terclim by ICS banner
IVES 9 IVES Conference Series 9 Learning from remote sensing data: a case study in the Trentino region 

Learning from remote sensing data: a case study in the Trentino region 

Abstract

Recent developments in satellite technology have yielded a substantial volume of data, providing a foundation for various machine learning approaches. These applications, utilizing extensive datasets, offer valuable insights into Earth’s conditions. Examples include climate change analysis, risk and damage assessment, water quality evaluation, and crop monitoring. Our study focuses on exploiting satellite thermal and multispectral imaging, and vegetation indexes, such as NDVI, in conjunction with ground truth information about soil type, land usage (forest, urban, crop cultivation), and irrigation water sources in the Trentino region in North-East of Italy. Trentino, characterized by diverse landscapes ranging from forests to crop fields, is notable for its grapevine cultivation, a significant contributor to the Italian wine industry. Our research aims to analyze the past two decades of satellite data (NASA and Copernicus) using supervised and unsupervised learning methods. The objective is to develop models for soil classification, assessing crop health and growth stage (phenology), and optimizing water management practices, specifically in the context of tree crops (mainly vineyards and apple orchards) in this region. This analytical approach seeks to contribute to a more systematic understanding of the environmental and agricultural dynamics in Trentino, facilitating informed and sustainable land management practices.

DOI:

Publication date: June 14, 2024

Issue: Open GPB 2024

Type: Poster

Authors

Marco Moretto1*, Luca Delucchi1, Roberto Zorer1, Pietro Franceschi1

1 Research and Innovation Centre, Fondazione Edmund Mach, San Michele all’Adige (Trento), Italy

Contact the author*

Keywords

machine learning, remote sensing, Trentino, soil, water

Tags

IVES Conference Series | Open GPB | Open GPB 2024

Citation

Related articles…

Study of Malvasia di Candia Aromatica shelf-life: effect of time and temperature on aroma compounds through an HS-SPME GCxGC-Ms approach

Young white wines should be consumed within a short time after bottling to avoid loss of their fresh, fruity attributes. Shelf-life of white wines can be extended if they are stored under suitable conditions of time and temperature prior to consumption.

Exemples de zonage au Chili et en Amérique Latine

Ce document présente la situation viticole des appellations d’origine en Argentine, Brésil, Chili et Uruguay.
L’étude s’est restreinte uniquement à ces 4 pays, bien qu’il en existe d’autres avec une production viticole d’une certaine importance.

Modeling from functioning of a grape berry to the whole plant

Grape quality is a complex trait that mainly refers to berry chemical composition, including sugars, organic acids, phenolics, aroma and aroma precursor compounds.

The role of NAC61 transcription factor in the regulation of berry ripening progression 

The undergoing global warming scenario is affecting grapevines phenology, including the timing of berry ripening and harvest date, negatively impacting production and quality. This work reports the crucial role of NAC61, a grapevine NAC transcription factor, in regulating metabolic processes occurring from the onset of ripening onwards. NAC61 high confidence targets mainly represent genes acting on stilbene biosynthesis and regulation, and in osmotic and oxidative/biotic stress-related responses. The direct regulation of the stilbene synthase regulator MYB14, the osmotic stress-related gene DHN1b, and the Botrytis cinerea susceptibility gene WRKY52, were all further validated.

Evaluation of intra-vineyard spatial and temporal variability of leaf area index using multispectral images obtained by satellite (Landsat 8, Sentinel-2) and unmanned aerial vehicle platforms

Estimation of vineyard leaf area index (LAI) is an important aspect for the winegrowers. However, tracking and monitoring are difficult tasks due to time constraints. Satellite and unmanned aerial vehicle (UAV) imaging have become a practical monitoring method for LAI. Nevertheless, for a proper LAI determination, the image’s spatial resolution is a key factor, since low-resolution images are incapable of distinguishing between adjacent vines due to the large area covered in each pixel, this leads to misinterpretation or generalisation of vineyard information.