A shadow fraction method for mapping biomass of northern boreal black spruce forests using QuickBird imagery

Leboeuf, Antoine; Beaudoin, A.; Fournier, Richard; Guindon, Luc; Luther, Joan E.; Lambert, Marie-Claude

doi:10.1016/j.rse.2006.05.025

Cited by 91 publications

(61 citation statements)

References 42 publications

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“…Conversely, if biomass does not correlate with forest canopy structure, its relationship with texture measures is stronger than with spectral parameters. This was also noted by Fuchs et al [10] for Siberian tundra forest, by Leboeuf et al [44] for boreal black spruce stands, and by Lu et al [32] for mature moist forest and liana forest stands in the Brazilian Amazon basin. Consequently, in the case of Malagasy lowland rainforest, the relationship between biomass and forest canopy structure is stronger for degraded forest stands than for non-degraded forest stands.…”

Section: Discussionsupporting

confidence: 64%

Improved Forest Biomass and Carbon Estimations Using Texture Measures from WorldView-2 Satellite Data

2012

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Accurate estimation of aboveground biomass and carbon stock has gained importance in the context of the United Nations Framework Convention on Climate Change (UNFCCC) and the Kyoto Protocol. In order to develop improved forest stratum-specific aboveground biomass and carbon estimation models for humid rainforest in northeast Madagascar, this study analyzed texture measures derived from WorldView-2 satellite data. A forest inventory was conducted to develop stratum-specific allometric equations for dry biomass. On this basis, carbon was calculated by applying a conversion factor. After satellite data preprocessing, vegetation indices, principal components, and texture measures were calculated. The strength of their relationships with the stratum-specific plot data was analyzed using Pearson's correlation. Biomass and carbon estimation models were developed by performing stepwise multiple linear regression. Pearson's correlation coefficients revealed that (a) texture measures correlated more with biomass and carbon than spectral parameters, and (b) correlations were stronger for degraded forest than for non-degraded forest. For degraded forest, the texture measures of Correlation, Angular Second Moment, and Contrast, derived from the red band, contributed to the best estimation model, which explained 84% of the variability in the field data (relative RMSE = 6.8%). For non-degraded forest, the vegetation index EVI and the texture measures of Variance, Mean, and Correlation, derived from the newly introduced coastal blue band, both NIR bands, and the red band, contributed to the best model, which explained 81% of the variability in the field data (relative RMSE = 11.8%). These results indicate that estimation of tropical rainforest biomass/carbon, based on very high resolution satellite data, can be improved by (a) developing and applying forest stratum-specific models, and (b) including textural information in addition to spectral information. OPEN ACCESSRemote Sens. 2012, 4 811

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Section: Discussionsupporting

confidence: 64%

Improved Forest Biomass and Carbon Estimations Using Texture Measures from WorldView-2 Satellite Data

2012

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“…We defined this value as TSF WV . The impact of variation in sun angle on TSF WV was assumed to be minimal because the WorldView-1 images were all acquired on the same day at local noon and since Leboeuf et al (2007) showed that normalising TSF based on sun and sensor geometry had a non-discernible impact on the relationship between TSF and field biomass measurements. Variation in snow depth was also assumed to have a negligible effect on TSF WV due to the minimal topographic relief in the area.…”

Section: Aboveground Biomass Mappingmentioning

confidence: 99%

Cajander larch (<i>Larix cajanderi</i>) biomass distribution, fire regime and post-fire recovery in northeastern Siberia

et al. 2012

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Abstract. Climate change and land-use activities are increasing fire activity across much of the Siberian boreal forest, yet the climate feedbacks from forest disturbances remain difficult to quantify due to limited information on forest biomass distribution, disturbance regimes and post-disturbance ecosystem recovery. Our primary objective here was to analyse post-fire accumulation of Cajander larch (Larix cajanderi Mayr.) aboveground biomass for a 100 000 km 2 area of open forest in far northeastern Siberia. In addition to examining effects of fire size and topography on post-fire larch aboveground biomass, we assessed regional fire rotation and density, as well as performance of burned area maps generated from MODIS satellite imagery. Using Landsat imagery, we mapped 116 fire scar perimeters that dated c. 1966-2007. We then mapped larch aboveground biomass by linking field biomass measurements to tree shadows mapped synergistically from WorldView-1 and Landsat 5 satellite imagery. Larch aboveground biomass tended to be low during early succession (≤ 25 yr, 271 ± 26 g m −2 , n = 66 [mean ± SE]) and decreased with increasing elevation and northwardly aspect. Larch aboveground biomass tended to be higher during mid-succession (33-38 yr, 746 ± 100 g m −2 , n = 32), though was highly variable. The high variability was not associated with topography and potentially reflected differences in post-fire density of tree regrowth. Neither fire size nor latitude were significant predictors of post-fire larch aboveground biomass. Fire activity was considerably higher in the Kolyma Mountains (fire rotation = 110 yr, fire density = 1.0 ± 1.0 fires yr −1 × 10 4 km −2 ) than along the forest-tundra border (fire rotation = 792 yr, fire density = 0.3 ± 0.3 fires yr −1 × 10 4 km −2 ). The MODIS burned area maps underestimated the total area burned in this region from 2000-2007 by 40 %. Tree shadows mapped jointly using high and medium resolution satellite imagery were strongly associated (r 2 ≈ 0.9) with field measurements of forest structure, which permitted spatial extrapolation of aboveground biomass to a regional extent. Better understanding of forest biomass distribution, disturbances and postdisturbance recovery is needed to improve predictions of the net climatic feedbacks associated with landscape-scale forest disturbances in northern Eurasia.

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“…Very high resolution satellite and aerial images with pixel size as small as 1.0 m are increasingly utilized for forest parameter estimation. In many studies using such data, however, information is aggregated to the smaller scale, and as with lower resolution sensors, the reliance is on the relative proportion of shade cast by the trees [7,11].…”

Section: Introductionmentioning

confidence: 99%

Combining SPOT 5 imagery with plotwise and standwise forest data to estimate volume and biomass in mountainous coniferous site

Dimitrov

Roumenina

2013

Open Geosciences

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Abstract:In this study, regression-based prediction of volume and aboveground biomass (AGB) of coniferous forests in a mountain test site was conducted. Two datasets -one with applied topographic correction and one without applied topographic correction -consisting of four spectral bands and six vegetation indices were generated from SPOT 5 multispectral image. The relationships between these data and ground data from field plots and national forest inventory polygons were examined. Strongest correlations of volume and AGB were observed with the near infrared band, regardless of the topographic correction. The maximal correlation coefficients when using plotwise data were -0.83 and -0.84 for the volume and AGB, respectively. The maximal correlation with standwise data was -0.63 for both parameters. The SCS+C topographic correction did not significantly affect the correlations between spectral data and forest parameters, but visually removed much of the topographically induced shading.Simple linear regression models resulted in relative RMSE of 32-33% using the plotwise data, and 43-45% using the standwise data. The importance of the source and the methodology used to obtain ground data for the successful modelling was pointed out. Keywords

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A shadow fraction method for mapping biomass of northern boreal black spruce forests using QuickBird imagery

Cited by 91 publications

References 42 publications

Improved Forest Biomass and Carbon Estimations Using Texture Measures from WorldView-2 Satellite Data

Improved Forest Biomass and Carbon Estimations Using Texture Measures from WorldView-2 Satellite Data

Cajander larch (<i>Larix cajanderi</i>) biomass distribution, fire regime and post-fire recovery in northeastern Siberia

Combining SPOT 5 imagery with plotwise and standwise forest data to estimate volume and biomass in mountainous coniferous site

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A shadow fraction method for mapping biomass of northern boreal black spruce forests using QuickBird imagery

Cited by 91 publications

References 42 publications

Improved Forest Biomass and Carbon Estimations Using Texture Measures from WorldView-2 Satellite Data

Improved Forest Biomass and Carbon Estimations Using Texture Measures from WorldView-2 Satellite Data

Cajander larch (&lt;i&gt;Larix cajanderi&lt;/i&gt;) biomass distribution, fire regime and post-fire recovery in northeastern Siberia

Combining SPOT 5 imagery with plotwise and standwise forest data to estimate volume and biomass in mountainous coniferous site

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Cajander larch (<i>Larix cajanderi</i>) biomass distribution, fire regime and post-fire recovery in northeastern Siberia