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  "metadata_created": "2021-01-19T20:54:07.907432",
            
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  "metadata_modified": "2022-02-22T13:22:35.785783",
            
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  "name": "teneo-soil-moisture-temperature-humidity-sensors",
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  "name": "teneo-soil-moisture-temperature-humidity-sensors",
            
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  "notes": "## Introduction\r\n\r\nWithin the frame of the SCOREwater 
46
  "notes": "## Introduction\r\n\r\nWithin the frame of the SCOREwater 
            
47
project, the City of Amersfoort commissioned 
47
project, the City of Amersfoort commissioned 
            
48
](https://hoefakker.com/boomspecialisten/smart-city-bodemvochtsensor/) 
48
](https://hoefakker.com/boomspecialisten/smart-city-bodemvochtsensor/) 
            
49
to install Teneo soil moisture and climate monitor sensors at several 
49
to install Teneo soil moisture and climate monitor sensors at several 
            
50
locations in the Schothorst neighbourhood and the Central Railway 
50
locations in the Schothorst neighbourhood and the Central Railway 
            
51
area. The sensors measure soil moisture, temperature and humidity. 
51
area. The sensors measure soil moisture, temperature and humidity. 
            
52
Schothorst and the Central Railway area differ in groundwater levels. 
52
Schothorst and the Central Railway area differ in groundwater levels. 
            
53
In Schothorst the groundwater levels are higher (average height: 0.7 
53
In Schothorst the groundwater levels are higher (average height: 0.7 
            
54
meter to 1.0 meter below ground level) than in the Central Railway 
54
meter to 1.0 meter below ground level) than in the Central Railway 
            
55
area (average height: lower than 1.6 meter below ground level). The 
55
area (average height: lower than 1.6 meter below ground level). The 
            
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lowest soil moisture sensors are placed on 1.2 meter below ground 
56
lowest soil moisture sensors are placed on 1.2 meter below ground 
            
57
level. As a result, in the Schothorst area the sensors are located 
57
level. As a result, in the Schothorst area the sensors are located 
            
58
close to or in the groundwater during winter. In the Central Railway 
58
close to or in the groundwater during winter. In the Central Railway 
            
59
area they are located far above the groundwater level. This makes both 
59
area they are located far above the groundwater level. This makes both 
            
60
areas interesting to include. What all soil moisture sensors have in 
60
areas interesting to include. What all soil moisture sensors have in 
            
61
common is that they are all located nearby trees and in public spaces. 
61
common is that they are all located nearby trees and in public spaces. 
            
62
Locations differ in terms of: being in the sun or in the shade, being 
62
Locations differ in terms of: being in the sun or in the shade, being 
            
63
in a green setting (unpaved, such as parks) or being in a paved 
63
in a green setting (unpaved, such as parks) or being in a paved 
            
64
setting, and being near surface water or not. Because of the 
64
setting, and being near surface water or not. Because of the 
            
65
differences between the locations the sensors have been installed in, 
65
differences between the locations the sensors have been installed in, 
            
66
data from the sensors can be used to investigate questions such 
66
data from the sensors can be used to investigate questions such 
            
67
as:\r\n\r\n* What is the influence of the type of surface on soil 
67
as:\r\n\r\n* What is the influence of the type of surface on soil 
            
68
moisture levels?\r\n* Does the nearby presence of surface water affect 
68
moisture levels?\r\n* Does the nearby presence of surface water affect 
            
69
soil moisture?\r\n* What is the influence of heat on soil 
69
soil moisture?\r\n* What is the influence of heat on soil 
            
70
moisture?\r\n* What is the relation between groundwater levels 
70
moisture?\r\n* What is the relation between groundwater levels 
            
71
fluctuance and soil moisture?\r\n* Are adjustments on in public spaces 
71
fluctuance and soil moisture?\r\n* Are adjustments on in public spaces 
            
72
(on street level) helpful to improve the soil situation for a more 
72
(on street level) helpful to improve the soil situation for a more 
            
73
climate adaptive city?\r\n\r\n## Contents of the data\r\n\r\nData are 
73
climate adaptive city?\r\n\r\n## Contents of the data\r\n\r\nData are 
            
74
being harmonized using FIWARE [Smart Data 
74
being harmonized using FIWARE [Smart Data 
            
75
Models](https://www.fiware.org/smart-data-models/). Data regarding 
75
Models](https://www.fiware.org/smart-data-models/). Data regarding 
            
76
soil moisture can be modelled using the GreenSpaceRecord model. The 
76
soil moisture can be modelled using the GreenSpaceRecord model. The 
            
77
data in this dataset provide the following elements from this data 
77
data in this dataset provide the following elements from this data 
            
78
model:\r\n\r\n* id - identifier of the sensors\r\n* recordingTimetamp 
78
model:\r\n\r\n* id - identifier of the sensors\r\n* recordingTimetamp 
            
79
- timestamp of the measurement\r\n* location - GPS location of the 
79
- timestamp of the measurement\r\n* location - GPS location of the 
            
80
sensor, GeoJSON with WGS84/EPSG:4326 coordinate\r\n* soilMoistureVwc - 
80
sensor, GeoJSON with WGS84/EPSG:4326 coordinate\r\n* soilMoistureVwc - 
            
81
percentage Volumetric Water Content of soil\r\n\r\nMeteorological data 
81
percentage Volumetric Water Content of soil\r\n\r\nMeteorological data 
            
82
can be modelled using the WeatherObserved model. The data in this 
82
can be modelled using the WeatherObserved model. The data in this 
            
83
dataset provide the following elements from this data model: \r\n\r\n* 
83
dataset provide the following elements from this data model: \r\n\r\n* 
            
84
id - identifier of the sensors\r\n* recordingTimetamp - timestamp of 
84
id - identifier of the sensors\r\n* recordingTimetamp - timestamp of 
            
85
the measurement\r\n* location - GPS location of the sensor, GeoJSON 
85
the measurement\r\n* location - GPS location of the sensor, GeoJSON 
            
86
with WGS84/EPSG:4326 coordinate\r\n* temperature - temperature in 
86
with WGS84/EPSG:4326 coordinate\r\n* temperature - temperature in 
            
87
degrees Celsius\r\n* relativeHumidity - percentage relative 
87
degrees Celsius\r\n* relativeHumidity - percentage relative 
            
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humidity\r\n\r\n## Access the data\r\n\r\nData are available using 
88
humidity\r\n\r\n## Access the data\r\n\r\nData are available using 
            
89
different API's:\r\n\r\n* The Orion ContextBroker allows you to access 
89
different API's:\r\n\r\n* The Orion ContextBroker allows you to access 
            
90
the [current status of 
90
the [current status of 
            
91
/gravitee-scorewater-gateway.dataplatform.nl/teneo/orion/v2/entities). 
91
/gravitee-scorewater-gateway.dataplatform.nl/teneo/orion/v2/entities). 
            
92
Use the information provided by the Orion ContextBroker to compile 
92
Use the information provided by the Orion ContextBroker to compile 
            
93
requests for the Short Term History API, the ContextBroker provides 
93
requests for the Short Term History API, the ContextBroker provides 
            
94
information on which entities are present and what attributes those 
94
information on which entities are present and what attributes those 
            
95
entities support. \r\n* The Short Term History API allows you to 
95
entities support. \r\n* The Short Term History API allows you to 
            
96
download historical data for the different sensors in both raw and 
96
download historical data for the different sensors in both raw and 
            
97
aggregated form in either JSON or CSV format:\r\n    * 
97
aggregated form in either JSON or CSV format:\r\n    * 
            
98
soilMoistureVwc\r\n        * JSON, 
98
soilMoistureVwc\r\n        * JSON, 
            
99
2/entities/206/attrs/soilMoistureVwc?type=GreenSpaceRecord&lastN=100), 
99
2/entities/206/attrs/soilMoistureVwc?type=GreenSpaceRecord&lastN=100), 
            
100
MoistureVwc?type=GreenSpaceRecord&aggrMethod=min&aggrPeriod=month)\r\n        
100
MoistureVwc?type=GreenSpaceRecord&aggrMethod=min&aggrPeriod=month)\r\n        
            
101
* CSW, 
101
* CSW, 
            
102
6/attrs/soilMoistureVwc?type=GreenSpaceRecord&lastN=100&fileType=csv), 
102
6/attrs/soilMoistureVwc?type=GreenSpaceRecord&lastN=100&fileType=csv), 
            
103
ype=GreenSpaceRecord&aggrMethod=min&aggrPeriod=month&fileType=csv)\r\n    
103
ype=GreenSpaceRecord&aggrMethod=min&aggrPeriod=month&fileType=csv)\r\n    
            
104
* temperature\r\n        * JSON, 
104
* temperature\r\n        * JSON, 
            
105
STH/v2/entities/240/attrs/temperature?type=WeatherObserved&lastN=100), 
105
STH/v2/entities/240/attrs/temperature?type=WeatherObserved&lastN=100), 
            
106
rs/temperature?type=WeatherObserved&aggrMethod=min&aggrPeriod=day)\r\n        
106
rs/temperature?type=WeatherObserved&aggrMethod=min&aggrPeriod=day)\r\n        
            
107
* CSW, 
107
* CSW, 
            
108
es/240/attrs/temperature?type=WeatherObserved&lastN=100&fileType=csv), 
108
es/240/attrs/temperature?type=WeatherObserved&lastN=100&fileType=csv), 
            
109
e?type=WeatherObserved&aggrMethod=min&aggrPeriod=day&fileType=csv)\r\n    
109
e?type=WeatherObserved&aggrMethod=min&aggrPeriod=day&fileType=csv)\r\n    
            
110
* relativeHumidity\r\n        * JSON, 
110
* relativeHumidity\r\n        * JSON, 
            
111
2/entities/240/attrs/relativeHumidity?type=WeatherObserved&lastN=100), 
111
2/entities/240/attrs/relativeHumidity?type=WeatherObserved&lastN=100), 
            
112
lativeHumidity?type=WeatherObserved&aggrMethod=min&aggrPeriod=day)\r\n        
112
lativeHumidity?type=WeatherObserved&aggrMethod=min&aggrPeriod=day)\r\n        
            
113
* CSW, 
113
* CSW, 
            
114
0/attrs/relativeHumidity?type=WeatherObserved&lastN=100&fileType=csv), 
114
0/attrs/relativeHumidity?type=WeatherObserved&lastN=100&fileType=csv), 
            
115
?type=WeatherObserved&aggrMethod=min&aggrPeriod=day&fileType=csv)\r\n* 
115
?type=WeatherObserved&aggrMethod=min&aggrPeriod=day&fileType=csv)\r\n* 
            
116
The OGC web services allows you to [render 
116
The OGC web services allows you to [render 
            
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vice=WMS&srs=EPSG%3A4326&format=image%2Fpng&request=GetMap&height=384) 
117
vice=WMS&srs=EPSG%3A4326&format=image%2Fpng&request=GetMap&height=384) 
            
118
of the sensors and to download historical data in different formats 
118
of the sensors and to download historical data in different formats 
            
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such as 
119
such as 
            
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taplatform_nl%3Ackan_current_weather_observed_hegcudye&version=2.0.0), 
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taplatform_nl%3Ackan_current_weather_observed_hegcudye&version=2.0.0), 
            
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ataplatform_nl%3Ackan_current_weather_observed_hegcudye&version=2.0.0) 
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ataplatform_nl%3Ackan_current_weather_observed_hegcudye&version=2.0.0) 
            
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and shape file. ",
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taplatform_nl%3Ackan_current_weather_observed_hegcudye&version=2.0.0",
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taplatform_nl%3Ackan_current_weather_observed_hegcudye&version=2.0.0",
            
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t
t
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    {
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    {
            
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}