Landcover change detection at tonle Sap, Cambodia, using ALOS PALSAR

Nguyen Van Trung, Jung Hyun Choi, Joong Sun Won

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Water level of the Tonle Sap is greatly influenced by the Mekong River. In order to detect landcover change in Tonle Sap floodplain, fifteen ALOS-PALSAR L-band data were acquired and examined from January 2007 to January 2009. Four methods applied to investigate the landcover change around the lake including grey difference images, correlation coefficient, texture feature difference images and multi-color composite images. Change maps of landcover (44 days interval) extracted from the difference images, coherence maps and texture feature difference images were formed. Two RGB images are also obtained by compositing three images acquired in early rainy season, in the middle of rainy season and at the end of the rainy season in 2007 and 2008. The results indicate that the change maps represent the relationship between vegetation and water level, leaf fall forest, cultivation and harvest crop.

Original languageEnglish
Title of host publication30th Asian Conference on Remote Sensing 2009, ACRS 2009
Pages929-934
Number of pages6
Volume2
Publication statusPublished - 2009 Dec 1
Event30th Asian Conference on Remote Sensing 2009, ACRS 2009 - Beijing, China
Duration: 2009 Oct 182009 Oct 23

Other

Other30th Asian Conference on Remote Sensing 2009, ACRS 2009
CountryChina
CityBeijing
Period09/10/1809/10/23

Fingerprint

Water levels
Textures
Crops
Lakes
Rivers
Color
Composite materials

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

Cite this

Van Trung, N., Choi, J. H., & Won, J. S. (2009). Landcover change detection at tonle Sap, Cambodia, using ALOS PALSAR. In 30th Asian Conference on Remote Sensing 2009, ACRS 2009 (Vol. 2, pp. 929-934)
Van Trung, Nguyen ; Choi, Jung Hyun ; Won, Joong Sun. / Landcover change detection at tonle Sap, Cambodia, using ALOS PALSAR. 30th Asian Conference on Remote Sensing 2009, ACRS 2009. Vol. 2 2009. pp. 929-934
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abstract = "Water level of the Tonle Sap is greatly influenced by the Mekong River. In order to detect landcover change in Tonle Sap floodplain, fifteen ALOS-PALSAR L-band data were acquired and examined from January 2007 to January 2009. Four methods applied to investigate the landcover change around the lake including grey difference images, correlation coefficient, texture feature difference images and multi-color composite images. Change maps of landcover (44 days interval) extracted from the difference images, coherence maps and texture feature difference images were formed. Two RGB images are also obtained by compositing three images acquired in early rainy season, in the middle of rainy season and at the end of the rainy season in 2007 and 2008. The results indicate that the change maps represent the relationship between vegetation and water level, leaf fall forest, cultivation and harvest crop.",
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Van Trung, N, Choi, JH & Won, JS 2009, Landcover change detection at tonle Sap, Cambodia, using ALOS PALSAR. in 30th Asian Conference on Remote Sensing 2009, ACRS 2009. vol. 2, pp. 929-934, 30th Asian Conference on Remote Sensing 2009, ACRS 2009, Beijing, China, 09/10/18.

Landcover change detection at tonle Sap, Cambodia, using ALOS PALSAR. / Van Trung, Nguyen; Choi, Jung Hyun; Won, Joong Sun.

30th Asian Conference on Remote Sensing 2009, ACRS 2009. Vol. 2 2009. p. 929-934.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - Water level of the Tonle Sap is greatly influenced by the Mekong River. In order to detect landcover change in Tonle Sap floodplain, fifteen ALOS-PALSAR L-band data were acquired and examined from January 2007 to January 2009. Four methods applied to investigate the landcover change around the lake including grey difference images, correlation coefficient, texture feature difference images and multi-color composite images. Change maps of landcover (44 days interval) extracted from the difference images, coherence maps and texture feature difference images were formed. Two RGB images are also obtained by compositing three images acquired in early rainy season, in the middle of rainy season and at the end of the rainy season in 2007 and 2008. The results indicate that the change maps represent the relationship between vegetation and water level, leaf fall forest, cultivation and harvest crop.

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Van Trung N, Choi JH, Won JS. Landcover change detection at tonle Sap, Cambodia, using ALOS PALSAR. In 30th Asian Conference on Remote Sensing 2009, ACRS 2009. Vol. 2. 2009. p. 929-934