The Usefulness of Drone Imagery and Remote Sensing Methods for Monitoring Turfgrass Irrigation
[EN] Irrigation is an essential input for grasslands sustainability, especially in seasons where rainfall is not regular and insufficient. The scarcity of water in many regions of the world decreases the timing and quantity of irrigation and affects the quality of grasslands. The use of remote sensi...
| Autores: | , , , , |
|---|---|
| Tipo de recurso: | capítulo de libro |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/232747 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/232747 |
| Access Level: | acceso abierto |
| Palabra clave: | Remote sensing Irrigation Drone imagery Vegetation indices Canopy temperature Soil moisture Turfgrass sustainability |
| Sumario: | [EN] Irrigation is an essential input for grasslands sustainability, especially in seasons where rainfall is not regular and insufficient. The scarcity of water in many regions of the world decreases the timing and quantity of irrigation and affects the quality of grasslands. The use of remote sensing techniques as precise methods to control the efficiency and the management of irrigation contribute to the more sustainability of grasslands. Vegetation indices and Canopy Temperature (CT) are the most common remote sensing approaches used for correct irrigation scheduling. In this study, we evaluated the Green Area (GA) vegetation index calculated from Red, Green, and Blue (RGB) drone images and the plant water status obtained through the CT measured by an infrared thermometer and drone thermal imagery of turfgrass species growing under different water regimes (limited and high irrigation). Experimental plots Soil Moisture (SM) was controlled by soil sensors humidity. Both RGB and thermal images taken by a drone showed heterogeneity in turfgrass growth, with dries zones and absence of vegetation observed under limited irrigation. Under reduced irrigation conditions, lower SM and GA and higher CT were observed. Whereas, under the high irrigation values of SM and GA increased, while CT decreased. The SM data correlated highly with both vegetation index and CT. This study highlights the usefulness of drones and sensors to evaluate turfgrass growth and irrigation efficiency. |
|---|