Using Apps to Display and Analyze Sensor Data

Sensor data provides critical real-time and historical insights into environmental and crop conditions. Common sensor sources include soil moisture probes, weather stations, multispectral cameras on drones, and GPS-enabled yield monitors. These sensors often store data in formats such as CSV, GeoJSON, or shapefiles, which can be easily imported into QGIS. Integration starts with ensuring that each dataset is georeferenced — either directly from the sensor’s GPS or by manually assigning coordinates. Once imported, the data can be joined to existing spatial layers (such as field boundaries or forest management compartments) for further analysis. For example, soil moisture readings collected at multiple points can be interpolated using QGIS’s IDW Interpolation tool to create continuous moisture maps that inform irrigation decisions. Similarly, canopy height data from LiDAR sensors can be processed in QGIS to identify areas of poor growth in forest stands.

Practical workflows increasingly involve mobile data collection apps that link directly with QGIS. Tools like QField allow field operators to collect sensor readings, photos, and GPS points directly on-site, and sync them to a central GIS project. In precision agriculture, a farmer might use QField to walk through a wheat field, recording leaf colour readings from a chlorophyll meter at geotagged locations. Back in QGIS, this data can be symbolised with graduated colours to quickly highlight nitrogen deficiencies, and combined with satellite NDVI layers to plan targeted fertiliser application.

These app-based workflows are not limited to simple display; they enable real-time decision-making. For example, integrating weather station data streams via APIs into QGIS allows a forester to visualise microclimate patterns across a plantation, correlate them with pest outbreak records, and design targeted treatment zones. Similarly, connecting drone-derived NDVI maps with in-field sensor data enables farmers to validate aerial imagery, refine management zones, and adjust harvest plans. By combining mobile data collection, sensor integration, and GIS analysis, QGIS serves as the central hub for transforming raw sensor readings into actionable maps for precision agriculture and forestry operations.

SensLog Dashboard

SensLog is a web application for displaying data using graphs. A graph can display a single sensor or a unit containing multiple sensors. Data is obtained from measurements taken by various types of sensors. The web application does not require the user to install any additional programs. All that is needed to run the web application is a web browser with cookies and JavaScript enabled.

The main dashboard page of SensLog dashboard.

After successfully logging in, the dashboard itself will be displayed. Ordinary users cannot add new users. If the logged-in user has admin privileges, a button for adding a new user will also be displayed in the left corner.

For logged-in users, the units assigned to that user are displayed. The “Sensors graph button” displays a graph for a specific unit. Each unit can contain multiple sensors. The unit contains multiple sensors. When the unit is pressed, a list of sensors belonging to that unit is displayed. The sensor can be displayed using the View graph button after expanding the specific unit. The sensor can be edited using the Edit sensor button and deleted using the Delete sensor button.

Graph of thermometer sensors in SensLog dashboard.