COSMO-SkyMed multi-temporal data for land cover classification and soil moisture retrieval over an agricultural site in Southern Australia

Giuseppe Satalino; Rocco Panciera; Anna Balenzano; Francesco Mattia; Jeffrey Walker

doi:10.1109/IGARSS.2012.6352317

COSMO-SkyMed multi-temporal data for land cover classification and soil moisture retrieval over an agricultural site in Southern Australia

Giuseppe Satalino
, Rocco Panciera
, Anna Balenzano
, Francesco Mattia
, Jeffrey Walker

Civil & Environmental Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

17 Citations (Scopus)

Abstract

This paper uses a time-series of COSMO-SkyMed SAR images for land cover classification and soil moisture retrieval over an agricultural area located in Southern Australia. The SAR products analyzed are 11 StripMap Ping Pong images, at HH and HV polarizations, acquired at 21° incidence angle and with a revisiting time of either 8 or 16 days. The classification accuracy has been assessed as a function of the polarization and the number of images analyzed. Results confirm that the temporal information is crucial to improve the classification results. An overall accuracy of approximately 82% was achieved for 10 classes. Moreover, soil moisture (m_v) maps over bare or sparsely vegetated areas have been retrieved by means of the SMOSAR-X ('Soil MOisture retrieval from multi-temporal SAR data') algorithm, developed in view of the forthcoming Sentinel-1 data and then adapted to X-band SAR data. The SMOSAR-X algorithm is shown to produce m_v maps with an rmse of 6.6% v/v.

Original language	English
Title of host publication	2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2012) -Proceedings
Subtitle of host publication	July 22–27, 2012, Munich, Germany
Editors	Irena Hajnsek, Helmut Rott
Place of Publication	Piscataway, NJ
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	5701-5704
Number of pages	4
ISBN (Electronic)	9781467311588, 9781467311595
ISBN (Print)	9781467311601
DOIs	https://doi.org/10.1109/IGARSS.2012.6352317
Publication status	Published - 2012
Event	IEEE International Geoscience and Remote Sensing Symposium 2012 - International Congress Centre, Munich, Germany Duration: 22 Jul 2012 → 27 Jul 2012 Conference number: 32nd http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6334512 (IEEE Conference Proceedings)

Conference

Conference	IEEE International Geoscience and Remote Sensing Symposium 2012
Abbreviated title	IGARSS 2012
Country/Territory	Germany
City	Munich
Period	22/07/12 → 27/07/12
Internet address	http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6334512 (IEEE Conference Proceedings)

Keywords

COSMO-SkyMed
Multitemporal Classification
SAR
Soil Moisture retrieval
X-band

Access to Document

10.1109/IGARSS.2012.6352317

Cite this

Satalino, G., Panciera, R., Balenzano, A., Mattia, F., & Walker, J. (2012). COSMO-SkyMed multi-temporal data for land cover classification and soil moisture retrieval over an agricultural site in Southern Australia. In I. Hajnsek, & H. Rott (Eds.), 2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2012) -Proceedings: July 22–27, 2012, Munich, Germany (pp. 5701-5704). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/IGARSS.2012.6352317

Satalino, Giuseppe ; Panciera, Rocco ; Balenzano, Anna et al. / COSMO-SkyMed multi-temporal data for land cover classification and soil moisture retrieval over an agricultural site in Southern Australia. 2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2012) -Proceedings: July 22–27, 2012, Munich, Germany. editor / Irena Hajnsek ; Helmut Rott. Piscataway, NJ : IEEE, Institute of Electrical and Electronics Engineers, 2012. pp. 5701-5704

@inproceedings{f42ef02a4447455bbb6449942626b8c3,

title = "COSMO-SkyMed multi-temporal data for land cover classification and soil moisture retrieval over an agricultural site in Southern Australia",

abstract = "This paper uses a time-series of COSMO-SkyMed SAR images for land cover classification and soil moisture retrieval over an agricultural area located in Southern Australia. The SAR products analyzed are 11 StripMap Ping Pong images, at HH and HV polarizations, acquired at 21° incidence angle and with a revisiting time of either 8 or 16 days. The classification accuracy has been assessed as a function of the polarization and the number of images analyzed. Results confirm that the temporal information is crucial to improve the classification results. An overall accuracy of approximately 82\% was achieved for 10 classes. Moreover, soil moisture (mv) maps over bare or sparsely vegetated areas have been retrieved by means of the SMOSAR-X ('Soil MOisture retrieval from multi-temporal SAR data') algorithm, developed in view of the forthcoming Sentinel-1 data and then adapted to X-band SAR data. The SMOSAR-X algorithm is shown to produce mv maps with an rmse of 6.6\% v/v. ",

keywords = "COSMO-SkyMed, Multitemporal Classification, SAR, Soil Moisture retrieval, X-band",

author = "Giuseppe Satalino and Rocco Panciera and Anna Balenzano and Francesco Mattia and Jeffrey Walker",

year = "2012",

doi = "10.1109/IGARSS.2012.6352317",

language = "English",

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booktitle = "2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2012) -Proceedings",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

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note = "IEEE International Geoscience and Remote Sensing Symposium 2012, IGARSS 2012 ; Conference date: 22-07-2012 Through 27-07-2012",

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Satalino, G, Panciera, R, Balenzano, A, Mattia, F & Walker, J 2012, COSMO-SkyMed multi-temporal data for land cover classification and soil moisture retrieval over an agricultural site in Southern Australia. in I Hajnsek & H Rott (eds), 2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2012) -Proceedings: July 22–27, 2012, Munich, Germany. IEEE, Institute of Electrical and Electronics Engineers, Piscataway, NJ, pp. 5701-5704, IEEE International Geoscience and Remote Sensing Symposium 2012, Munich, Berlin, Germany, 22/07/12. https://doi.org/10.1109/IGARSS.2012.6352317

COSMO-SkyMed multi-temporal data for land cover classification and soil moisture retrieval over an agricultural site in Southern Australia. / Satalino, Giuseppe; Panciera, Rocco; Balenzano, Anna et al.
2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2012) -Proceedings: July 22–27, 2012, Munich, Germany. ed. / Irena Hajnsek; Helmut Rott. Piscataway, NJ: IEEE, Institute of Electrical and Electronics Engineers, 2012. p. 5701-5704.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

TY - GEN

T1 - COSMO-SkyMed multi-temporal data for land cover classification and soil moisture retrieval over an agricultural site in Southern Australia

AU - Satalino, Giuseppe

AU - Panciera, Rocco

AU - Balenzano, Anna

AU - Mattia, Francesco

AU - Walker, Jeffrey

N1 - Conference code: 32nd

PY - 2012

Y1 - 2012

N2 - This paper uses a time-series of COSMO-SkyMed SAR images for land cover classification and soil moisture retrieval over an agricultural area located in Southern Australia. The SAR products analyzed are 11 StripMap Ping Pong images, at HH and HV polarizations, acquired at 21° incidence angle and with a revisiting time of either 8 or 16 days. The classification accuracy has been assessed as a function of the polarization and the number of images analyzed. Results confirm that the temporal information is crucial to improve the classification results. An overall accuracy of approximately 82% was achieved for 10 classes. Moreover, soil moisture (mv) maps over bare or sparsely vegetated areas have been retrieved by means of the SMOSAR-X ('Soil MOisture retrieval from multi-temporal SAR data') algorithm, developed in view of the forthcoming Sentinel-1 data and then adapted to X-band SAR data. The SMOSAR-X algorithm is shown to produce mv maps with an rmse of 6.6% v/v.

AB - This paper uses a time-series of COSMO-SkyMed SAR images for land cover classification and soil moisture retrieval over an agricultural area located in Southern Australia. The SAR products analyzed are 11 StripMap Ping Pong images, at HH and HV polarizations, acquired at 21° incidence angle and with a revisiting time of either 8 or 16 days. The classification accuracy has been assessed as a function of the polarization and the number of images analyzed. Results confirm that the temporal information is crucial to improve the classification results. An overall accuracy of approximately 82% was achieved for 10 classes. Moreover, soil moisture (mv) maps over bare or sparsely vegetated areas have been retrieved by means of the SMOSAR-X ('Soil MOisture retrieval from multi-temporal SAR data') algorithm, developed in view of the forthcoming Sentinel-1 data and then adapted to X-band SAR data. The SMOSAR-X algorithm is shown to produce mv maps with an rmse of 6.6% v/v.

KW - COSMO-SkyMed

KW - Multitemporal Classification

KW - SAR

KW - Soil Moisture retrieval

KW - X-band

UR - https://www.scopus.com/pages/publications/84873185142

U2 - 10.1109/IGARSS.2012.6352317

DO - 10.1109/IGARSS.2012.6352317

M3 - Conference Paper

AN - SCOPUS:84873185142

SN - 9781467311601

SP - 5701

EP - 5704

BT - 2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2012) -Proceedings

A2 - Hajnsek, Irena

A2 - Rott, Helmut

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Piscataway, NJ

T2 - IEEE International Geoscience and Remote Sensing Symposium 2012

Y2 - 22 July 2012 through 27 July 2012

ER -

Satalino G, Panciera R, Balenzano A, Mattia F, Walker J. COSMO-SkyMed multi-temporal data for land cover classification and soil moisture retrieval over an agricultural site in Southern Australia. In Hajnsek I, Rott H, editors, 2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2012) -Proceedings: July 22–27, 2012, Munich, Germany. Piscataway, NJ: IEEE, Institute of Electrical and Electronics Engineers. 2012. p. 5701-5704 doi: 10.1109/IGARSS.2012.6352317

COSMO-SkyMed multi-temporal data for land cover classification and soil moisture retrieval over an agricultural site in Southern Australia

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