Drone Imagery Combined With Soil Moisture Monitoring for Efficient Irrigation

Urban green infrastructure provide several benefits to inhabitants and helps cities adapt to climate change. This project aimed to develop a landscaping data integrator that provides smart data solutions for urban green infrastructure management, using soil, moisture sensors, and plant health imagery associated with workflow support for watering. Geostatistics was used to produce maps of soil moisture and compare them with the Normalized Difference Vegetation Index (NDVI) and thermal images of an urban park in Loule, Portugal. The results revealed a linear regression with a coefficient of determination R2 = 0.9607, R2 = 0.9432, R2 = 0.9523, respectively, for the months of August, September, and October. The method can be used to optimize urban green space management and assist in watering decisions.