard", "Arnaud", 
    "Atlantic Ocean Seaboard", "Attawapiskat", "Back", "Baleine", 
    "Broadback", "Churchill", "Columbia", "Eastmain", "Feuilles", 
    "Fraser", "George", "Grande Baleine", "Harricanaw", "Hayes", 
    "Hudson Bay Seaboard", "Koksoak", "La Grande", "Little Mecatina", 
    "Mackenzie", "Mississippi", "Moose", "Naskaupi", "Nass", "Natashquan", 
    "Nelson", "Nottaway", "Pacific Ocean Seaboard", "Povungnituk", 
    "Romaine", "Rupert", "Saint John", "Saint Lawrence", "Seal", 
    "Severn", "Skeena", "St.-Augustin", "Stikine", "Taku", "Thelon", 
    "Wannock", "Winisk", "Yukon"), class = "factor"), NAODA_EN = structure(c(1L, 
    5L, 1L, 5L, 4L, 4L, 5L, 4L, 4L, 4L, 5L, 4L, 5L, 2L, 4L, 2L, 2L, 
    2L, 2L, 4L, 5L, 2L, 4L, 1L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 4L, 
    4L, 4L, 5L, 4L, 5L, 4L, 4L, 2L, 3L, 4L, 4L, 2L, 2L), .Label = c("Arctic Ocean", 
    "Atlantic Ocean", "Gulf of Mexico", "Hudson Bay", "Pacific Ocean" 
    ), class = "factor"), NAMRB_FR = structure(c(4L, 45L, 19L, 41L, 
    31L, 2L, 40L, 12L, 42L, 5L, 27L, 10L, 38L, 26L, 36L, 7L, 39L, 
    28L, 32L, 16L, 43L, 18L, 13L, 23L, 17L, 7L, 15L, 9L, 33L, 44L, 
    37L, 11L, 6L, 3L, 22L, 21L, 14L, 8L, 1L, 30L, 34L, 24L, 25L, 
    29L, 20L, 35L), .Label = c("Albany", "Arnaud", "Attawapiskat", 
    "Back", "Baleine", "Broadback", "Churchill", "Columbia", "Eastmain", 
    "Feuilles", "Fraser", "George", "Grande Baleine", "Harricanaw", 
    "Hayes", "Koksoak", "La Grande", "Little Mecatina", "Littoral de l'océan Arctique", 
    "Littoral de l'océan Atlantique", "Littoral de l'océan Pacifique", 
    "Littoral de la Baie d'Hudson", "Mackenzie", "Mississippi", "Moose", 
    "Naskaupi", "Nass", "Natashquan", "Nelson", "Nottaway", "Povungnituk", 
    "Romaine", "Rupert", "Saint-Jean", "Saint-Laurent", "Seal", "Severn", 
    "Skeena", "St.-Augustin", "Stikine", "Taku", "Thelon", "Wannock", 
    "Winisk", "Yukon"), class = "factor"), NAODA_FR = structure(c(3L, 
    5L, 3L, 5L, 1L, 1L, 5L, 1L, 1L, 1L, 5L, 1L, 5L, 4L, 1L, 4L, 4L, 
    4L, 4L, 1L, 5L, 4L, 1L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 5L, 1L, 
    1L, 1L, 5L, 1L, 5L, 1L, 1L, 4L, 2L, 1L, 1L, 4L, 4L), .Label = c("Baie d'Hudson", 
    "Golfe de Mexique", "Océan Arctique", "Océan Atlantique", "Océan Pacifique" 
    ), class = "factor")), .Names = c("NAMRB_EN", "NAODA_EN", "NAMRB_FR", 
    "NAODA_FR"), row.names = 0:45, class = "data.frame") 
     , polygons = list(<S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>, 
     <S4 object of class structure("Polygons", package = "sp")>) 
     , plotOrder = c(3L, 24L, 35L, 46L, 44L, 2L, 42L, 38L, 45L, 36L, 26L, 9L, 32L, 
    1L, 20L, 39L, 27L, 31L, 43L, 25L, 16L, 7L, 30L, 40L, 6L, 15L, 
    34L, 13L, 12L, 41L, 28L, 8L, 23L, 29L, 5L, 10L, 37L, 11L, 14L, 
    33L, 4L, 22L, 18L, 19L, 17L, 21L) 
     , bbox = structure(c(-152.812332679775, 40.3769750107632, -52.6362915039062, 
    83.1106262207029), .Dim = c(2L, 2L), .Dimnames = list(c("x", 
    "y"), c("min", "max"))) 
     , proj4string = new("CRS" 
     , projargs = "+proj=longlat +datum=NAD83 +no_defs +ellps=GRS80 +towgs84=0,0,0" 
    ) 
    ) 

Answer 1

空间多边形数据帧有几个插槽。 @data是数据帧，@polygons是多边形。你可以先尝试str(polys@polygons)看看你得到了什么。如果是多边形的列表，然后lapply它sp::bbox功能

require(sp) 
lapply(polys@polygons, bbox) 

Answer 2

以前的答案是好的，可惜是多少，我对大数据集（百万多边形）太慢。

使用RCPP可以加快步伐了很多（> 20倍），以下功能从spatDataManagement包提取出来，你可以把它放在一个CPP文件，并在其上运行sourceCpp获得功能也可以安装spatDataManagement并直接使用该功能。此外，它很好地把一切都在一个data.frame有足够的列名：

> head(GetBBoxes(phillyCensusTracts)) 
     minX  minY  maxX  maxY 
1 -74.97678 40.07721 -74.95576 40.09781 
2 -75.00539 40.09937 -74.96408 40.12390 
3 -75.14641 39.92889 -75.13040 39.96294 
4 -75.00942 40.05475 -74.99043 40.06916 
5 -75.03647 40.05078 -75.02171 40.06731 
6 -74.98463 40.07198 -74.97151 40.09381 

代码：

#include <Rcpp.h> 
#include <string> 

using namespace Rcpp; 

//' Get bounding box for each polygon/polyline 
//' @description Gets the bounding box (range of x and y) for each item of a SpatialLines/Polygons (DataFrame or not) object. 
//' It is equivalent to applying the \code{sp::bbox} function to all polygons with lapply but it is 
//' simpler to use and much faster (even on a toy example of a few hundred polygons but designed for datasets with millions, then easily gets > 20x faster). 
//' It is an important function to speed up other more complex comparisons between sp objects such as over(). 
//' @param x A SpatialPolygons[DataFrame] or SpatialLines[DataFrame] 
//' @return A matrix of same number of columns than x and 4 columns : xmin, ymin, xmax, ymax 
//' @export 
//' @examples 
//' data(phillyCensusTract) 
//' ## simple use 
//' system.time(bboxes <- GetBBoxes(phillyCensusTracts)) 
//' #=> 0.002 seconds 
//' ## same using bbox 
//' system.time(bboxesRef <- matrix(unlist(lapply(phillyCensusTracts@polygons,bbox)),ncol=4,byrow=TRUE)) 
//' #=> 0.021 seconds 
// [[Rcpp::export]] 
SEXP GetBBoxes(SEXP x){ 
    // determines object type and adapts the search of coordinates 
    S4 obj(x) ; 
    std::string nameList; 
    std::string nameSubList; 
    if(Rf_inherits(x, "SpatialLines") || Rf_inherits(x, "SpatialLinesDataFrame")){ 
     nameList = "lines"; 
     nameSubList = "Lines"; 
    }else if(Rf_inherits(x, "SpatialPolygons") || Rf_inherits(x, "SpatialPolygonsDataFrame")){ 
     nameList = "polygons"; 
     nameSubList = "Polygons"; 
    }else{ 
     ::Rf_error("In GetBBoxes, class must be Spatial[Polygons|Lines][DataFrame]"); 
    } 
    List a = obj.slot(nameList); 

    // count items 
    int nPol = a.length(); 
    NumericMatrix bboxes(nPol,4); 

    // get the range 
    for(int iPol = 0;iPol < nPol;iPol++){ 
     S4 pol = a(iPol); 
     List b = pol.slot(nameSubList); 

     double minX = std::numeric_limits<double>::infinity(); 
     double maxX = -std::numeric_limits<double>::infinity(); 
     double minY = std::numeric_limits<double>::infinity(); 
     double maxY = -std::numeric_limits<double>::infinity(); 

     for(int iSP = 0; iSP < b.length(); iSP++){ 
      S4 subPol = b(iSP); 
      NumericMatrix coords = subPol.slot("coords"); 
      // X 
      NumericVector rangeX = range(coords(_,0)); 
      if(rangeX(0)<minX) minX = rangeX(0); 
      if(rangeX(1)>maxX) maxX = rangeX(1); 
      // Y 
      NumericVector rangeY = range(coords(_,1)); 
      if(rangeY(0)<minY) minY = rangeY(0); 
      if(rangeY(1)>maxY) maxY = rangeY(1); 
     } 

     bboxes(iPol,0) = minX; 
     bboxes(iPol,1) = minY; 
     bboxes(iPol,2) = maxX; 
     bboxes(iPol,3) = maxY; 
    } 
    Rcpp::DataFrame BBoxes = Rcpp::DataFrame::create(Rcpp::Named("minX")=bboxes(_,0), 
      Rcpp::Named("minY")=bboxes(_,1), 
      Rcpp::Named("maxX")=bboxes(_,2), 
      Rcpp::Named("maxY")=bboxes(_,3)); 

    return BBoxes; 
} 

Answer 3

要返回plottable边框（在SpatialPolygonsDataFrame的形式），而不是名单这lapply(polys@polygons, bbox)收益矩阵：

spatial_bboxes <- function(polygons) { 
    individual_bb <- function(polygon, projection) { 
    polygon <- sp::SpatialPolygons(list(polygon), proj4string = projection) 
    spatial_bbox <- as(raster::extent(polygon), "SpatialPolygons") 
    spatial_bbox <- spatial_bbox@polygons[[1]] 
    spatial_bbox@ID <- polygon@polygons[[1]]@ID 
    return(spatial_bbox) 
    } 
    polys <- lapply(polygons@polygons, individual_bb, polygons@proj4string) 
    spatial_polys <- sp::SpatialPolygons(polys, proj4string = polygons@proj4string) 
    spatial_polys_df <- sp::SpatialPolygonsDataFrame(spatial_polys, polygons@data) 
    return(spatial_polys_df) 
}