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      "title": "Natuur en milieu"
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      "title": "Natuur en milieu"
            
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  "metadata_created": "2021-01-19T20:54:07.907432",
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  "metadata_created": "2021-01-19T20:54:07.907432",
            
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  "metadata_modified": "2022-02-17T09:03:29.845775",
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  "metadata_modified": "2022-02-17T09:03:29.845775",
            
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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 Flexyz to install Teneo 
47
project, the City of Amersfoort commissioned Flexyz to install Teneo 
            
48
soil moisture and climate monitor sensors at several locations in the 
48
soil moisture and climate monitor sensors at several locations in the 
            
49
Schothorst neighbourhood and the Central Railway area. The sensors 
49
Schothorst neighbourhood and the Central Railway area. The sensors 
            
50
measure soil moisture, temperature and humidity. Schothorst and the 
50
measure soil moisture, temperature and humidity. Schothorst and the 
            
51
Central Railway area differ in groundwater levels. In Schothorst the 
51
Central Railway area differ in groundwater levels. In Schothorst the 
            
52
groundwater levels are higher (average height: 0.7 meter to 1.0 meter 
52
groundwater levels are higher (average height: 0.7 meter to 1.0 meter 
            
53
below ground level) than in the Central Railway area (average height: 
53
below ground level) than in the Central Railway area (average height: 
            
54
lower than 1.6 meter below ground level). The lowest soil moisture 
54
lower than 1.6 meter below ground level). The lowest soil moisture 
            
55
sensors are placed on 1.2 meter below ground level. As a result, in 
55
sensors are placed on 1.2 meter below ground level. As a result, in 
            
56
the Schothorst area the sensors are located close to or in the 
56
the Schothorst area the sensors are located close to or in the 
            
57
groundwater during winter. In the Central Railway area they are 
57
groundwater during winter. In the Central Railway area they are 
            
58
located far above the groundwater level. This makes both areas 
58
located far above the groundwater level. This makes both areas 
            
59
interesting to include. What all soil moisture sensors have in common 
59
interesting to include. What all soil moisture sensors have in common 
            
60
is that they are all located nearby trees and in public spaces. 
60
is that they are all located nearby trees and in public spaces. 
            
61
Locations differ in terms of: being in the sun or in the shade, being 
61
Locations differ in terms of: being in the sun or in the shade, being 
            
62
in a green setting (unpaved, such as parks) or being in a paved 
62
in a green setting (unpaved, such as parks) or being in a paved 
            
63
setting, and being near surface water or not. Because of the 
63
setting, and being near surface water or not. Because of the 
            
64
differences between the locations the sensors have been installed in, 
64
differences between the locations the sensors have been installed in, 
            
65
data from the sensors can be used to investigate questions such 
65
data from the sensors can be used to investigate questions such 
            
66
as:\r\n\r\n* What is the influence of the type of surface on soil 
66
as:\r\n\r\n* What is the influence of the type of surface on soil 
            
67
moisture levels?\r\n* Does the nearby presence of surface water affect 
67
moisture levels?\r\n* Does the nearby presence of surface water affect 
            
68
soil moisture?\r\n* What is the influence of heat on soil 
68
soil moisture?\r\n* What is the influence of heat on soil 
            
69
moisture?\r\n* What is the relation between groundwater levels 
69
moisture?\r\n* What is the relation between groundwater levels 
            
70
fluctuance and soil moisture?\r\n* Are adjustments on in public spaces 
70
fluctuance and soil moisture?\r\n* Are adjustments on in public spaces 
            
71
(on street level) helpful to improve the soil situation for a more 
71
(on street level) helpful to improve the soil situation for a more 
            
72
climate adaptive city?\r\n\r\n## Contents of the data\r\n\r\nData are 
72
climate adaptive city?\r\n\r\n## Contents of the data\r\n\r\nData are 
            
73
being harmonized using FIWARE [Smart Data 
73
being harmonized using FIWARE [Smart Data 
            
74
Models](https://www.fiware.org/smart-data-models/). Data regarding 
74
Models](https://www.fiware.org/smart-data-models/). Data regarding 
            
75
soil moisture can be modelled using the GreenSpaceRecord model. The 
75
soil moisture can be modelled using the GreenSpaceRecord model. The 
            
76
data in this dataset provide the following elements from this data 
76
data in this dataset provide the following elements from this data 
            
77
model:\r\n\r\n* id - identifier of the sensors\r\n* recordingTimetamp 
77
model:\r\n\r\n* id - identifier of the sensors\r\n* recordingTimetamp 
            
78
- timestamp of the measurement\r\n* location - GPS location of the 
78
- timestamp of the measurement\r\n* location - GPS location of the 
            
79
sensor, GeoJSON with WGS84/EPSG:4326 coordinate\r\n* soilMoistureVwc - 
79
sensor, GeoJSON with WGS84/EPSG:4326 coordinate\r\n* soilMoistureVwc - 
            
80
percentage Volumetric Water Content of soil\r\n\r\nMeteorological data 
80
percentage Volumetric Water Content of soil\r\n\r\nMeteorological data 
            
81
can be modelled using the WeatherObserved model. The data in this 
81
can be modelled using the WeatherObserved model. The data in this 
            
82
dataset provide the following elements from this data model: \r\n\r\n* 
82
dataset provide the following elements from this data model: \r\n\r\n* 
            
83
id - identifier of the sensors\r\n* recordingTimetamp - timestamp of 
83
id - identifier of the sensors\r\n* recordingTimetamp - timestamp of 
            
84
the measurement\r\n* location - GPS location of the sensor, GeoJSON 
84
the measurement\r\n* location - GPS location of the sensor, GeoJSON 
            
85
with WGS84/EPSG:4326 coordinate\r\n* temperature - temperature in 
85
with WGS84/EPSG:4326 coordinate\r\n* temperature - temperature in 
            
86
degrees Celsius\r\n* relativeHumidity - percentage relative 
86
degrees Celsius\r\n* relativeHumidity - percentage relative 
            
87
humidity\r\n\r\n## Access the data\r\n\r\nData are available using 
87
humidity\r\n\r\n## Access the data\r\n\r\nData are available using 
            
88
different API's:\r\n\r\n* The Orion ContextBroker allows you to access 
88
different API's:\r\n\r\n* The Orion ContextBroker allows you to access 
            
89
the [current status of 
89
the [current status of 
            
90
/gravitee-scorewater-gateway.dataplatform.nl/teneo/orion/v2/entities). 
90
/gravitee-scorewater-gateway.dataplatform.nl/teneo/orion/v2/entities). 
            
91
Use the information provided by the Orion ContextBroker to compile 
91
Use the information provided by the Orion ContextBroker to compile 
            
92
requests for the Short Term History API, the ContextBroker provides 
92
requests for the Short Term History API, the ContextBroker provides 
            
93
information on which entities are present and what attributes those 
93
information on which entities are present and what attributes those 
            
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entities support. \r\n* The Short Term History API allows you to 
94
entities support. \r\n* The Short Term History API allows you to 
            
95
download historical data for the different sensors in both raw and 
95
download historical data for the different sensors in both raw and 
            
96
aggregated form in either JSON or CSV format:\r\n    * 
96
aggregated form in either JSON or CSV format:\r\n    * 
            
97
soilMoistureVwc\r\n        * JSON, 
97
soilMoistureVwc\r\n        * JSON, 
            
98
2/entities/206/attrs/soilMoistureVwc?type=GreenSpaceRecord&lastN=100), 
98
2/entities/206/attrs/soilMoistureVwc?type=GreenSpaceRecord&lastN=100), 
            
99
MoistureVwc?type=GreenSpaceRecord&aggrMethod=min&aggrPeriod=month)\r\n        
99
MoistureVwc?type=GreenSpaceRecord&aggrMethod=min&aggrPeriod=month)\r\n        
            
100
* CSW, 
100
* CSW, 
            
101
6/attrs/soilMoistureVwc?type=GreenSpaceRecord&lastN=100&fileType=csv), 
101
6/attrs/soilMoistureVwc?type=GreenSpaceRecord&lastN=100&fileType=csv), 
            
102
ype=GreenSpaceRecord&aggrMethod=min&aggrPeriod=month&fileType=csv)\r\n    
102
ype=GreenSpaceRecord&aggrMethod=min&aggrPeriod=month&fileType=csv)\r\n    
            
103
* temperature\r\n        * JSON, 
103
* temperature\r\n        * JSON, 
            
104
STH/v2/entities/240/attrs/temperature?type=WeatherObserved&lastN=100), 
104
STH/v2/entities/240/attrs/temperature?type=WeatherObserved&lastN=100), 
            
105
rs/temperature?type=WeatherObserved&aggrMethod=min&aggrPeriod=day)\r\n        
105
rs/temperature?type=WeatherObserved&aggrMethod=min&aggrPeriod=day)\r\n        
            
106
* CSW, 
106
* CSW, 
            
107
es/240/attrs/temperature?type=WeatherObserved&lastN=100&fileType=csv), 
107
es/240/attrs/temperature?type=WeatherObserved&lastN=100&fileType=csv), 
            
108
e?type=WeatherObserved&aggrMethod=min&aggrPeriod=day&fileType=csv)\r\n    
108
e?type=WeatherObserved&aggrMethod=min&aggrPeriod=day&fileType=csv)\r\n    
            
109
* relativeHumidity\r\n        * JSON, 
109
* relativeHumidity\r\n        * JSON, 
            
110
2/entities/240/attrs/relativeHumidity?type=WeatherObserved&lastN=100), 
110
2/entities/240/attrs/relativeHumidity?type=WeatherObserved&lastN=100), 
            
111
lativeHumidity?type=WeatherObserved&aggrMethod=min&aggrPeriod=day)\r\n        
111
lativeHumidity?type=WeatherObserved&aggrMethod=min&aggrPeriod=day)\r\n        
            
112
* CSW, 
112
* CSW, 
            
113
0/attrs/relativeHumidity?type=WeatherObserved&lastN=100&fileType=csv), 
113
0/attrs/relativeHumidity?type=WeatherObserved&lastN=100&fileType=csv), 
            
114
?type=WeatherObserved&aggrMethod=min&aggrPeriod=day&fileType=csv)\r\n* 
114
?type=WeatherObserved&aggrMethod=min&aggrPeriod=day&fileType=csv)\r\n* 
            
115
The OGC web services allows you to [render 
115
The OGC web services allows you to [render 
            
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vice=WMS&srs=EPSG%3A4326&format=image%2Fpng&request=GetMap&height=384) 
116
vice=WMS&srs=EPSG%3A4326&format=image%2Fpng&request=GetMap&height=384) 
            
117
of the sensors and to download historical data in different formats 
117
of the sensors and to download historical data in different formats 
            
118
such as 
118
such as 
            
119
platform_nl%3Ackan_current_green_space_record_hegcudye&version=2.0.0), 
119
platform_nl%3Ackan_current_green_space_record_hegcudye&version=2.0.0), 
            
120
aplatform_nl%3Ackan_current_green_space_record_hegcudye&version=2.0.0) 
120
aplatform_nl%3Ackan_current_green_space_record_hegcudye&version=2.0.0) 
            
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and shape file. ",
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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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vice=WMS&srs=EPSG%3A4326&format=image%2Fpng&request=GetMap&height=384"
            
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}