Wolfram Data Repository

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Sample Data: Meuse River

Source Notebook

Annotated locations of soil samples along the Dutch bank of the Meuse River north of Maastricht

Details

Locations of soil samples collected in a flood plain of the river Meuse, near the village of Stein (NL) in the observation region which is the convex hull of the sample locations, annotated with marks including elevation (in meters), distance to river (in meters), flooding frequency, cadmium (in ppm), copper (in ppm), lead (in ppm), zinc (in ppm), percent of organic matter, presence of lime, and soil type (Rd10A - Calcareous weakly-developed meadow soils, light sandy clay; Rd90C/VII - Non-calcareous weakly-developed meadow soils, heavy sandy clay to light clay; Bkd26/VII - Red Brick soil, fine-sandy, silty light clay).

Examples

Basic Examples (2) 

In[1]:=
ResourceData[\!\(\* TagBox["\"\<Sample Data: Meuse River\>\"", #& , BoxID -> "ResourceTag-Sample Data: Meuse River-Input", AutoDelete->True]\), "Data"]
Out[1]=

Summary of the spatial point data:

In[2]:=
ResourceData[\!\(\* TagBox["\"\<Sample Data: Meuse River\>\"", #& , BoxID -> "ResourceTag-Sample Data: Meuse River-Input", AutoDelete->True]\), "Data"]["Summary"]
Out[2]=

List annotations keys:

In[3]:=
ResourceData[\!\(\* TagBox["\"\<Sample Data: Meuse River\>\"", #& , BoxID -> "ResourceTag-Sample Data: Meuse River-Input", AutoDelete->True]\), "AnnotationsKeys"]
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Visualizations (5) 

Plot the locations:

In[4]:=
ListPlot[ResourceData[\!\(\* TagBox["\"\<Sample Data: Meuse River\>\"", #& , BoxID -> "ResourceTag-Sample Data: Meuse River-Input", AutoDelete->True]\), "Data"]]
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Visualize the smooth point density:

In[5]:=
density = SmoothPointDensity[ResourceData[\!\(\* TagBox["\"\<Sample Data: Meuse River\>\"", #& , BoxID -> "ResourceTag-Sample Data: Meuse River-Input", AutoDelete->True]\), "Data"]]
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In[6]:=
Show[ContourPlot[density[{x, y}], {x, y} \[Element] ResourceData[\!\(\* TagBox["\"\<Sample Data: Meuse River\>\"", #& , BoxID -> "ResourceTag-Sample Data: Meuse River-Input", AutoDelete->True]\), "ObservationRegion"], ColorFunction -> "Rainbow"], ListPlot[ResourceData[\!\(\* TagBox["\"\<Sample Data: Meuse River\>\"", #& , BoxID -> "ResourceTag-Sample Data: Meuse River-Input", AutoDelete->True]\), "Data"], PlotStyle -> Black]]
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Visualize points with some annotations:

In[7]:=
PointValuePlot[ResourceData[\!\(\* TagBox["\"\<Sample Data: Meuse River\>\"", #& , BoxID -> "ResourceTag-Sample Data: Meuse River-Input", AutoDelete->True]\), "Locations"] -> ResourceData[\!\(\* TagBox["\"\<Sample Data: Meuse River\>\"", #& , BoxID -> "ResourceTag-Sample Data: Meuse River-Input", AutoDelete->True]\), "Annotations"]["Cadmium"], ColorFunction -> "Rainbow", PlotLegends -> Automatic, PlotLabel -> "Cadmium in ppm"]
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Compare distributions of the four metals:

In[8]:=
elements = {"Cadmium", "Copper", "Lead", "Zinc"};
In[9]:=
With[{pts = ResourceData[\!\(\* TagBox["\"\<Sample Data: Meuse River\>\"", #& , BoxID -> "ResourceTag-Sample Data: Meuse River-Input", AutoDelete->True]\), "Locations"]}, GraphicsGrid@ Partition[Table[PointValuePlot[pts -> (ResourceData[\!\(\* TagBox["\"\<Sample Data: Meuse River\>\"", #& , BoxID -> "ResourceTag-Sample Data: Meuse River-Input", AutoDelete->True]\), "Annotations"][elements[[k]]]), {1 -> "Size"}, PlotLabel -> elements[[k]]], {k, 1, 4}], 2]]
Out[9]=

Flood frequency at locations:

In[10]:=
PointValuePlot[ResourceData[\!\(\* TagBox["\"\<Sample Data: Meuse River\>\"", #& , BoxID -> "ResourceTag-Sample Data: Meuse River-Input", AutoDelete->True]\), "Locations"] -> ResourceData[\!\(\* TagBox["\"\<Sample Data: Meuse River\>\"", #& , BoxID -> "ResourceTag-Sample Data: Meuse River-Input", AutoDelete->True]\), "Annotations"]["FloodFrequency"], ColorFunction -> "Rainbow", PlotLegends -> Automatic, PlotLabel -> "Flood frequency"]
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Analysis (3) 

Use SpatialEstimate to create a continuous estimate from sparse observation locations:

In[11]:=
est = SpatialEstimate[ResourceData[\!\(\* TagBox["\"\<Sample Data: Meuse River\>\"", #& , BoxID -> "ResourceTag-Sample Data: Meuse River-Input", AutoDelete->True]\), "Data"] -> "Lead"]
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Create a set of random points and compute the estimated values at these locations:
In[12]:=
pts = RandomPoint[ResourceData[\!\(\* TagBox["\"\<Sample Data: Meuse River\>\"", #& , BoxID -> "ResourceTag-Sample Data: Meuse River-Input", AutoDelete->True]\), "ObservationRegion"], 2000]; vals = est[pts];

Visualize the values over the whole region:

In[13]:=
Labeled[GraphicsRow[{PointValuePlot[pts -> vals, ColorFunction -> "Rainbow"], DensityPlot[est[{x, y}], {x, y} \[Element] ResourceData[\!\(\* TagBox["\"\<Sample Data: Meuse River\>\"", #& , BoxID -> "ResourceTag-Sample Data: Meuse River-Input", AutoDelete->True]\), "ObservationRegion"], ColorFunction -> "Rainbow"]}], "Lead level in ppm", Top]
Out[13]=

Gosia Konwerska, "Sample Data: Meuse River" from the Wolfram Data Repository (2022)  

Data Resource History

  • Date Created:

Source Metadata

  • Citation:
    • M G J Rikken and R P G Van Rijn, 1993. Soil pollution with heavy metals - an inquiry into spatial variation, cost of mapping and the risk evaluation of copper, cadmium, lead and zinc in the floodplains of the Meuse west of Stein, the Netherlands. Doctoraalveldwerkverslag, Dept. of Physical Geography, Utrecht University

Publisher Information

  • Prepared for the Wolfram Data Repository By: Gosia Konwerska
    (Wolfram Research, Inc.)
  • Publisher of Record: Gosia Konwerska