Soil moisture and climate data from SmartCityTrees sensors in Amersfoort

Within the frame of the SCOREwater project, the City of Amersfoort commissioned Hoefakker to install Teneo soil moisture and climate monitor sensors at several locations in the Schothorst neighbourhood and the Central Railway area. These sensors have been branded as "SmartCityTrees" by Hoefakker. The sensors measure soil moisture, temperature and humidity. Schothorst and the Central Railway area differ in groundwater levels. In Schothorst the groundwater levels are higher (average height: 0.7 meter to 1.0 meter below ground level) than in the Central Railway area (average height: lower than 1.6 meter below ground level). The lowest soil moisture sensors are placed on 1.2 meter below ground level. As a result, in the Schothorst area the sensors are located close to or in the groundwater during winter. In the Central Railway area they are located far above the groundwater level. This makes both areas interesting to include. What all soil moisture sensors have in common is that they are all located nearby trees and in public spaces. Locations differ in terms of: being in the sun or in the shade, being in a green setting (unpaved, such as parks) or being in a paved setting, and being near surface water or not. Because of the differences between the locations the sensors have been installed in, data from the sensors can be used to investigate questions such as:

What is the influence of the type of surface on soil moisture levels?

Does the nearby presence of surface water affect soil moisture?

What is the influence of heat on soil moisture?

What is the relation between groundwater levels fluctuance and soil moisture?

Are adjustments on in public spaces (on street level) helpful to improve the soil situation for a more climate adaptive city?

The soil moisture dataset contains soil moisture VWC (volumetric water content, the ratio of water volume to soil volume). This is a percentage represented as a number between 0 and 1. 0.73 for example is 73%.

The climate dataset contains temperature in degrees Celsius and the relative humidity. Relative humidity is a percentage represented as a number between 0 and 1 as well.

Time period: from 2021-01-01 to 2022-12-31.