Advanced Methods for the Analysis of Multitemporal Sentinel 2 Images

Claudia Paris; Lorenzo Bruzzone; Francesca Bovolo; Diego Fernández-Prieto; Y. T. Solano-Correa; Massimo Zanetti

Abstract

Due to the recent launch of the optical remote sensing satellite Sentinel 2 (S-2) contellation, it is necessary to define advanced methods tailored to the specific properties of the unprecedented data provided by this mission. S-2 is the first optical Earth observation mission including three bands in the “red edge” acquired at high spatial resolution (10-20m), which provide key information on vegetation and agricultural state. Moreover, S-2 acquires dense time series (TS) of images with worldwide coverage at high temporal resolution (about 5 days depending on the latitude), thus determining a new standard for the use of high resolution optical data for multitemporal analysis. The “S2-4Sci Land and Water - Multitemporal Analysis” project (2016-2018), funded by the European Space
Agency (ESA) in the framework of the “Scientific Exploitation of Operational Missions” (SEOM) program, aims at developing unsupervised methods to perform
advanced multitemporal analyses of S-2 images. The project investigates three methodological areas: i) land-cover maps updating, ii) land-cover change
detection, and iii) time-series analysis.

Original language	English
Publication status	Published - 1 Jun 2018
Externally published	Yes
Event	2nd Italian Workshop on Radar and Remote Sensing 2018 - Pavia, Italy Duration: 28 Apr 2018 → 29 Apr 2018 Conference number: 2

Workshop

Workshop	2nd Italian Workshop on Radar and Remote Sensing 2018
Country/Territory	Italy
City	Pavia
Period	28/04/18 → 29/04/18

Keywords

ITC-CV

Cite this

@conference{249fac14aa644ebe809b06e5065ab55e,

title = "Advanced Methods for the Analysis of Multitemporal Sentinel 2 Images",

abstract = "Due to the recent launch of the optical remote sensing satellite Sentinel 2 (S-2) contellation, it is necessary to define advanced methods tailored to the specific properties of the unprecedented data provided by this mission. S-2 is the first optical Earth observation mission including three bands in the “red edge” acquired at high spatial resolution (10-20m), which provide key information on vegetation and agricultural state. Moreover, S-2 acquires dense time series (TS) of images with worldwide coverage at high temporal resolution (about 5 days depending on the latitude), thus determining a new standard for the use of high resolution optical data for multitemporal analysis. The “S2-4Sci Land and Water - Multitemporal Analysis” project (2016-2018), funded by the European Space Agency (ESA) in the framework of the “Scientific Exploitation of Operational Missions” (SEOM) program, aims at developing unsupervised methods to perform advanced multitemporal analyses of S-2 images. The project investigates three methodological areas: i) land-cover maps updating, ii) land-cover change detection, and iii) time-series analysis.",

keywords = "ITC-CV",

author = "Claudia Paris and Lorenzo Bruzzone and Francesca Bovolo and Diego Fern{\'a}ndez-Prieto and Solano-Correa, {Y. T.} and Massimo Zanetti",

year = "2018",

month = jun,

day = "1",

language = "English",

note = "2nd Italian Workshop on Radar and Remote Sensing 2018<br/> ; Conference date: 28-04-2018 Through 29-04-2018",

}

TY - CONF

T1 - Advanced Methods for the Analysis of Multitemporal Sentinel 2 Images

AU - Paris, Claudia

AU - Bruzzone, Lorenzo

AU - Bovolo, Francesca

AU - Fernández-Prieto, Diego

AU - Solano-Correa, Y. T.

AU - Zanetti, Massimo

N1 - Conference code: 2

PY - 2018/6/1

Y1 - 2018/6/1

N2 - Due to the recent launch of the optical remote sensing satellite Sentinel 2 (S-2) contellation, it is necessary to define advanced methods tailored to the specific properties of the unprecedented data provided by this mission. S-2 is the first optical Earth observation mission including three bands in the “red edge” acquired at high spatial resolution (10-20m), which provide key information on vegetation and agricultural state. Moreover, S-2 acquires dense time series (TS) of images with worldwide coverage at high temporal resolution (about 5 days depending on the latitude), thus determining a new standard for the use of high resolution optical data for multitemporal analysis. The “S2-4Sci Land and Water - Multitemporal Analysis” project (2016-2018), funded by the European Space Agency (ESA) in the framework of the “Scientific Exploitation of Operational Missions” (SEOM) program, aims at developing unsupervised methods to perform advanced multitemporal analyses of S-2 images. The project investigates three methodological areas: i) land-cover maps updating, ii) land-cover change detection, and iii) time-series analysis.

AB - Due to the recent launch of the optical remote sensing satellite Sentinel 2 (S-2) contellation, it is necessary to define advanced methods tailored to the specific properties of the unprecedented data provided by this mission. S-2 is the first optical Earth observation mission including three bands in the “red edge” acquired at high spatial resolution (10-20m), which provide key information on vegetation and agricultural state. Moreover, S-2 acquires dense time series (TS) of images with worldwide coverage at high temporal resolution (about 5 days depending on the latitude), thus determining a new standard for the use of high resolution optical data for multitemporal analysis. The “S2-4Sci Land and Water - Multitemporal Analysis” project (2016-2018), funded by the European Space Agency (ESA) in the framework of the “Scientific Exploitation of Operational Missions” (SEOM) program, aims at developing unsupervised methods to perform advanced multitemporal analyses of S-2 images. The project investigates three methodological areas: i) land-cover maps updating, ii) land-cover change detection, and iii) time-series analysis.

KW - ITC-CV

UR - https://iris.unitn.it/handle/11572/355061

M3 - Abstract

T2 - 2nd Italian Workshop on Radar and Remote Sensing 2018<br/>

Y2 - 28 April 2018 through 29 April 2018

ER -

Advanced Methods for the Analysis of Multitemporal Sentinel 2 Images

Abstract

Workshop

Keywords

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