Comparison of crop classification capabilities of spaceborne multi-parameter SAR data

Xin Tian; Erxue Chen; Zengyuan Li; Z. Bob Su; Feilong Ling; Lina Bai; Fengyu Wang

doi:10.1109/IGARSS.2010.5651326

Comparison of crop classification capabilities of spaceborne multi-parameter SAR data

Xin Tian^*
, Erxue Chen
, Zengyuan Li
, Z. Bob Su
, Feilong Ling
, Lina Bai
, Fengyu Wang

^*Corresponding author for this work

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

3 Citations (Scopus)

Abstract

With the arisen spaceborne multi-parameter Synthetic Aperture Radar (SAR) systems, such as Envisat ASAR, TerraSAR-X, ALOS PALSAR, and RADARSAT-2, the interest of crop mapping has been increasing. The present study compares the capabilities of the multi-parameter SAR in discriminating the main crop types by object-based classification in Haian county of Jiangsu province, South China. Two kinds of information, SAR intensity based and SAR statistical properties based are used for Maximum Likelihood Classification (MLC) and Minimum Distance Classification (MDC) respectively. The results show that, the L-band SAR can uniquely identify mulberry from dryland crops, such as maize and vegetable and C-band SAR has some advantages in mapping rice. Specifically, the polarimetric RADARASAT-2 data can identify the rice with accuracy about 75% ∼ 80% which is similar as the result from X-band TerraSAR-X Spotlight data but higher than that from C-band dual-polarization Envisat ASAR data. Nevertheless, both of X- and C-band can hardly separate the mulberry from the other dry-land crops.

Original language	English
Title of host publication	2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010
Place of Publication	Honolulu
Publisher	IEEE
Pages	359-362
Number of pages	4
ISBN (Print)	9781424495658, 9781424495665
DOIs	https://doi.org/10.1109/IGARSS.2010.5651326
Publication status	Published - 1 Dec 2010
Event	30st IEEE International Geoscience And Remote Sensing Symposium, IGARSS 2010 - Honolulu, United States Duration: 25 Jul 2010 → 30 Jul 2010 Conference number: 30

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)

Conference

Conference	30st IEEE International Geoscience And Remote Sensing Symposium, IGARSS 2010
Abbreviated title	IGARSS 2010
Country/Territory	United States
City	Honolulu
Period	25/07/10 → 30/07/10

Keywords

Covariance matrix
Crop classification
Object based method
SAR
Statistical properties

Access to Document

10.1109/IGARSS.2010.5651326

Cite this

Tian, X., Chen, E., Li, Z., Su, Z. B., Ling, F., Bai, L., & Wang, F. (2010). Comparison of crop classification capabilities of spaceborne multi-parameter SAR data. In 2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010 (pp. 359-362). Article 5651326 (International Geoscience and Remote Sensing Symposium (IGARSS)). IEEE. https://doi.org/10.1109/IGARSS.2010.5651326

@inproceedings{6d1bb4c083a442778a44369e5e15a617,

title = "Comparison of crop classification capabilities of spaceborne multi-parameter SAR data",

abstract = "With the arisen spaceborne multi-parameter Synthetic Aperture Radar (SAR) systems, such as Envisat ASAR, TerraSAR-X, ALOS PALSAR, and RADARSAT-2, the interest of crop mapping has been increasing. The present study compares the capabilities of the multi-parameter SAR in discriminating the main crop types by object-based classification in Haian county of Jiangsu province, South China. Two kinds of information, SAR intensity based and SAR statistical properties based are used for Maximum Likelihood Classification (MLC) and Minimum Distance Classification (MDC) respectively. The results show that, the L-band SAR can uniquely identify mulberry from dryland crops, such as maize and vegetable and C-band SAR has some advantages in mapping rice. Specifically, the polarimetric RADARASAT-2 data can identify the rice with accuracy about 75\% ∼ 80\% which is similar as the result from X-band TerraSAR-X Spotlight data but higher than that from C-band dual-polarization Envisat ASAR data. Nevertheless, both of X- and C-band can hardly separate the mulberry from the other dry-land crops.",

keywords = "Covariance matrix, Crop classification, Object based method, SAR, Statistical properties",

author = "Xin Tian and Erxue Chen and Zengyuan Li and Su, \{Z. Bob\} and Feilong Ling and Lina Bai and Fengyu Wang",

year = "2010",

month = dec,

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doi = "10.1109/IGARSS.2010.5651326",

language = "English",

isbn = "9781424495658",

series = "International Geoscience and Remote Sensing Symposium (IGARSS)",

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booktitle = "2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010",

address = "United States",

note = "30st IEEE International Geoscience And Remote Sensing Symposium, IGARSS 2010, IGARSS 2010 ; Conference date: 25-07-2010 Through 30-07-2010",

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Tian, X, Chen, E, Li, Z, Su, ZB, Ling, F, Bai, L & Wang, F 2010, Comparison of crop classification capabilities of spaceborne multi-parameter SAR data. in 2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010., 5651326, International Geoscience and Remote Sensing Symposium (IGARSS), IEEE, Honolulu, pp. 359-362, 30st IEEE International Geoscience And Remote Sensing Symposium, IGARSS 2010, Honolulu, Hawaii, United States, 25/07/10. https://doi.org/10.1109/IGARSS.2010.5651326

Comparison of crop classification capabilities of spaceborne multi-parameter SAR data. / Tian, Xin; Chen, Erxue; Li, Zengyuan et al.
2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010. Honolulu: IEEE, 2010. p. 359-362 5651326 (International Geoscience and Remote Sensing Symposium (IGARSS)).

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

TY - GEN

T1 - Comparison of crop classification capabilities of spaceborne multi-parameter SAR data

AU - Tian, Xin

AU - Chen, Erxue

AU - Li, Zengyuan

AU - Su, Z. Bob

AU - Ling, Feilong

AU - Bai, Lina

AU - Wang, Fengyu

N1 - Conference code: 30

PY - 2010/12/1

Y1 - 2010/12/1

N2 - With the arisen spaceborne multi-parameter Synthetic Aperture Radar (SAR) systems, such as Envisat ASAR, TerraSAR-X, ALOS PALSAR, and RADARSAT-2, the interest of crop mapping has been increasing. The present study compares the capabilities of the multi-parameter SAR in discriminating the main crop types by object-based classification in Haian county of Jiangsu province, South China. Two kinds of information, SAR intensity based and SAR statistical properties based are used for Maximum Likelihood Classification (MLC) and Minimum Distance Classification (MDC) respectively. The results show that, the L-band SAR can uniquely identify mulberry from dryland crops, such as maize and vegetable and C-band SAR has some advantages in mapping rice. Specifically, the polarimetric RADARASAT-2 data can identify the rice with accuracy about 75% ∼ 80% which is similar as the result from X-band TerraSAR-X Spotlight data but higher than that from C-band dual-polarization Envisat ASAR data. Nevertheless, both of X- and C-band can hardly separate the mulberry from the other dry-land crops.

AB - With the arisen spaceborne multi-parameter Synthetic Aperture Radar (SAR) systems, such as Envisat ASAR, TerraSAR-X, ALOS PALSAR, and RADARSAT-2, the interest of crop mapping has been increasing. The present study compares the capabilities of the multi-parameter SAR in discriminating the main crop types by object-based classification in Haian county of Jiangsu province, South China. Two kinds of information, SAR intensity based and SAR statistical properties based are used for Maximum Likelihood Classification (MLC) and Minimum Distance Classification (MDC) respectively. The results show that, the L-band SAR can uniquely identify mulberry from dryland crops, such as maize and vegetable and C-band SAR has some advantages in mapping rice. Specifically, the polarimetric RADARASAT-2 data can identify the rice with accuracy about 75% ∼ 80% which is similar as the result from X-band TerraSAR-X Spotlight data but higher than that from C-band dual-polarization Envisat ASAR data. Nevertheless, both of X- and C-band can hardly separate the mulberry from the other dry-land crops.

KW - Covariance matrix

KW - Crop classification

KW - Object based method

KW - SAR

KW - Statistical properties

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U2 - 10.1109/IGARSS.2010.5651326

DO - 10.1109/IGARSS.2010.5651326

M3 - Conference contribution

AN - SCOPUS:78650860641

SN - 9781424495658

SN - 9781424495665

T3 - International Geoscience and Remote Sensing Symposium (IGARSS)

SP - 359

EP - 362

BT - 2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010

PB - IEEE

CY - Honolulu

T2 - 30st IEEE International Geoscience And Remote Sensing Symposium, IGARSS 2010

Y2 - 25 July 2010 through 30 July 2010

ER -

Comparison of crop classification capabilities of spaceborne multi-parameter SAR data

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