Leveraging Google Earth Engine for a More Effective Grassland Management: A Decision Support Application Perspective.

EVI Google Earth Engine (GEE) Sentinel-2 Web-GIS decision support systems grassland grazing management harmonic modeling

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
27 Jan 2024
Historique:
received: 30 10 2023
revised: 11 01 2024
accepted: 24 01 2024
medline: 10 2 2024
pubmed: 10 2 2024
entrez: 10 2 2024
Statut: epublish

Résumé

Grasslands cover a substantial portion of the earth's surface and agricultural land and is crucial for human well-being and livestock farming. Ranchers and grassland management authorities face challenges in effectively controlling herders' grazing behavior and grassland utilization due to underdeveloped infrastructure and poor communication in pastoral areas. Cloud-based grazing management and decision support systems (DSS) are needed to address this issue, promote sustainable grassland use, and preserve their ecosystem services. These systems should enable rapid and large-scale grassland growth and utilization monitoring, providing a basis for decision-making in managing grazing and grassland areas. In this context, this study contributes to the objectives of the EU LIFE IMAGINE project, aiming to develop a Web-GIS app for conserving and monitoring Umbria's grasslands and promoting more informed decisions for more sustainable livestock management. The app, called "Praterie" and developed in Google Earth Engine, utilizes historical Sentinel-2 satellite data and harmonic modeling of the EVI (Enhanced Vegetation Index) to estimate vegetation growth curves and maturity periods for the forthcoming vegetation cycle. The app is updated in quasi-real time and enables users to visualize estimates for the upcoming vegetation cycle, including the maximum greenness, the days remaining to the subsequent maturity period, the accuracy of the harmonic models, and the grassland greenness status in the previous 10 days. Even though future additional developments can improve the informative value of the Praterie app, this platform can contribute to optimizing livestock management and biodiversity conservation by providing timely and accurate data about grassland status and growth curves.

Identifiants

pubmed: 38339552
pii: s24030834
doi: 10.3390/s24030834
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Cecilia Parracciani (C)

Department of Agricultural, Food, and Environmental Sciences, University of Perugia, 06121 Perugia, Italy.

Daniela Gigante (D)

Department of Agricultural, Food, and Environmental Sciences, University of Perugia, 06121 Perugia, Italy.

Federica Bonini (F)

Department of Agricultural, Food, and Environmental Sciences, University of Perugia, 06121 Perugia, Italy.

Anna Grassi (A)

Department of Agricultural, Food, and Environmental Sciences, University of Perugia, 06121 Perugia, Italy.

Luciano Morbidini (L)

Department of Agricultural, Food, and Environmental Sciences, University of Perugia, 06121 Perugia, Italy.

Mariano Pauselli (M)

Department of Agricultural, Food, and Environmental Sciences, University of Perugia, 06121 Perugia, Italy.

Bernardo Valenti (B)

Department of Agricultural, Food, and Environmental Sciences, University of Perugia, 06121 Perugia, Italy.

Emanuele Lilli (E)

Department of Agricultural, Food, and Environmental Sciences, University of Perugia, 06121 Perugia, Italy.

Francesco Antonielli (F)

Department of Agricultural, Food, and Environmental Sciences, University of Perugia, 06121 Perugia, Italy.

Marco Vizzari (M)

Department of Agricultural, Food, and Environmental Sciences, University of Perugia, 06121 Perugia, Italy.

Classifications MeSH