Timely Mapping of Crop Stage and Watering Events Through Sentinel-L Time-Series

Lorenzo Iannini; Ramses Molijn; Silvia Alfieri; Susan Steele-Dunne; Massimo Menenti

doi:10.1109/IGARSS.2018.8518906

Timely Mapping of Crop Stage and Watering Events Through Sentinel-L Time-Series

Lorenzo Iannini, Ramses Molijn, Silvia Alfieri, Susan Steele-Dunne, Massimo Menenti

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

Abstract

Reliable and timely mapping of crop growth conditions and of their water resources is considered a prioritary application in light of the abrupt climate changes. With this view, the paper presents a novel approach that makes use of dense C-Band time-series for the timely estimation of crop growth stages and for the detection of changes in crop water conditions, especially related to precipitation and irrigation events. Aided by vegetation indexes extracted from Landsat and Sentinel-2 imagery, the proposed Sentinel-l centered method exploits both temporal patterns of crop growth and spatial patterns of water anomalies to enhance its classification robustness.

Original language	English
Title of host publication	IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
Editors	Jose Moreno
Publisher	IEEE
Pages	196-199
Volume	2018
ISBN (Electronic)	978-1-5386-7150-4
ISBN (Print)	978-1-5386-7151-1
DOIs	https://doi.org/10.1109/IGARSS.2018.8518906
Publication status	Published - 2018
Event	IGARSS 2018: 2018 IEEE International Geoscience and Remote Sensing Symposium: Observing, Understanding And Forecasting The Dynamics Of Our Planet - Valencia, Spain Duration: 22 Jul 2018 → 27 Jul 2018 Conference number: 38 https://www.igarss2018.org/

Conference

Conference	IGARSS 2018: 2018 IEEE International Geoscience and Remote Sensing Symposium
Abbreviated title	IGARSS 2018
Country/Territory	Spain
City	Valencia
Period	22/07/18 → 27/07/18
Internet address	https://www.igarss2018.org/

Keywords

Synthetic Aperture Radar
C-Band, Sentinel
data assimilation
land cover mapping
soil
agriculture
precipitation
irrigation

Access to Document

10.1109/IGARSS.2018.8518906

Cite this

@inproceedings{779267f3257445c780e0943da4f0144f,

title = "Timely Mapping of Crop Stage and Watering Events Through Sentinel-L Time-Series",

abstract = "Reliable and timely mapping of crop growth conditions and of their water resources is considered a prioritary application in light of the abrupt climate changes. With this view, the paper presents a novel approach that makes use of dense C-Band time-series for the timely estimation of crop growth stages and for the detection of changes in crop water conditions, especially related to precipitation and irrigation events. Aided by vegetation indexes extracted from Landsat and Sentinel-2 imagery, the proposed Sentinel-l centered method exploits both temporal patterns of crop growth and spatial patterns of water anomalies to enhance its classification robustness.",

keywords = "Synthetic Aperture Radar, C-Band, Sentinel, data assimilation, land cover mapping, soil, agriculture, precipitation, irrigation",

author = "Lorenzo Iannini and Ramses Molijn and Silvia Alfieri and Susan Steele-Dunne and Massimo Menenti",

year = "2018",

doi = "10.1109/IGARSS.2018.8518906",

language = "English",

isbn = "978-1-5386-7151-1 ",

volume = "2018",

pages = "196--199",

editor = "Jose Moreno",

booktitle = "IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium",

publisher = "IEEE",

address = "United States",

note = "IGARSS 2018: 2018 IEEE International Geoscience and Remote Sensing Symposium : Observing, Understanding And Forecasting The Dynamics Of Our Planet, IGARSS 2018 ; Conference date: 22-07-2018 Through 27-07-2018",

url = "https://www.igarss2018.org/",

}

Iannini, L, Molijn, R, Alfieri, S , Steele-Dunne, S & Menenti, M 2018, Timely Mapping of Crop Stage and Watering Events Through Sentinel-L Time-Series. in J Moreno (ed.), IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium . vol. 2018, IEEE, pp. 196-199, IGARSS 2018: 2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain, 22/07/18. https://doi.org/10.1109/IGARSS.2018.8518906

Timely Mapping of Crop Stage and Watering Events Through Sentinel-L Time-Series. / Iannini, Lorenzo; Molijn, Ramses; Alfieri, Silvia et al.
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium . ed. / Jose Moreno. Vol. 2018 IEEE, 2018. p. 196-199.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Timely Mapping of Crop Stage and Watering Events Through Sentinel-L Time-Series

AU - Iannini, Lorenzo

AU - Molijn, Ramses

AU - Alfieri, Silvia

AU - Steele-Dunne, Susan

AU - Menenti, Massimo

N1 - Conference code: 38

PY - 2018

Y1 - 2018

N2 - Reliable and timely mapping of crop growth conditions and of their water resources is considered a prioritary application in light of the abrupt climate changes. With this view, the paper presents a novel approach that makes use of dense C-Band time-series for the timely estimation of crop growth stages and for the detection of changes in crop water conditions, especially related to precipitation and irrigation events. Aided by vegetation indexes extracted from Landsat and Sentinel-2 imagery, the proposed Sentinel-l centered method exploits both temporal patterns of crop growth and spatial patterns of water anomalies to enhance its classification robustness.

AB - Reliable and timely mapping of crop growth conditions and of their water resources is considered a prioritary application in light of the abrupt climate changes. With this view, the paper presents a novel approach that makes use of dense C-Band time-series for the timely estimation of crop growth stages and for the detection of changes in crop water conditions, especially related to precipitation and irrigation events. Aided by vegetation indexes extracted from Landsat and Sentinel-2 imagery, the proposed Sentinel-l centered method exploits both temporal patterns of crop growth and spatial patterns of water anomalies to enhance its classification robustness.

KW - Synthetic Aperture Radar

KW - C-Band, Sentinel

KW - data assimilation

KW - land cover mapping

KW - soil

KW - agriculture

KW - precipitation

KW - irrigation

U2 - 10.1109/IGARSS.2018.8518906

DO - 10.1109/IGARSS.2018.8518906

M3 - Conference contribution

SN - 978-1-5386-7151-1

VL - 2018

SP - 196

EP - 199

BT - IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium

A2 - Moreno, Jose

PB - IEEE

T2 - IGARSS 2018: 2018 IEEE International Geoscience and Remote Sensing Symposium

Y2 - 22 July 2018 through 27 July 2018

ER -

Timely Mapping of Crop Stage and Watering Events Through Sentinel-L Time-Series

Abstract

Conference

Keywords

Access to Document

Fingerprint

Cite this