Mapping specific crop: a multi sensor temporal approach

G. Misra; A. Kumar; N.R. Patel; R. Zurita-Milla; A. Singh

doi:10.1109/IGARSS.2012.6350786

Mapping specific crop: a multi sensor temporal approach

G. Misra
, A. Kumar
, N.R. Patel
, R. Zurita-Milla
, A. Singh

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

10 Citations (Scopus)

63 Downloads (Pure)

Abstract

This study explores the applicability of temporal and multi sensor data for specific crop mapping. For this, temporal data from a single sensor (LISS III from IRS- P6 satellite) was used and classified after selecting the best dates for mapping. In the second case a Landsat- 5 TM image (other sensor/ multi sensor approach) is added to the selected best LISS III temporal dates combination and classified again for evaluating the effect of the addition of a another sensor data (i.e. Landsat- 5 TM) on the overall accuracy of classification. A Possibilistic c-Means (PCM) classification technique has been used for extracting single class of interest (Sugarcane-ratoon) and for including the mixed pixels occurring in the heterogeneous landscape of the study area. In the absence of reference data, evaluation of the soft (fuzzy) classified outputs was done as an entropy measurement, where entropy provides an indirect absolute measurement of the classification accuracy in the form of an uncertainty measure.

Original language	English
Title of host publication	Proceedings of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2012)
Subtitle of host publication	Remote sensing for a dynamic earth, 22-27 July 2012, Munich, Germany
Place of Publication	Piscataway, NJ
Publisher	IEEE
Pages	3034-3037
Number of pages	4
ISBN (Electronic)	978-1-4673-1159-5, 978-1-4673-1158-8
ISBN (Print)	978-1-4673-1160-1
DOIs	https://doi.org/10.1109/IGARSS.2012.6350786
Publication status	Published - 22 Jul 2012
Event	IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012: Remote Sensing for a Dynamic Earth - Munich, Germany Duration: 22 Jul 2012 → 27 Jul 2012 http://www.igarss2012.org/

Conference

Conference	IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012
Abbreviated title	IGARSS
Country/Territory	Germany
City	Munich
Period	22/07/12 → 27/07/12
Internet address	http://www.igarss2012.org/

Keywords

2023 OA procedure

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10.1109/IGARSS.2012.6350786

ArticleFinal published version, 117 KBLicence: Taverne

Cite this

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title = "Mapping specific crop: a multi sensor temporal approach",

abstract = "This study explores the applicability of temporal and multi sensor data for specific crop mapping. For this, temporal data from a single sensor (LISS III from IRS- P6 satellite) was used and classified after selecting the best dates for mapping. In the second case a Landsat- 5 TM image (other sensor/ multi sensor approach) is added to the selected best LISS III temporal dates combination and classified again for evaluating the effect of the addition of a another sensor data (i.e. Landsat- 5 TM) on the overall accuracy of classification. A Possibilistic c-Means (PCM) classification technique has been used for extracting single class of interest (Sugarcane-ratoon) and for including the mixed pixels occurring in the heterogeneous landscape of the study area. In the absence of reference data, evaluation of the soft (fuzzy) classified outputs was done as an entropy measurement, where entropy provides an indirect absolute measurement of the classification accuracy in the form of an uncertainty measure.",

keywords = "2023 OA procedure",

author = "G. Misra and A. Kumar and N.R. Patel and R. Zurita-Milla and A. Singh",

year = "2012",

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doi = "10.1109/IGARSS.2012.6350786",

language = "English",

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

publisher = "IEEE",

address = "United States",

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

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}

Misra, G, Kumar, A, Patel, NR, Zurita-Milla, R & Singh, A 2012, Mapping specific crop: a multi sensor temporal approach. in Proceedings of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2012) : Remote sensing for a dynamic earth, 22-27 July 2012, Munich, Germany. IEEE, Piscataway, NJ, pp. 3034-3037, IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012, Munich, Germany, 22/07/12. https://doi.org/10.1109/IGARSS.2012.6350786

Mapping specific crop: a multi sensor temporal approach. / Misra, G.; Kumar, A.; Patel, N.R. et al.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2012) : Remote sensing for a dynamic earth, 22-27 July 2012, Munich, Germany. Piscataway, NJ: IEEE, 2012. p. 3034-3037.

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

TY - GEN

T1 - Mapping specific crop

T2 - IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012

AU - Misra, G.

AU - Kumar, A.

AU - Patel, N.R.

AU - Zurita-Milla, R.

AU - Singh, A.

PY - 2012/7/22

Y1 - 2012/7/22

N2 - This study explores the applicability of temporal and multi sensor data for specific crop mapping. For this, temporal data from a single sensor (LISS III from IRS- P6 satellite) was used and classified after selecting the best dates for mapping. In the second case a Landsat- 5 TM image (other sensor/ multi sensor approach) is added to the selected best LISS III temporal dates combination and classified again for evaluating the effect of the addition of a another sensor data (i.e. Landsat- 5 TM) on the overall accuracy of classification. A Possibilistic c-Means (PCM) classification technique has been used for extracting single class of interest (Sugarcane-ratoon) and for including the mixed pixels occurring in the heterogeneous landscape of the study area. In the absence of reference data, evaluation of the soft (fuzzy) classified outputs was done as an entropy measurement, where entropy provides an indirect absolute measurement of the classification accuracy in the form of an uncertainty measure.

AB - This study explores the applicability of temporal and multi sensor data for specific crop mapping. For this, temporal data from a single sensor (LISS III from IRS- P6 satellite) was used and classified after selecting the best dates for mapping. In the second case a Landsat- 5 TM image (other sensor/ multi sensor approach) is added to the selected best LISS III temporal dates combination and classified again for evaluating the effect of the addition of a another sensor data (i.e. Landsat- 5 TM) on the overall accuracy of classification. A Possibilistic c-Means (PCM) classification technique has been used for extracting single class of interest (Sugarcane-ratoon) and for including the mixed pixels occurring in the heterogeneous landscape of the study area. In the absence of reference data, evaluation of the soft (fuzzy) classified outputs was done as an entropy measurement, where entropy provides an indirect absolute measurement of the classification accuracy in the form of an uncertainty measure.

KW - 2023 OA procedure

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M3 - Conference contribution

SN - 978-1-4673-1160-1

SP - 3034

EP - 3037

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

PB - IEEE

CY - Piscataway, NJ

Y2 - 22 July 2012 through 27 July 2012

ER -

Mapping specific crop: a multi sensor temporal approach

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