如何使用 coord_map 获取 ggplot 以使用 ESPG 投影 ID？
How do I get ggplot with coord_map to use an ESPG projection id?
我正在绘制几个图层，一个是多边形图层，它在lat/lon中。另一个是 sf 对象。如果我将我的 sf 对象放入 WGS84 (ESPG 4326)，那么多边形和 sf 对象会很好地叠加在一起。然而，我在阿拉斯加工作，所以 WGS84 确实扭曲了事情。
我的 sf 对象最初是在阿拉斯加阿尔伯斯投影中 (espg:2964)。我希望将多边形对象投影到该坐标系中。我认为你应该使用 coord_map() 来处理它，但我不确定如何让 coord_map 进行阿拉斯加阿尔伯斯投影，因为 coord_map() 似乎没有espg 代码或 proj4 字符串。
在此先感谢您的帮助。
此代码有效，但将两者都放入 wgs84：
results.transform = results %>% st_transform(4326)
ggplot(ak, aes(long, lat, group=group))+
geom_polygon(fill="grey", color="black")+
geom_sf(data=results.transform, aes(color=doy),inherit.aes = FALSE, size=2)
此代码不会引发错误，但多边形和 sf 图层不会相互叠加：
#results is the original sf object in espg 2964
ggplot(ak, aes(long, lat, group=group))+
geom_polygon(fill="grey", color="black")+
coord_map("albers", lat0 =50, lat1=55)+
geom_sf(data=results, aes(color=doy),inherit.aes = FALSE, size=2)
输入样本（使用 dput）：
结果：
results =structure(list(id = c("1", "2", "3"), doy = c(152, 158, 142),
doy_meanthresh = c(156, 160, 140), threshold = c(0.173556868958583,
0.109912373062543, 0.074946580423674), smooth.series = list(
c(0.356716711457841, 0.370050893258325, 0.383236999766461,
0.396376974233949, 0.40957275991249, 0.422784291482468,
0.435895856103075, 0.448895925744217, 0.461772972375802,
0.474515467967738, 0.48722268616777, 0.499933470515835,
0.512545647820125, 0.524957044888832, 0.537065488530148,
0.549189274496968, 0.561532939869938, 0.573823673448877,
0.5857886640336, 0.597155100423927, 0.608751798005646,
0.621116663488914, 0.633540522660091, 0.645314201305544,
0.655728525211634, 0.665571086939856, 0.675708836320647,
0.685551635043781, 0.694509344799033, 0.701991827276177,
0.70938842013153, 0.717660871422796, 0.725577658441836,
0.731907258480512, 0.735418148830686, 0.737609381488737,
0.740068708326791, 0.741697656450321, 0.741397752964802,
0.738070524975708, 0.730787113459408, 0.720275348839784,
0.707921792393576, 0.695113005397529, 0.683235549128384,
0.66854065601544, 0.648565682783239, 0.626626377151392,
0.606038486839507, 0.590117759567193, 0.575248354822936,
0.557183338977548, 0.538291820074129, 0.520942906155777,
0.507505705265592, 0.497170423227522, 0.487542218972326,
0.478612630203321, 0.470373194623822, 0.462815449937146,
0.458831683827816, 0.459466542404155, 0.461940101005184,
0.463472434969922, 0.461283619637389, 0.458826926942516,
0.459760482491641, 0.461611642130895, 0.461907761706409,
0.458176197064313, 0.45041527548862, 0.440794234319326,
0.430096794486539, 0.419106676920368, 0.408607602550923,
0.396242242656226, 0.380503346606902, 0.363449752471964,
0.347140298320423, 0.333633822221291, 0.321253095838767,
0.307606088569194, 0.293679435079791, 0.28045977003778,
0.268933728110384, 0.258699817638372, 0.248739536036072,
0.239114001581039, 0.22988433255083, 0.221111647222998,
0.213576575535607, 0.207511807976447, 0.202156553647666,
0.196750021651411, 0.19053142108983, 0.183900129705502,
0.177683584689661, 0.17176308431744, 0.166019926863971,
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0.695420287796062, 0.673237132540861, 0.653273968452586,
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0.566211150306591, 0.561187101242345, 0.557303219009872,
0.555232501533965, 0.555534753213423, 0.557674343776691,
0.561115642952215, 0.565323020468442, 0.573372729704498,
0.586895414376992, 0.603187029720595, 0.619543530969977,
0.63326087335981, 0.649100787927623, 0.670935206211495,
0.694725384196925, 0.716432577869408, 0.732018043214443,
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0.787858534012854, 0.795658319927888, 0.799986340749408,
0.803308852568436, 0.805054155877942, 0.804650551170897,
0.801526338940272, 0.794278541385548, 0.783000246619136,
0.769363854003397, 0.755041762900692, 0.741706372673384,
0.725475019829043, 0.703589930868272, 0.679410840142977,
0.656297482005064, 0.637609590806439, 0.619522671663228,
0.59768917697572, 0.574684262022063, 0.553083082080407,
0.535460792428901, 0.520724989583801, 0.506208924554847,
0.492126234360422, 0.478690556018906, 0.466115526548682,
0.456163205377972, 0.449307080301381, 0.443827930886861,
0.438006536702364, 0.430123677315843, 0.422161025148951,
0.416341337462143, 0.411307021081574, 0.405700482833399,
0.398164129543771, 0.388509330252805, 0.377833000710694,
0.366705867808713, 0.355698658438137, 0.34538209949024,
0.334476225402477, 0.322019919293152, 0.309062181074817,
0.296652010660021, 0.285838407961315, 0.276447235011443,
0.267512949813937, 0.258897446237528, 0.250462618150946,
0.242070359422922, 0.234129641095434, 0.226902750204945,
0.220031554611916, 0.21315792217681, 0.205923720760086,
0.19852372751621, 0.191343478746417, 0.184310981031329,
0.177354240951568, 0.170401265087756, 0.163192040497278,
0.155702671847874, 0.148215342135701, 0.141012234356916,
0.134375531507676, 0.127758694427545, 0.120727232121655,
0.113731399834516, 0.107221452810637, 0.101647646294526,
0.0965005694542742, 0.091209569652388, 0.0861330394250022,
0.0816293713082512, 0.0780569578382695, 0.075371315752509,
0.0732346851768886, 0.0715655437302434, 0.0702823690314086,
0.0693036386992192, 0.0691863250953481, 0.0701883842483067,
0.0717797692771877, 0.073430433301084, 0.0746103294390886,
0.0761784204310707, 0.0788956524181342, 0.0820849536212236,
0.0850692522612836, 0.0871714765592586, 0.0890972731947091,
0.0916871981841642, 0.094466543754022, 0.0969606021306803,
0.0986946655405372, 0.0998521594454551, 0.100914181761071,
0.101852533394445, 0.102639015252636, 0.103245428242704,
0.103462264899288, 0.103250578499722, 0.102838011065113,
0.102452204616565, 0.102320801175184, 0.102287042959656,
0.102088178523127, 0.101792859388387, 0.10146973707823,
0.101187463115447, 0.100889974984667, 0.100495657145597,
0.100034831583652, 0.0995378202842451, 0.0990349452327908,
0.0985243275768939, 0.097982837008049, 0.0974089183275044,
0.0968010163365085, 0.0961575758363094, 0.0954770416281557,
0.0947578585132956, 0.0939984712929773, 0.0931973247684494
), c(0.754994105046569, 0.759262980856892, 0.763248462599852,
0.767062652758686, 0.77081765381663, 0.774472838830307,
0.777902459086919, 0.781090934415562, 0.784022684645335,
0.786682129605334, 0.789179136777192, 0.791558707699299,
0.793707963285894, 0.795514024451214, 0.796864012109498,
0.798059444416928, 0.799307737538445, 0.800354859401417,
0.800946777933214, 0.800829461061205, 0.800535183022801,
0.800489794522664, 0.800279628189041, 0.799491016650182,
0.797710292534332, 0.793727807721641, 0.787531875152631,
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0.766814565429895, 0.764644322900798, 0.76247504120512,
0.759796356039472, 0.756097903100465, 0.753105409945246,
0.751812834849642, 0.750612159588286, 0.747895365935809,
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0.718600671135361, 0.709396840144846, 0.698532958371117,
0.685958066059214, 0.672217339551, 0.657624725365782,
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0.113524600030087, 0.104251044466771, 0.0957537295245833,
0.0883000338464436, 0.0824702507214148, 0.0782344478172879,
0.0749446653450757, 0.0719529435157916, 0.0686113225404485,
0.0661995394292459, 0.0657367472597934, 0.0661841103442199,
0.0665027929946539, 0.0656539595232242, 0.0644681965998428,
0.0641406846621584, 0.0641794786739045, 0.0640926335988149,
0.0633882044006231, 0.0619833956742033, 0.0602788637336122,
0.058507841121357, 0.0569035603799449, 0.0556992540518834,
0.0546528395507013, 0.0534742168963767, 0.0523245925410911,
0.0513651729370255, 0.0507571645363614, 0.0504376622860656,
0.050241048436331, 0.0501744603941783, 0.0502450355666279,
0.0504599113607003, 0.0510283221178971, 0.052012828131863,
0.0532005557378333, 0.0543786312710432, 0.055334181066728,
0.0564245098836434, 0.057962991953209, 0.0596708578196554,
0.0612693380272137, 0.0624796631201147, 0.0635479377810315,
0.0648035693895804, 0.0660927425354069, 0.0672616418081562,
0.0681564517974736, 0.0687850088878122, 0.0692835297177245,
0.0696907692580061, 0.0700454824794523, 0.0703864243528584,
0.0706277104270338, 0.0707098566767007, 0.0707112187115236,
0.0707101521411668, 0.0707850125752948, 0.0708833573425856,
0.0709155836751044, 0.0709043070375961, 0.0708721428948058,
0.0708417067114787, 0.070795102344694, 0.0707055967085618,
0.0705825498533734, 0.0704353218294197, 0.0702732726869918,
0.0700959115439309, 0.0698961835839182, 0.069673602956005,
0.0694276838092427, 0.0691579402926828, 0.0688638865553766,
0.0685450367463756, 0.0682009050147312, 0.0678310055094947
)), doy.series = list(c(55, 56, 57, 58, 59, 60, 61, 62,
63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77,
78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92,
93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105,
106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117,
118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129,
130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141,
142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153,
154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165,
166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177,
178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189,
190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201,
202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213
), c(55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67,
68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82,
83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97,
98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109,
110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121,
122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133,
134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145,
146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157,
158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169,
170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181,
182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193,
194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205,
206, 207, 208, 209, 210, 211, 212, 213), c(55, 56, 57, 58,
59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73,
74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88,
89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102,
103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114,
115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126,
127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138,
139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150,
151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162,
163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174,
175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186,
187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198,
199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210,
211, 212, 213)), year = c("2000", "2000", "2000"), geometry = structure(list(
structure(c(-1661436.84461341, -1661115.05202279, -1661228.76098043,
-1660425.2592279, -1659056.23818505, -1658307.31829931,
-1656634.51866674, -1656620.45332118, -1656912.32303615,
-1658398.86388024, -1659675.83584702, 4861078.89101535,
4860325.10237897, 4859645.11439113, 4857608.78556975,
4855675.65967803, 4850643.61215932, 4846958.71327386,
4845855.03478051, 4845305.91718129, 4844752.81259044,
4843366.85928571), .Dim = c(11L, 2L), class = c("XY",
"LINESTRING", "sfg")), structure(c(-1658241.19039753,
-1654712.75990038, -1651942.38784669, -1650404.98329246,
-1648988.60261601, -1645978.84503211, -1643222.00421422,
-1639781.08711522, -1638602.99625793, -1637902.54559266,
-1639311.78216295, -1639248.9245045, -1638107.13443693,
-1637058.59090575, 4774391.6371314, 4774653.20892703,
4775738.21754787, 4774227.59717794, 4771389.21271209,
4770934.19458225, 4769568.55276305, 4771094.02869766,
4770996.1462525, 4769827.51755788, 4767060.08312911,
4765949.41565321, 4763854.76024583, 4763305.58844374), .Dim = c(14L,
2L), class = c("XY", "LINESTRING", "sfg")), structure(c(-1637058.59090575,
-1634446.33873168, -1631719.63870714, -1629361.15811325,
-1628116.65633233, -1627013.82581023, -1626189.71570171,
-1625551.50211327, -1624075.99821849, -1622805.13871411,
-1622273.7980277, -1620254.94375451, -1618394.36936387,
-1616289.48293551, -1615299.3539038, -1613130.11112742,
4763305.58844374, 4761938.07374864, 4761581.34917333,
4761984.29842838, 4762878.85905119, 4765596.31389399,
4766660.74696295, 4766903.7237966, 4766207.39483074,
4763687.87083808, 4763298.06222046, 4763460.09645817,
4765651.28116598, 4765148.87541194, 4763932.07676722,
4759749.97915703), .Dim = c(16L, 2L), class = c("XY",
"LINESTRING", "sfg"))), class = c("sfc_LINESTRING", "sfc"
), precision = 0, bbox = structure(c(-1661436.84461341, 4759749.97915703,
-1613130.11112742, 4861078.89101535), .Names = c("xmin",
"ymin", "xmax", "ymax"), class = "bbox"), crs = structure(list(
epsg = 2964L, proj4string = "+proj=aea +lat_1=55 +lat_2=65 +lat_0=50 +lon_0=-154 +x_0=0 +y_0=0 +datum=NAD27 +units=us-ft +no_defs"), .Names = c("epsg",
"proj4string"), class = "crs"), n_empty = 0L)), .Names = c("id",
"doy", "doy_meanthresh", "threshold", "smooth.series", "doy.series",
"year", "geometry"), row.names = c(NA, 3L), class = c("sf", "data.frame"
), sf_column = "geometry", agr = structure(c(NA_integer_, NA_integer_,
NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_
), .Names = c("id", "doy", "doy_meanthresh", "threshold", "smooth.series",
"doy.series", "year"), .Label = c("constant", "aggregate", "identity"
), class = "factor"))
阿克：
ak=structure(list(long = c(-130.013061523438, -130.01530456543,
-130.015808105469, -130.015014648438, -130.015808105469, -130.014724731445,
-130.014434814453, -130.014434814453, -130.01416015625, -130.014724731445,
-130.027786254883, -130.041656494141, -130.053924560547, -130.066925048828,
-130.080841064453, -130.088623046875, -130.117797851562, -130.146667480469,
-130.175262451172, -130.204147338867, -130.229187011719, -130.235260009766,
-130.242767333984, -130.249176025391, -130.25749206543, -130.264984130859,
-130.275527954102, -130.285278320312, -130.296676635742, -130.307220458984,
-130.318328857422, -130.329742431641, -130.341934204102, -130.354141235352,
-130.365249633789, -130.375564575195, -130.387496948242, -130.397811889648,
-130.409713745117, -130.414184570312), lat = c(55.9116859436035,
55.9241752624512, 55.9383277893066, 55.952766418457, 55.9669189453125,
55.9814147949219, 55.9952812194824, 56.0100021362305, 56.0238723754883,
56.0258178710938, 56.0422058105469, 56.05859375, 56.075553894043,
56.0919380187988, 56.1086120605469, 56.1180648803711, 56.1122207641602,
56.1066627502441, 56.1008186340332, 56.0949745178223, 56.090274810791,
56.0925102233887, 56.0961227416992, 56.0994453430176, 56.1021919250488,
56.1058616638184, 56.1083221435547, 56.1111297607422, 56.11279296875,
56.1150283813477, 56.1166915893555, 56.118350982666, 56.1203002929688,
56.1222457885742, 56.123908996582, 56.1252822875977, 56.1263732910156,
56.1278038024902, 56.1288948059082, 56.1288948059082), group = c(1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), order = 1:40,
region = c("USA", "USA", "USA", "USA", "USA", "USA", "USA",
"USA", "USA", "USA", "USA", "USA", "USA", "USA", "USA", "USA",
"USA", "USA", "USA", "USA", "USA", "USA", "USA", "USA", "USA",
"USA", "USA", "USA", "USA", "USA", "USA", "USA", "USA", "USA",
"USA", "USA", "USA", "USA", "USA", "USA"), subregion = c("Alaska",
"Alaska", "Alaska", "Alaska", "Alaska", "Alaska", "Alaska",
"Alaska", "Alaska", "Alaska", "Alaska", "Alaska", "Alaska",
"Alaska", "Alaska", "Alaska", "Alaska", "Alaska", "Alaska",
"Alaska", "Alaska", "Alaska", "Alaska", "Alaska", "Alaska",
"Alaska", "Alaska", "Alaska", "Alaska", "Alaska", "Alaska",
"Alaska", "Alaska", "Alaska", "Alaska", "Alaska", "Alaska",
"Alaska", "Alaska", "Alaska")), .Names = c("long", "lat",
"group", "order", "region", "subregion"), row.names = c(NA, 40L
), class = "data.frame")
将 ak 转换为 EPSG:2964，然后在 ggplot 调用
中使用 coord_sf(datum = st_crs(2964))
library(sp)
library(sf)
library(tidyverse)
# Convert ak to EPSG:2964
ak_sf <- sf::st_as_sf(ak, coords = c("long", "lat"), crs = 4326)
ak_sf_tp <- st_transform(ak_sf, crs = 2964)
str(ak_sf_tp)
# Plot everything under EPSG:2964
ggplot() +
geom_sf(data = ak_sf_tp) +
geom_sf(data = results, aes(color = doy), inherit.aes = FALSE, size = 2) +
coord_sf(datum = st_crs(2964))
编辑：如果我们想将ak绘制为多边形
# Get lat/long from sf object
ak_poly <- as(ak_sf_tp, 'Spatial') %>%
as.data.frame() %>%
rename(long = "coords.x1", lat = "coords.x2")
ggplot(ak_poly, aes(long, lat, group = group)) +
geom_polygon(fill = "grey", color = "black") +
geom_sf(data = results, aes(color = doy), inherit.aes = FALSE, size = 2) +
coord_sf(datum = st_crs(2964))
我正在绘制几个图层，一个是多边形图层，它在lat/lon中。另一个是 sf 对象。如果我将我的 sf 对象放入 WGS84 (ESPG 4326)，那么多边形和 sf 对象会很好地叠加在一起。然而，我在阿拉斯加工作，所以 WGS84 确实扭曲了事情。
我的 sf 对象最初是在阿拉斯加阿尔伯斯投影中 (espg:2964)。我希望将多边形对象投影到该坐标系中。我认为你应该使用 coord_map() 来处理它，但我不确定如何让 coord_map 进行阿拉斯加阿尔伯斯投影，因为 coord_map() 似乎没有espg 代码或 proj4 字符串。
在此先感谢您的帮助。
此代码有效，但将两者都放入 wgs84：
results.transform = results %>% st_transform(4326)
ggplot(ak, aes(long, lat, group=group))+
geom_polygon(fill="grey", color="black")+
geom_sf(data=results.transform, aes(color=doy),inherit.aes = FALSE, size=2)
此代码不会引发错误，但多边形和 sf 图层不会相互叠加：
#results is the original sf object in espg 2964
ggplot(ak, aes(long, lat, group=group))+
geom_polygon(fill="grey", color="black")+
coord_map("albers", lat0 =50, lat1=55)+
geom_sf(data=results, aes(color=doy),inherit.aes = FALSE, size=2)
输入样本（使用 dput）：
结果：
results =structure(list(id = c("1", "2", "3"), doy = c(152, 158, 142),
doy_meanthresh = c(156, 160, 140), threshold = c(0.173556868958583,
0.109912373062543, 0.074946580423674), smooth.series = list(
c(0.356716711457841, 0.370050893258325, 0.383236999766461,
0.396376974233949, 0.40957275991249, 0.422784291482468,
0.435895856103075, 0.448895925744217, 0.461772972375802,
0.474515467967738, 0.48722268616777, 0.499933470515835,
0.512545647820125, 0.524957044888832, 0.537065488530148,
0.549189274496968, 0.561532939869938, 0.573823673448877,
0.5857886640336, 0.597155100423927, 0.608751798005646,
0.621116663488914, 0.633540522660091, 0.645314201305544,
0.655728525211634, 0.665571086939856, 0.675708836320647,
0.685551635043781, 0.694509344799033, 0.701991827276177,
0.70938842013153, 0.717660871422796, 0.725577658441836,
0.731907258480512, 0.735418148830686, 0.737609381488737,
0.740068708326791, 0.741697656450321, 0.741397752964802,
0.738070524975708, 0.730787113459408, 0.720275348839784,
0.707921792393576, 0.695113005397529, 0.683235549128384,
0.66854065601544, 0.648565682783239, 0.626626377151392,
0.606038486839507, 0.590117759567193, 0.575248354822936,
0.557183338977548, 0.538291820074129, 0.520942906155777,
0.507505705265592, 0.497170423227522, 0.487542218972326,
0.478612630203321, 0.470373194623822, 0.462815449937146,
0.458831683827816, 0.459466542404155, 0.461940101005184,
0.463472434969922, 0.461283619637389, 0.458826926942516,
0.459760482491641, 0.461611642130895, 0.461907761706409,
0.458176197064313, 0.45041527548862, 0.440794234319326,
0.430096794486539, 0.419106676920368, 0.408607602550923,
0.396242242656226, 0.380503346606902, 0.363449752471964,
0.347140298320423, 0.333633822221291, 0.321253095838767,
0.307606088569194, 0.293679435079791, 0.28045977003778,
0.268933728110384, 0.258699817638372, 0.248739536036072,
0.239114001581039, 0.22988433255083, 0.221111647222998,
0.213576575535607, 0.207511807976447, 0.202156553647666,
0.196750021651411, 0.19053142108983, 0.183900129705502,
0.177683584689661, 0.17176308431744, 0.166019926863971,
0.160335410604389, 0.153743267353215, 0.146014563103421,
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0.176039161718523, 0.175223509244339, 0.174367860290815
), c(0.774610362619149, 0.746412269781788, 0.719913789191898,
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0.586895414376992, 0.603187029720595, 0.619543530969977,
0.63326087335981, 0.649100787927623, 0.670935206211495,
0.694725384196925, 0.716432577869408, 0.732018043214443,
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0.787858534012854, 0.795658319927888, 0.799986340749408,
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0.801526338940272, 0.794278541385548, 0.783000246619136,
0.769363854003397, 0.755041762900692, 0.741706372673384,
0.725475019829043, 0.703589930868272, 0.679410840142977,
0.656297482005064, 0.637609590806439, 0.619522671663228,
0.59768917697572, 0.574684262022063, 0.553083082080407,
0.535460792428901, 0.520724989583801, 0.506208924554847,
0.492126234360422, 0.478690556018906, 0.466115526548682,
0.456163205377972, 0.449307080301381, 0.443827930886861,
0.438006536702364, 0.430123677315843, 0.422161025148951,
0.416341337462143, 0.411307021081574, 0.405700482833399,
0.398164129543771, 0.388509330252805, 0.377833000710694,
0.366705867808713, 0.355698658438137, 0.34538209949024,
0.334476225402477, 0.322019919293152, 0.309062181074817,
0.296652010660021, 0.285838407961315, 0.276447235011443,
0.267512949813937, 0.258897446237528, 0.250462618150946,
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0.134375531507676, 0.127758694427545, 0.120727232121655,
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0.0968010163365085, 0.0961575758363094, 0.0954770416281557,
0.0947578585132956, 0.0939984712929773, 0.0931973247684494
), c(0.754994105046569, 0.759262980856892, 0.763248462599852,
0.767062652758686, 0.77081765381663, 0.774472838830307,
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)), doy.series = list(c(55, 56, 57, 58, 59, 60, 61, 62,
63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77,
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202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213
), c(55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67,
68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82,
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199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210,
211, 212, 213)), year = c("2000", "2000", "2000"), geometry = structure(list(
structure(c(-1661436.84461341, -1661115.05202279, -1661228.76098043,
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-1654712.75990038, -1651942.38784669, -1650404.98329246,
-1648988.60261601, -1645978.84503211, -1643222.00421422,
-1639781.08711522, -1638602.99625793, -1637902.54559266,
-1639311.78216295, -1639248.9245045, -1638107.13443693,
-1637058.59090575, 4774391.6371314, 4774653.20892703,
4775738.21754787, 4774227.59717794, 4771389.21271209,
4770934.19458225, 4769568.55276305, 4771094.02869766,
4770996.1462525, 4769827.51755788, 4767060.08312911,
4765949.41565321, 4763854.76024583, 4763305.58844374), .Dim = c(14L,
2L), class = c("XY", "LINESTRING", "sfg")), structure(c(-1637058.59090575,
-1634446.33873168, -1631719.63870714, -1629361.15811325,
-1628116.65633233, -1627013.82581023, -1626189.71570171,
-1625551.50211327, -1624075.99821849, -1622805.13871411,
-1622273.7980277, -1620254.94375451, -1618394.36936387,
-1616289.48293551, -1615299.3539038, -1613130.11112742,
4763305.58844374, 4761938.07374864, 4761581.34917333,
4761984.29842838, 4762878.85905119, 4765596.31389399,
4766660.74696295, 4766903.7237966, 4766207.39483074,
4763687.87083808, 4763298.06222046, 4763460.09645817,
4765651.28116598, 4765148.87541194, 4763932.07676722,
4759749.97915703), .Dim = c(16L, 2L), class = c("XY",
"LINESTRING", "sfg"))), class = c("sfc_LINESTRING", "sfc"
), precision = 0, bbox = structure(c(-1661436.84461341, 4759749.97915703,
-1613130.11112742, 4861078.89101535), .Names = c("xmin",
"ymin", "xmax", "ymax"), class = "bbox"), crs = structure(list(
epsg = 2964L, proj4string = "+proj=aea +lat_1=55 +lat_2=65 +lat_0=50 +lon_0=-154 +x_0=0 +y_0=0 +datum=NAD27 +units=us-ft +no_defs"), .Names = c("epsg",
"proj4string"), class = "crs"), n_empty = 0L)), .Names = c("id",
"doy", "doy_meanthresh", "threshold", "smooth.series", "doy.series",
"year", "geometry"), row.names = c(NA, 3L), class = c("sf", "data.frame"
), sf_column = "geometry", agr = structure(c(NA_integer_, NA_integer_,
NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_
), .Names = c("id", "doy", "doy_meanthresh", "threshold", "smooth.series",
"doy.series", "year"), .Label = c("constant", "aggregate", "identity"
), class = "factor"))
阿克：
ak=structure(list(long = c(-130.013061523438, -130.01530456543,
-130.015808105469, -130.015014648438, -130.015808105469, -130.014724731445,
-130.014434814453, -130.014434814453, -130.01416015625, -130.014724731445,
-130.027786254883, -130.041656494141, -130.053924560547, -130.066925048828,
-130.080841064453, -130.088623046875, -130.117797851562, -130.146667480469,
-130.175262451172, -130.204147338867, -130.229187011719, -130.235260009766,
-130.242767333984, -130.249176025391, -130.25749206543, -130.264984130859,
-130.275527954102, -130.285278320312, -130.296676635742, -130.307220458984,
-130.318328857422, -130.329742431641, -130.341934204102, -130.354141235352,
-130.365249633789, -130.375564575195, -130.387496948242, -130.397811889648,
-130.409713745117, -130.414184570312), lat = c(55.9116859436035,
55.9241752624512, 55.9383277893066, 55.952766418457, 55.9669189453125,
55.9814147949219, 55.9952812194824, 56.0100021362305, 56.0238723754883,
56.0258178710938, 56.0422058105469, 56.05859375, 56.075553894043,
56.0919380187988, 56.1086120605469, 56.1180648803711, 56.1122207641602,
56.1066627502441, 56.1008186340332, 56.0949745178223, 56.090274810791,
56.0925102233887, 56.0961227416992, 56.0994453430176, 56.1021919250488,
56.1058616638184, 56.1083221435547, 56.1111297607422, 56.11279296875,
56.1150283813477, 56.1166915893555, 56.118350982666, 56.1203002929688,
56.1222457885742, 56.123908996582, 56.1252822875977, 56.1263732910156,
56.1278038024902, 56.1288948059082, 56.1288948059082), group = c(1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), order = 1:40,
region = c("USA", "USA", "USA", "USA", "USA", "USA", "USA",
"USA", "USA", "USA", "USA", "USA", "USA", "USA", "USA", "USA",
"USA", "USA", "USA", "USA", "USA", "USA", "USA", "USA", "USA",
"USA", "USA", "USA", "USA", "USA", "USA", "USA", "USA", "USA",
"USA", "USA", "USA", "USA", "USA", "USA"), subregion = c("Alaska",
"Alaska", "Alaska", "Alaska", "Alaska", "Alaska", "Alaska",
"Alaska", "Alaska", "Alaska", "Alaska", "Alaska", "Alaska",
"Alaska", "Alaska", "Alaska", "Alaska", "Alaska", "Alaska",
"Alaska", "Alaska", "Alaska", "Alaska", "Alaska", "Alaska",
"Alaska", "Alaska", "Alaska", "Alaska", "Alaska", "Alaska",
"Alaska", "Alaska", "Alaska", "Alaska", "Alaska", "Alaska",
"Alaska", "Alaska", "Alaska")), .Names = c("long", "lat",
"group", "order", "region", "subregion"), row.names = c(NA, 40L
), class = "data.frame")
将 ak 转换为 EPSG:2964，然后在 ggplot 调用
coord_sf(datum = st_crs(2964))
library(sp)
library(sf)
library(tidyverse)
# Convert ak to EPSG:2964
ak_sf <- sf::st_as_sf(ak, coords = c("long", "lat"), crs = 4326)
ak_sf_tp <- st_transform(ak_sf, crs = 2964)
str(ak_sf_tp)
# Plot everything under EPSG:2964
ggplot() +
geom_sf(data = ak_sf_tp) +
geom_sf(data = results, aes(color = doy), inherit.aes = FALSE, size = 2) +
coord_sf(datum = st_crs(2964))
编辑：如果我们想将ak绘制为多边形
# Get lat/long from sf object
ak_poly <- as(ak_sf_tp, 'Spatial') %>%
as.data.frame() %>%
rename(long = "coords.x1", lat = "coords.x2")
ggplot(ak_poly, aes(long, lat, group = group)) +
geom_polygon(fill = "grey", color = "black") +
geom_sf(data = results, aes(color = doy), inherit.aes = FALSE, size = 2) +
coord_sf(datum = st_crs(2964))