Advances in the integration of Alos Palsar and Landsat  sensor data for forest characterisation, mapping and monitoring

Richard M. Lucas; John Armston; N. Nugroho; Joao Carreiras; F. de Grandi; Daniel Clewley

Advances in the integration of Alos Palsar and Landsat sensor data for forest characterisation, mapping and monitoring

Richard M. Lucas, John Armston, N. Nugroho, Joao Carreiras, F. de Grandi, Daniel Clewley

Department of Geography and Earth Sciences

Research output: Contribution to conference › Paper

Abstract

Based on case studies undertaken in tropical forests in Brazil and Indonesia and subtropical woodlands in Australia, the paper highlights how data acquired by the Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band Synthetic Aperture Radar (SAR) and Landsat sensors can be integrated to better quantify the extent, biophysical characteristics and/or dynamics of undisturbed, degraded and regenerating forests. The benefits of using time-series of Landsat sensor data to support the interpretation of ALOS PALSAR data and to identify areas with greatest potential for ecosystem recovery are conveyed.

Original language	English
Pages	25-30
Number of pages	6
Publication status	Published - 13 Jun 2011

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http://hdl.handle.net/2160/7050

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Cite this

@conference{296b72db7c0a41b99ad3956338e59f1c,

title = "Advances in the integration of Alos Palsar and Landsat sensor data for forest characterisation, mapping and monitoring",

abstract = "Based on case studies undertaken in tropical forests in Brazil and Indonesia and subtropical woodlands in Australia, the paper highlights how data acquired by the Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band Synthetic Aperture Radar (SAR) and Landsat sensors can be integrated to better quantify the extent, biophysical characteristics and/or dynamics of undisturbed, degraded and regenerating forests. The benefits of using time-series of Landsat sensor data to support the interpretation of ALOS PALSAR data and to identify areas with greatest potential for ecosystem recovery are conveyed.",

author = "Lucas, {Richard M.} and John Armston and N. Nugroho and Joao Carreiras and {de Grandi}, F. and Daniel Clewley",

note = "Lucas, R. M., Armston, J., Carreiras, J., Nugroho, N., Clewley, D., de Grandi, F. (2010). Advances in the integration of Alos Palsar and Landsat sensor data for forest characterisation, mapping and monitoring. 2010 IEEE International Geoscience and Remote Sensing Symposium, Honolulu, 25-30 June 2010, 1851-1854.",

year = "2011",

month = jun,

day = "13",

language = "English",

pages = "25--30",

}

TY - CONF

T1 - Advances in the integration of Alos Palsar and Landsat sensor data for forest characterisation, mapping and monitoring

AU - Lucas, Richard M.

AU - Armston, John

AU - Nugroho, N.

AU - Carreiras, Joao

AU - de Grandi, F.

AU - Clewley, Daniel

N1 - Lucas, R. M., Armston, J., Carreiras, J., Nugroho, N., Clewley, D., de Grandi, F. (2010). Advances in the integration of Alos Palsar and Landsat sensor data for forest characterisation, mapping and monitoring. 2010 IEEE International Geoscience and Remote Sensing Symposium, Honolulu, 25-30 June 2010, 1851-1854.

PY - 2011/6/13

Y1 - 2011/6/13

N2 - Based on case studies undertaken in tropical forests in Brazil and Indonesia and subtropical woodlands in Australia, the paper highlights how data acquired by the Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band Synthetic Aperture Radar (SAR) and Landsat sensors can be integrated to better quantify the extent, biophysical characteristics and/or dynamics of undisturbed, degraded and regenerating forests. The benefits of using time-series of Landsat sensor data to support the interpretation of ALOS PALSAR data and to identify areas with greatest potential for ecosystem recovery are conveyed.

AB - Based on case studies undertaken in tropical forests in Brazil and Indonesia and subtropical woodlands in Australia, the paper highlights how data acquired by the Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band Synthetic Aperture Radar (SAR) and Landsat sensors can be integrated to better quantify the extent, biophysical characteristics and/or dynamics of undisturbed, degraded and regenerating forests. The benefits of using time-series of Landsat sensor data to support the interpretation of ALOS PALSAR data and to identify areas with greatest potential for ecosystem recovery are conveyed.

M3 - Paper

SP - 25

EP - 30

ER -