Profilo di elevazione con etichette sui waypoint (QGIS, Python)
Aug 30 2020
Vorrei tracciare molti profili altimetrici con etichette su waypoint specifici (punti di interesse). Alla fine dovrebbe assomigliare a questo:
Il DEM e le tracce (gpx e altri formati) sono già presenti. Ora voglio creare i profili di elevazione con nomi usando QGIS e script.
Ho già controllato i plugin del profilo in QGIS ma nessuno di loro è in grado di visualizzare i nomi di waypoint specifici.
Conosci una soluzione semplice per ottenere questo risultato?
EDIT1: la traccia gpx ha questo aspetto. Voglio che i nomi delle caratteristiche del WPT (es. "Valle", "inizio", "picco") siano scritti sul profilo altimetrico
<?xml version="1.0" encoding="UTF-8"?>
<!-- track-length = 4644 filtered ascend = 159 plain-ascend = -764 cost=12636 energy=.0kwh time=2h 9m 17s -->
<gpx
xmlns="http://www.topografix.com/GPX/1/1"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://www.topografix.com/GPX/1/1 http://www.topografix.com/GPX/1/1/gpx.xsd"
creator="BRouter-1.6.1" version="1.1">
<wpt lon="6.005273" lat="44.910205">
<name>start</name>
</wpt>
<wpt lon="6.000938" lat="44.907256">
<name>valley</name>
</wpt>
<wpt lon="6.000209" lat="44.904671">
<name>peak1</name>
</wpt>
<wpt lon="5.984759" lat="44.905219">
<name>peak2</name>
</wpt>
<wpt lon="5.988064" lat="44.915039">
<name>end</name>
</wpt>
<trk>
<name>hike</name>
<trkseg>
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</trkseg>
</trk>
</gpx>```
Risposte
4 christoph Aug 31 2020 at 20:40
Puoi combinare QGIS con HTML / Javascript ( Highcharts o qualsiasi altro framework) per produrre attraenti profili di elevazione. Con l'aiuto di alcune funzioni di espressione Python, è possibile utilizzare la funzione QGIS Atlas per mostrare più tracce insieme ai loro waypoint corrispondenti. L'idea è creare un layer di waypoint virtuali che verrà filtrato in base al nome delle tracce:
- Trascina e rilascia il tuo file GPX nella mappa di QGIS, importa e converti il tuo tracciato da MultiLinestring a Linestring. Chiama il livello risultante "traccia". Quindi importa il tuo layer waypoint e rinominalo in "waypoints_orig".
- Aggiungi una colonna "nome" al tuo livello "traccia" e assegna alle tue tracce nomi significativi. Quindi aggiungi una colonna "track" al tuo layer "waypoints_orig" e assegna i nomi delle tracce corrispondenti ai waypoint. Aggiungi il livello virtuale "waypoint" al tuo progetto:
vlayer = QgsVectorLayer ("? query = select * from waypoints_orig where track = '' & geometry = geometry", 'waypoints', 'virtual')
QgsProject.instance (). AddMapLayer (vlayer)
- Metti il seguente codice Python nella sezione Macro del tuo progetto QGIS e abilita le macro Python:
from qgis.core import qgsfunction,QgsCoordinateTransform,QgsProject
from qgis.PyQt.QtCore import QTimer,QEventLoop
from itertools import accumulate
@qgsfunction(args=0, group='Custom', usesgeometry=True)
def GetProfileData(values, feature, parent):
vertices = list(feature.geometry().vertices())
dList,zList = zip(*[[vertices[i-1].distance(vertex),vertex.z()] for i,vertex in enumerate(vertices) if i > 0])
dList = tuple(accumulate(dList))
data = [list(elem) for elem in list(zip(dList,zList))]
data.insert(0,[0,vertices[0].z()])
return str(data)
@qgsfunction(args=0, group='Custom')
def wait1000(values, feature, parent):
loop = QEventLoop()
QTimer.singleShot(1000,loop.quit)
loop.exec_()
return 0
@qgsfunction(args=3, group='Custom', usesgeometry=True)
def GetWaypoints(values, feature, parent):
waypointLayer = values[0]
trackLayer = values[1]
nameFilter = values[2]
wplayer = QgsProject.instance().mapLayersByName(waypointLayer)[0]
wplayer.setDataSource("?query=select * from waypoints_orig where track='%s'&geometry=geometry" % nameFilter,waypointLayer,'virtual')
loop = QEventLoop()
QTimer.singleShot(1000,loop.quit)
loop.exec_()
trlayer = QgsProject.instance().mapLayersByName(trackLayer)[0]
geom = feature.geometry()
crsSrc = wplayer.crs()
crsDest = trlayer.crs()
xform = QgsCoordinateTransform(crsSrc, crsDest,QgsProject.instance())
ret = ''
for wpf in wplayer.getFeatures():
wpgeom = wpf.geometry()
wpgeom.transform(xform)
vtx = geom.closestVertex(wpgeom.asPoint())[1]
elev = geom.vertexAt(vtx).z()
d = geom.distanceToVertex(vtx)
print(d)
ret += "{point: { xAxis: 0, yAxis: 0, x: %s, y: %s}, text: '%s'}," % (d,elev, wpf["name"])
ret = ret[0:-1]
return ret
- Genera un atlante con il tuo livello "traccia" come "livello di copertura"
- Aggiungi una cornice HTML al tuo layout:
<!DOCTYPE html>
<html>
<head>
<style type="text/css">
#container {
max-width: 850px;
height: 350px;
margin: 1em auto;
}
</style>
<title>Highcharts Demo</title>
</head>
<body>
<script src="http://code.highcharts.com/highcharts.js"></script>
<script src="http://code.highcharts.com/modules/annotations.js"></script>
<div id="container" style="height: 400px; min-width: 380px;"></div>
<script type="text/javascript">//<![CDATA[
var elevationData = [%GetProfileData()%];
Highcharts.chart('container', {
chart: {
type: 'area'
},
title: {
style: { color: "#2b435d" },
text: "Mountain Trail"
},
subtitle: {
style: { color: "#2b435d" },
text: 'Total Length: [%round($length)%]m'
},
xAxis: {
labels: {
style: { color: "#2b435d" },
format: '{value}'
},
minTickInterval: 250,
title: {
text: 'Distance [m]'
}
},
yAxis: {
startOnTick: true,
endOnTick: false,
maxPadding: 0.35,
title: {
text: 'Elevation [m]'
},
labels: {
style: { color: "#2b435d" },
format: '{value}'
}
},
legend: {
enabled: false
},
annotations: [{
labelOptions: {
backgroundColor: 'rgba(255,255,255,0.5)'
},
labels: [[% GetWaypoints('waypoints','track',"name") %]]}
],
plotOptions: {
area: {
fillColor: {
linearGradient: {
x1: 0,
y1: 0,
x2: 0,
y2: 1
},
stops: [
[0,'#8B4513'],
[1, Highcharts.Color(Highcharts.getOptions().colors[2]).setOpacity(0.3).get('rgba')]
]
},
marker: {
radius: 2
},
lineWidth: 1,
states: {
hover: {
lineWidth: 1
}
},
threshold: null
}
},
series: [{
data: elevationData,
lineColor: Highcharts.getOptions().colors[1],
color: Highcharts.getOptions().colors[2],
fillOpacity: 0.5,
name: 'Elevation',
marker: {
enabled: false
},
threshold: null
}]
});
//]]>
</script>
</body>
</html>
- A causa di problemi di temporizzazione dobbiamo aggiungere la funzione di espressione Python wait1000 () al frame HTML (cioè usa l'override definito dai dati per "Escludi elemento dalle esportazioni")
4 BERA Aug 30 2020 at 16:07
Usando il tuo file xml e matplotlib puoi ottenere buoni risultati se ci metti un po 'di impegno. I grafici di Matplotlib possono essere modificati per assomigliare molto al tuo esempio. La parte più difficile è stata calcolare dove posizionare le etichette.
import matplotlib.pyplot as plt
import numpy as np
#Function to project geometries to get distances in meters instead of degrees
#From: https://gis.stackexchange.com/questions/163645/transforming-single-qgsgeometry-object-from-one-crs-to-another-using-pyqgis
def pr(ingeom):
sourceCrs = QgsCoordinateReferenceSystem(4326)
destCrs = QgsCoordinateReferenceSystem(32632)
tr = QgsCoordinateTransform(sourceCrs, destCrs, QgsProject.instance())
ingeom.transform(tr)
return ingeom
tp = QgsProject.instance().mapLayersByName('track_points')[0]
zfield = 'ele'
orderfield = 'track_seg_point_id'
tpfeats = [f for f in tp.getFeatures()] #List all trackpoints
tpfeats.sort(key=lambda x: x[orderfield]) #Sort by orderfield (maybe they already are(?), doesnt matter)
#List all horizontal distances, the plot x values
hdist = [pr(p1.geometry()).distance(pr(p2.geometry())) for p1,p2 in zip(tpfeats, tpfeats[1:])]
hdist.insert(0,0) #First point
hdist = np.cumsum(hdist)
#List heights
zs = [f[zfield] for f in tpfeats] #The plot y values
#Which track point is closest to each waypoint?
#To know where to place each label in horizontal and height directions
wp = QgsProject.instance().mapLayersByName('waypoints')[0]
placenamefield = 'name'
wpfeats = [f for f in wp.getFeatures()]
labels = [] #Each waypoints name attribute and the index of the closest trackpoint
for wpf in wpfeats:
closest_trackpoint = min(tpfeats, key=lambda x: pr(x.geometry()).distance(pr(wpf.geometry())))
ix = [tpf.id() for tpf in tpfeats].index(closest_trackpoint.id())
labels.append([wpf[placenamefield], ix])
labels = [[l[0], hdist[l[1]]-100, zs[l[1]]+25] for l in labels] #List of lists like this: [['somelabeltext',horizontal distance, height], ['somelabeltext2',...
#Plot
plt.plot(hdist, zs, 'g')
plt.xlabel("Distance")
plt.ylabel("Elevation")
plt.title("Forgiving terrain 50k")
plt.hlines(range(1600,2700,100), xmin=0, xmax=4500, colors='silver', linestyles='solid')
x1,x2,y1,y2 = plt.axis()
plt.axis((x1,x2,1600,2600))
plt.fill_between(hdist, zs, color='#c1daba')
for labeltext, x, y, in labels:
plt.annotate(labeltext, (x, y), color='g')
plt.show()
