Relating forest biomass to SAR data

Toan, Thuy Le; Beaudoin, A.; Riom, J.; Guyon, Dominique

doi:10.1109/36.134089

Cited by 700 publications

(323 citation statements)

References 18 publications

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“…The wavelength interaction with canopy elements results in diffuse scattering, hence more energy returning to the sensor [32]. SAR systems with longer wavelengths like L-band sensors penetrate into the canopy [29,33]. Cross-polarized measurements (HV or VH) work better than co-polarized (HH or VV) in correlating σ 0 to AGB since the former accounts for canopy as opposed to ground components.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Aboveground Woody Biomass Dynamics Using Terrestrial Laser Scanner and L-Band ALOS PALSAR Data in South African Savanna

Odipo

Nickless

Berger

et al. 2016

Forests

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Abstract:The use of optical remote sensing data for savanna vegetation structure mapping is hindered by sparse and heterogeneous distribution of vegetation canopy, leading to near-similar spectral signatures among lifeforms. An additional challenge to optical sensors is the high cloud cover and unpredictable weather conditions. Longwave microwave data, with its low sensitivity to clouds addresses some of these problems, but many space borne studies are still limited by low quality structural reference data. Terrestrial laser scanning (TLS) derived canopy cover and height metrics can improve aboveground biomass (AGB) prediction at both plot and landscape level. To date, few studies have explored the strength of TLS for vegetation structural mapping, and particularly few focusing on savannas. In this study, we evaluate the potential of high resolution TLS-derived canopy cover and height metrics to estimate plot-level aboveground biomass, and to extrapolate to a landscape-wide biomass estimation using multi-temporal L-band Synthetic Aperture Radar (SAR) within a 9 km 2 area savanna in Kruger National Park (KNP). We inventoried 42 field plots in the wet season and computed AGB for each plot using site-specific allometry. Canopy cover, canopy height, and their product were regressed with plot-level AGB over the TLS-footprint, while SAR backscatter was used to model dry season biomass for the years 2007, 2008, 2009, and 2010 for the study area. The results from model validation showed a significant linear relationship between TLS-derived predictors with field biomass, p < 0.05 and adjusted R 2 ranging between 0.56 for SAR to 0.93 for the TLS-derived canopy cover and height. Log-transformed AGB yielded lower errors with TLS metrics compared with non-transformed AGB. An assessment of the backscatter based on root mean square error (RMSE) showed better AGB prediction with cross-polarized (RMSE = 6.6 t/ha) as opposed to co-polarized data (RMSE = 6.7 t/ha), attributed to volume scattering of woody vegetation along river valleys and streams. The AGB change analysis showed 32 ha (3.5%) of the 900 ha experienced AGB loses above an average of 5 t/ha per annum, which can mainly be attributed to the falling of trees by mega herbivores such as elephants. The study concludes that SAR data, especially L-band SAR, can be used in the detection of small changes in savanna vegetation over time.

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Section: Introductionmentioning

confidence: 99%

Assessment of Aboveground Woody Biomass Dynamics Using Terrestrial Laser Scanner and L-Band ALOS PALSAR Data in South African Savanna

Odipo

Nickless

Berger

et al. 2016

Forests

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“…A further area of application where SAR data proved to have good potential is biomass retrieval, as reported, for example, in temperate coniferous forests by Le Toan et al (1992) and Beaudoin et al (1994). Unfortunately, the backscattering coefficient saturates at low levels of biomass (L-band: 75-100 tons dm/ha), which is a major drawback in tropical forests showing much higher biomass levels.…”

Section: Forest Monitoringmentioning

confidence: 99%

Management of secondary and logged-over forests in Indonesia: selected proceedings of an international workshop, 17-19 November, 1997

Sist¹,

Sabogal²,

Byron³

1999

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“…Basically, the ability of a SAR system to detect structures of different sizes depends on its frequency (i.e., its wavelength). Lower frequencies (longer wavelength) are sensitive to coarser structures and are thus less likely to saturate in high forest biomass conditions (Dobson et al 1992;Le Toan et al 1992). For instance, a C-band SAR signal is known to saturate rapidly with forest biomass because its wavelength is small (5-6 cm).…”

Section: Radio Detection and Ranging Technologymentioning

confidence: 99%

“…Using longer wavelengths, radar observations are expected to be sensitive to the forest structure and, therefore indirectly, forest biomass and volume (Dobson et al 1992;Le Toan et al 1992). Some studies have shown that Lband (~25 cm) signal (Fig.…”

Section: Radio Detection and Ranging Technologymentioning

confidence: 99%

“…The L-band ALOS PALSAR is currently the single spaceborne radar sensor operating at long wavelengths suited to monitoring forest structure; and its sequel, ALOS2, was launched in 2014. With an even longer wavelength, such as the P-band (~70 cm), radar backscatters may be used for a larger range of forest types (Le Toan et al 1992), including dense tropical forests (Dinh Ho Tong et al 2014). The first Pband satellite, BIOMASS (Le Toan et al 2011), will be launched in 2020.…”

Section: Radio Detection and Ranging Technologymentioning

confidence: 99%

See 1 more Smart Citation

An overview of existing and promising technologies for national forest monitoring

Henry

Réjou‐Méchain

Cifuentes-Jara

et al. 2015

Annals of Forest Science

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Relating forest biomass to SAR data

Cited by 700 publications

References 18 publications

Assessment of Aboveground Woody Biomass Dynamics Using Terrestrial Laser Scanner and L-Band ALOS PALSAR Data in South African Savanna

Assessment of Aboveground Woody Biomass Dynamics Using Terrestrial Laser Scanner and L-Band ALOS PALSAR Data in South African Savanna

Management of secondary and logged-over forests in Indonesia: selected proceedings of an international workshop, 17-19 November, 1997

An overview of existing and promising technologies for national forest monitoring

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