Clustering of Remotely Sensed Time Series using Functional Principal Component Analysis to Monitor Crops-Reference-Cited by-同舟云学术

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Clustering of Remotely Sensed Time Series using Functional Principal Component Analysis to Monitor Crops

Published:2022-11-03 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)
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Author:

Coviello Luca¹,Martini Francesco Maria²,Cesaretti Lorenzo³,Pesaresi Simone²,Solfanelli Francesco²,Mancini Adriano⁴

Affiliation:

1. University of Trento,Trento,Italy

2. Università Politecnica delle Marche,Department of Agricultural, Food and Environmental Sciences (D3A),Ancona,Italy

3. Centro di ricerca, Foreste e Legno Arezzo,CREA,Arezzo,Italy

4. VRAI Lab, Università Politecnica delle Marche,Dipartimento di Ingegneria dell'Informazione (DII),Ancona,Italy

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9964476/9964488/09964799.pdf?arnumber=9964799

Reference18 articles.

1. Mapping Mediterranean Forest Plant Associations and Habitats with Functional Principal Component Analysis Using Landsat 8 NDVI Time Series

2. Functional Analysis for Habitat Mapping in a Special Area of Conservation Using Sentinel-2 Time-Series Data

3. Comparing vegetation indices from Sentinel-2 and Landsat 8 under different vegetation gradients based on a controlled grazing experiment

4. Methodology for the Definition of Durum Wheat Yield Homogeneous Zones by Using Satellite Spectral Indices

5. Farming and Earth Observation: Sentinel-2 data to estimate within-field wheat grain yield

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Evaluation and Selection of Multi-Spectral Indices to Classify Vegetation Using Multivariate Functional Principal Component Analysis;Remote Sensing;2024-03-30

2. Time Series from Sentinel-2 for Organic Durum Wheat Yield Prediction Using Functional Data Analysis and Deep Learning;Agronomy;2024-01-01

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