Radar remote sensing for monitoring of dynamic ecosystem processes related to biogeochemical exchanges in tropical peatlands View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2004-01

AUTHORS

Shakil Ahmad Romshoo

ABSTRACT

Peatlands are an important multipurpose ecosystem, supporting huge quantities of biomass and peat soil carbon. A time series of Japanese Earth Resource Satellite-1 (JERS-1) L-band Synthetic Aperture Radar (SAR) data was employed to monitor two dynamic ecosystem processes; deforestation and inundation patterns. Using a change detection analysis for three images acquired during dry seasons of 1994, 1997 and 1998, we detected the deforestation that has occurred in the region due to the anthropogenic and natural causes. At a threshold of ±2 dB change in backscattering response, an area of about 98 km2 of these forests was found to have been cleared during 1994–1997 for conversion to cultivatable lands. However, the agricultural crops miserably failed to grow on these cleared lands because of the adverse water and soil chemistry conditions. The deliberate draining of these lands, by laying and extension of a huge network of canals, created congenial ecological conditions for the spread of forest fires, particularly during the 1997 El Niño period. An area of 250 km2 of forests was thus detected to have been destroyed by these fires between September 1997 and January 1998. These deforested lands are rapidly regenerating since their abandonment and the regenerating carbon stocks were simulated using the CENTURY ecosystem dynamics model. Furthermore, the L-band SAR was able to detect the pixel-wise seasonal and spatial inundation information for particular forest types where the transmissivity of the L-band SAR signals was quite significant. These forest types corresponded to comparatively low biomass areas. The SAR derived information about these two important dynamic processes would be useful for improving the accuracy of modelling the spatial and temporal distribution of the carbon and other trace gases in these ecosystems. More... »

PAGES

9-28

Journal

TITLE

Visual Geosciences

ISSUE

1

VOLUME

9

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10069-003-0015-9

DOI

http://dx.doi.org/10.1007/s10069-003-0015-9

DIMENSIONS

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52 schema:description Peatlands are an important multipurpose ecosystem, supporting huge quantities of biomass and peat soil carbon. A time series of Japanese Earth Resource Satellite-1 (JERS-1) L-band Synthetic Aperture Radar (SAR) data was employed to monitor two dynamic ecosystem processes; deforestation and inundation patterns. Using a change detection analysis for three images acquired during dry seasons of 1994, 1997 and 1998, we detected the deforestation that has occurred in the region due to the anthropogenic and natural causes. At a threshold of ±2 dB change in backscattering response, an area of about 98 km2 of these forests was found to have been cleared during 1994–1997 for conversion to cultivatable lands. However, the agricultural crops miserably failed to grow on these cleared lands because of the adverse water and soil chemistry conditions. The deliberate draining of these lands, by laying and extension of a huge network of canals, created congenial ecological conditions for the spread of forest fires, particularly during the 1997 El Niño period. An area of 250 km2 of forests was thus detected to have been destroyed by these fires between September 1997 and January 1998. These deforested lands are rapidly regenerating since their abandonment and the regenerating carbon stocks were simulated using the CENTURY ecosystem dynamics model. Furthermore, the L-band SAR was able to detect the pixel-wise seasonal and spatial inundation information for particular forest types where the transmissivity of the L-band SAR signals was quite significant. These forest types corresponded to comparatively low biomass areas. The SAR derived information about these two important dynamic processes would be useful for improving the accuracy of modelling the spatial and temporal distribution of the carbon and other trace gases in these ecosystems.
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