Deep Learning Approach for Terrace Vineyards Detection from Google Earth Satellite Imagery
- Resource Type
- Conference
- Authors
- Figueiredo, Nuno; Neto, Alexandre; Cunha, Antonio; Sousa, Joaquim J.; Sousa, Antonio
- Source
- IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium Geoscience and Remote Sensing Symposium, IGARSS 2022 - 2022 IEEE International. :5824-5827 Jul, 2022
- Subject
- Aerospace
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Fields, Waves and Electromagnetics
Geoscience
Photonics and Electrooptics
Power, Energy and Industry Applications
Signal Processing and Analysis
Earth
Deep learning
Satellites
Crops
Manuals
Internet
Rivers
Remote sensing
Terrace Vineyards
Deep Learning
Satellite
- Language
- ISSN
- 2153-7003
On rugged slopes overlooking the Douro River we find the Alto Douro Wine Region in Portugal, populated by plantations in schist lands of difficult access and mostly manual work. The combined features of this region are a source of motivation to explore remote sensing techniques associated with artificial intelligence. In this paper, a preliminary approach for terrace vineyards detection is presented. This is a key-enabling task towards the achievement of important goals such as multi-temporal crop evaluation and cultures characterization. The proposed methodology consists in the application of a deep learning model (U-net) to detect the terrace vineyards using satellite images dataset acquired with Google Earth Pro. The proposed methodology showed very promising detection capabilities.