Geoscience Reference
In-Depth Information
the random or systematic sampling frames. We begin with the random sampling
frame:
def randomFrame(n_sample, bbox_dict, output_format):
output_ds, layer, layerDefinition =
createVector(output_format)
featureIndex=0
for i in range(0, int(n_sample)):
print i
x_tmp = int(random.randrange(bbox_dict['xmin'],
bbox_dict['xmax'], 1))
y_tmp = int(random.randrange(bbox_dict['ymin'],
bbox_dict['ymax'], 1))
point = ogr.Geometry(ogr.wkbPoint)
point.SetPoint(0, x_tmp, y_tmp)
feature = ogr.Feature(layerDefinition)
feature.SetGeometry(point)
feature.SetFID(featureIndex)
feature.SetField("plot_id", i)
feature.SetField("x",x_tmp)
feature.SetField("y",y_tmp)
layer.CreateFeature(feature)
featureIndex += 1
output_ds.Destroy()
We also include a function to create a systematic sampling frame.
def systematicFrame(output_format):
output_ds, layer, layerDefinition =
createVector(output_format)
featureIndex=0
x=0
y=0
while x < 6:
while y < 6:
print x,y
y+=1
point = ogr.Geometry(ogr.wkbPoint)
point.SetPoint(0, x, y)
feature = ogr.Feature(layerDefinition)
feature.SetGeometry(point)
feature.SetFID(featureIndex)
layer.CreateFeature(feature)
featureIndex+=1
y=0
x+=1
output_ds.Destroy()
 
 
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