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Assessment of ALOS-2 PALSAR-2L-band and Sentinel-1 C-band SAR backscatter for discriminating between large-scale oil palm plantations and smallholdings on tropical peatlands

Assessment of ALOS-2 PALSAR-2L-band and Sentinel-1 C-band SAR backscatter for discriminating between large-scale oil palm plantations and smallholdings on tropical peatlands
Assessment of ALOS-2 PALSAR-2L-band and Sentinel-1 C-band SAR backscatter for discriminating between large-scale oil palm plantations and smallholdings on tropical peatlands

Oil palm agriculture is rapidly expanding across the tropics, particularly on peatlands to meet increasing global demand for palm oil based products. Oil palm production systems can be divided into two broad categories of management system: large-scale monoculture plantations and smallholdings. Both categories are separated by large differences in environmental and social impacts. These oil palm production systems are often characterized by different agricultural practices and vegetation characteristics and therefore land cover. To date, there are no examples of radar remote sensing studies in oil palm production landscapes assessing differences between large-scale plantations and smallholdings. Here, we investigate whether these management systems have distinct radar signatures that can be identified through backscattering intensity using ALOS (Synthetic Aperture Radar) – PALSAR (Phased Array L-band Synthetic Aperture Radar) L-band and Sentinel-1 C-band Synthetic Aperture Radar (SAR). SAR has been shown to be superior to other remote sensing sensors in the tropics for monitoring oil palm expansion due to its all-weather capabilities. In this study we measured backscattered intensity of 196 plots planted with oil palm that were established on peatland in Peninsular Malaysia. Our results indicated that backscattered intensity was significantly influenced by the management systems. We found that canopy and soil moisture was greater in smallholdings compared to large-scale plantations. With the exception of HV polarization method, season had significant effect on backscattered intensity. Irrespective of management systems, canopy and soil moisture was greater in wet months compared to dry months. Our findings suggest that ALOS-2-PALSAR-2L-band and Sentinel-1 C-band have great potential to discriminate oil palm production landscapes managed under different management systems. Further investigation is needed to determine whether the current findings are consistent for oil palm in mineral soils.

Canopy moisture, Management systems, Polarization, Radar, Soil moisture, Vegetation structure
183-190
Oon, Aslinda
c68fe0c7-82f1-43ae-acf1-dc9c1b2ec8e6
Ngo, Khanh Duc
3457cac8-3e14-464a-97e2-be21ba951d19
Azhar, Rozilah
bfd6fbc7-12c4-40e5-bf39-f0863f1b8897
Ashton-Butt, Adham
327a148f-4a26-45f2-9611-6b4378134e04
Lechner, Alex Mark
19c72359-7dc0-435c-817a-f67d4956656f
Azhar, Badrul
1b729d4a-a1a3-4a11-beab-9cf3a9cbaf4c
Oon, Aslinda
c68fe0c7-82f1-43ae-acf1-dc9c1b2ec8e6
Ngo, Khanh Duc
3457cac8-3e14-464a-97e2-be21ba951d19
Azhar, Rozilah
bfd6fbc7-12c4-40e5-bf39-f0863f1b8897
Ashton-Butt, Adham
327a148f-4a26-45f2-9611-6b4378134e04
Lechner, Alex Mark
19c72359-7dc0-435c-817a-f67d4956656f
Azhar, Badrul
1b729d4a-a1a3-4a11-beab-9cf3a9cbaf4c

Oon, Aslinda, Ngo, Khanh Duc, Azhar, Rozilah, Ashton-Butt, Adham, Lechner, Alex Mark and Azhar, Badrul (2019) Assessment of ALOS-2 PALSAR-2L-band and Sentinel-1 C-band SAR backscatter for discriminating between large-scale oil palm plantations and smallholdings on tropical peatlands. Remote Sensing Applications: Society and Environment, 13, 183-190. (doi:10.1016/j.rsase.2018.11.002).

Record type: Article

Abstract

Oil palm agriculture is rapidly expanding across the tropics, particularly on peatlands to meet increasing global demand for palm oil based products. Oil palm production systems can be divided into two broad categories of management system: large-scale monoculture plantations and smallholdings. Both categories are separated by large differences in environmental and social impacts. These oil palm production systems are often characterized by different agricultural practices and vegetation characteristics and therefore land cover. To date, there are no examples of radar remote sensing studies in oil palm production landscapes assessing differences between large-scale plantations and smallholdings. Here, we investigate whether these management systems have distinct radar signatures that can be identified through backscattering intensity using ALOS (Synthetic Aperture Radar) – PALSAR (Phased Array L-band Synthetic Aperture Radar) L-band and Sentinel-1 C-band Synthetic Aperture Radar (SAR). SAR has been shown to be superior to other remote sensing sensors in the tropics for monitoring oil palm expansion due to its all-weather capabilities. In this study we measured backscattered intensity of 196 plots planted with oil palm that were established on peatland in Peninsular Malaysia. Our results indicated that backscattered intensity was significantly influenced by the management systems. We found that canopy and soil moisture was greater in smallholdings compared to large-scale plantations. With the exception of HV polarization method, season had significant effect on backscattered intensity. Irrespective of management systems, canopy and soil moisture was greater in wet months compared to dry months. Our findings suggest that ALOS-2-PALSAR-2L-band and Sentinel-1 C-band have great potential to discriminate oil palm production landscapes managed under different management systems. Further investigation is needed to determine whether the current findings are consistent for oil palm in mineral soils.

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More information

Accepted/In Press date: 4 November 2018
e-pub ahead of print date: 6 November 2018
Published date: 1 January 2019
Keywords: Canopy moisture, Management systems, Polarization, Radar, Soil moisture, Vegetation structure

Identifiers

Local EPrints ID: 428988
URI: http://eprints.soton.ac.uk/id/eprint/428988
PURE UUID: 460624f5-5ff9-4dba-8e64-d2e4eea73ac0

Catalogue record

Date deposited: 15 Mar 2019 17:30
Last modified: 14 Sep 2021 17:49

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