Perfil de elevación con etiquetas en waypoints (QGIS, Python)
Aug 30 2020
Me gustaría trazar muchos perfiles de elevación con etiquetas en puntos de referencia específicos (puntos de interés). Al final, debería verse así:
El DEM y los Tracks (gpx y otros formatos) ya están ahí. Ahora quiero crear los perfiles de elevación con nombres usando QGIS y scripts.
Ya verifiqué los complementos de perfil en QGIS, pero ninguno de ellos puede generar los nombres de puntos de referencia específicos.
¿Conoce una solución sencilla para lograrlo?
EDIT1: La pista gpx se ve así. Quiero tener los nombres de las características del WPT (por ejemplo, "valle", "inicio", "pico") escritos en el perfil de elevación
<?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>```
Respuestas
4 christoph Aug 31 2020 at 20:40
Puede combinar QGIS con HTML / Javascript ( Highcharts o cualquier otro marco) para producir atractivos perfiles de elevación. Con la ayuda de algunas funciones de expresión de Python, es posible utilizar la función QGIS Atlas para mostrar múltiples pistas junto con sus puntos de referencia correspondientes. La idea es, crear una capa de waypoints virtuales que se filtrará por el nombre de los tracks:
- Arrastre y suelte su archivo GPX en el lienzo del mapa QGIS, importe y convierta su capa de pista de MultiLinestring a Linestring. Llame a la capa resultante "pista". Luego, importe su capa de waypoint y cámbiele el nombre a "waypoints_orig".
- Agrega un "nombre" de columna a tu capa de "pista" y dales a tus pistas algunos nombres significativos. Luego agregue una columna "track" a su capa "waypoints_orig" y asigne los nombres de track correspondientes a los waypoints. Agregue los "waypoints" de la capa virtual a su proyecto:
vlayer = QgsVectorLayer ("? query = select * from waypoints_orig where track = '' & geometry = geometry", 'waypoints', 'virtual')
QgsProject.instance (). AddMapLayer (vlayer)
- Coloque el siguiente código Python en la sección Macro de su proyecto QGIS y habilite las macros 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
- Genere un Atlas con su capa de "seguimiento" como "Capa de cobertura"
- Agregue un marco HTML a su diseño:
<!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>
- Debido a problemas de tiempo, tenemos que agregar la función de expresión de Python wait1000 () al marco HTML (es decir, usar la anulación definida por datos para "Excluir elemento de las exportaciones")
4 BERA Aug 30 2020 at 16:07
Usando su archivo xml y matplotlib, puede lograr buenos resultados si se esfuerza un poco. Los gráficos de Matplotlib se pueden modificar para que se parezcan mucho a su ejemplo. La parte más complicada fue calcular dónde colocar las etiquetas.
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()
