André Beaudoin

Dependence of radar backscatter on coniferous forest biomass

Two independent experimental efforts have examined the dependence of radar backscatter on above-ground biomass of monospecie conifer forests using polarimetric airborne SAR data at P-, L- and C-bands. Plantations of maritime pines near Landes, France, range in age from 8 to 46 years with above-ground biomass between 5 and 105 tons/ha. Loblolly pine stands established on abandoned agricultural fields near Duke, NC, range in age from 4 to 90 years and extend the range of above-ground biomass to 560 tons/ha for the older stands. These two experimental forests are largely complementary with respect to biomass. Radar backscatter is found to increase approximately linearly with increasing biomass until it saturates at a biomass level that depends on the radar frequency. The biomass saturation level is about 200 tons/ha at P-band and 100 tons/ha at L-band, and the C-band backscattering coefficient shows much less sensitivity to total above-ground biomass. >

A microwave polarimetric scattering model for forest canopies based on vector radiative transfer theory

A microwave polarimetric scattering model for a forest canopy is developed based on the iterative solution of the vector radiative transfer equations up to the second order. The forest canopy constituents (branches, leaves, stems, and trunks) are embedded in a multi-layered medium over a rough interface. The branches, stems, and trunks are modeled as finite randomly oriented cylinders. Deciduous leaves are modeled as randomly oriented discs and coniferous leaves are modeled as randomly oriented needles. The vector radiative transfer equations contain non-diagonal extinction matrices that account for the difference in propagation constants and the attenuation rates between the vertical and horizontal polarizations. For a plane wave exciting the canopy, the average Mueller matrix is formulated, and then used to determine the linearly polarized backscattering coefficients including both the copolarized and cross-polarized power returns. Comparisons of the model with measurements from Les Landes Forest of France showed good agreements over a wide frequency band and gave a quantitative understanding of the relation between the backscattering coefficients and the age of the trees in the forest and forest biomass.

Landuse mapping with ERS SAR interferometry

Two landuse maps and a forest map of three different areas in Europe were completed with ERS SAR interferometry. The test sites represent various geomorphological regions with different cover types. In this article, the mapping algorithms are presented, the results are summarized, and the potential and limitations of ERS SAR interferometry for landuse mapping are discussed. Overall, the results suggest that landuse classification accuracies on the order of 75% are possible with, in the best case, simultaneous forest and nonforest accuracies of around 80-85%. The presence of topography reduces the performance.

ERS INSAR data for remote sensing hilly forested areas

Abstract ERS INSAR data have proved to be of interest for forest applications. The interferometric coherence was found to be related to various land uses and forest types, while in some special cases (e.g., flat terrain) the interferometric phase has been linked to the forest height. This paper reports an investigation on the information content of the interferometric coherence over a hilly terrain supporting various land use types and large pine plantations. The approach includes the use of a Geographic Information System and multitemporal data to analyze the coherence behavior as a function of forest-type forest parameters and environmental factors such as meteorological and topographic effects. Coherence appears to be efficient to discriminate between forest types. However, topography and environmental conditions strongly affect the coherence and its estimation, pointing out the need for rejection of strong slopes areas (>15°) and the sensitivity to local meteorological/seasonal effects. Based on these observations, forest classification results are presented. Forest/nonforest discrimination is very efficient (accuracy >90%) using one-day interval acquisition. More detailed classification with discrimination between forest themes gives also good results. Then, we investigate the indirect link between coherence and forest parameters. The coherence is sensitive to the forest growth stage, making forest parameter retrieval possible using a simple straight-line model. Finally, the importance of wind upon temporal decorrelation is addressed, and a semiempirical correction is proposed.

Estimates of Forest Growing Stock Volume for Sweden, Central Siberia, and Québec Using Envisat Advanced Synthetic Aperture Radar Backscatter Data

A study was undertaken to assess Envisat Advanced Synthetic Aperture Radar (ASAR) ScanSAR data for quantifying forest growing stock volume (GSV) across three boreal regions with varying forest types, composition, and structure (Sweden, Central Siberia, and Quebec). Estimates of GSV were obtained using hyper-temporal observations of the radar backscatter acquired by Envisat ASAR with the BIOMASAR algorithm. In total, 5.3×106 km2 were mapped with a 0.01 degrees pixel size to obtain estimates representative for the year of 2005. Comparing the SAR-based estimates to spatially explicit datasets of GSV, generated from forest field inventory and/or Earth Observation data, revealed similar spatial distributions of GSV. Nonetheless, the weak sensitivity of C-band backscatter to forest structural parameters introduced significant uncertainty to the estimated GSV at full resolution. Further discrepancies were observed in the case of different scales of the ASAR and the reference GSV and in areas of fragmented landscapes. Aggregation to 0.1 degrees and 0.5 degrees was then undertaken to generate coarse scale estimates of GSV. The agreement between ASAR and the reference GSV datasets improved; the relative difference at 0.5 degrees was consistently within a magnitude of 20-30%. The results indicate an improvement of the characterization of forest GSV in the boreal zone with respect to currently available information.

Measurements and modeling of vertical backscatter distribution in forest canopy

Presents the results of analysis and modeling of the airborne ranging Helsinki University of Technology Scatterometer (HUTSCAT) data obtained over an Austrian pine forest in southern France. The objective is to use high vertical resolution backscatter profiles to validate a model that is subsequently used to determine the scattering sources within a canopy and to understand the wave/tree interaction mechanisms. The backscatter coefficients derived from HUTSCAT measurements at X-band at near-normal incidence and polarizations HH, VV, and VH are analyzed. The tree crown backscatter separated from the ground backscattering shows a sensitivity of about 3 dB between 0 and 200 m/sup 3//ha. The estimation of tree height using HUTSCAT profiles gives very good results, with a mean precision of 1 m. The vertical backscatter profiles are compared with the output from the MIT/CESBIO radiative transfer (RT) model coupled with a tree growth architectural model, AMAP, which recreates tree architecture using botanical bases. An a posteriori modification to the RT model is introduced, taking into account the vertical and horizontal variability of the scattering area in order to correctly estimate the backscatter attenuation. The results show good agreement between both simulated and HUTSCAT-derived vertical backscatter distribution within the canopy. The penetration depth at near normal incidence is studied. Both simulated and experimental penetration depth are compared and appear to be of several meters, varying with the stands age.

Climate change impacts on forest landscapes along the Canadian southern boreal forest transition zone

ContextForest landscapes at the southern boreal forest transition zone are likely to undergo great alterations due to projected changes in regional climate.ObjectivesWe projected changes in forest landscapes resulting from four climate scenarios (baseline, RCP 2.6, RCP 4.5 and RCP 8.5), by simulating changes in tree growth and disturbances at the southern edge of Canada’s boreal zone.MethodsProjections were performed for four regions located on an east–west gradient using a forest landscape model (LANDIS-II) parameterized using a forest patch model (PICUS).ResultsClimate-induced changes in the competitiveness of dominant tree species due to changes in potential growth, and substantial intensification of the fire regime, appear likely to combine in driving major changes in boreal forest landscapes. Resulting cumulative impacts on forest ecosystems would be manifold but key changes would include (i) a strong decrease in the biomass of the dominant boreal species, especially mid- to late-successional conifers; (ii) increases in abundance of some temperate species able to colonize disturbed areas in a warmer climate; (iii) increases in the proportions of pioneer and fire-adapted species in these landscapes and (iv) an overall decrease in productivity and total biomass. The greatest changes would occur under the RCP 8.5 radiative forcing scenario, but some impacts can be expected even with RCP 2.6.ConclusionsWestern boreal forests, i.e., those bordering the prairies, are the most vulnerable because of a lack of species adapted to warmer climates and major increases in areas burned. Conservation and forest management planning within the southern boreal transition zone should consider both disturbance- and climate-induced changes in forest communities.

A strategy for mapping Canada's Forest biomass with Landsat TM imagery

Estimates of forest biomass are needed to meet Canadas international reporting requirements and to provide important inputs for global change, carbon accounting, and forest productivity models. The Canadian Forest Service, in cooperation with the Canadian Space Agency, has developed a strategy for mapping Canadas forest biomass as part of the Earth Observation for Sustainable Development of Forests (EOSD) Project. The strategy includes: (i) development of a biomass mapping method, (ii) regional expansion of the method, and (iii) national implementation. The method estimates forest biomass at the forest management stand level using forest cover type and structure information extracted from Landsat Thematic Mapper (TM) data. Regional expansion of the method has occurred over several pilot regions that represent a range of forest ecosystems across Canada. Validation of regional products provides an indication of the precision of the method, defines the data requirements and limits to regional expansion, and has led to the development of research themes. Specific research themes address known limitations of the method by (i) improving the extraction of cover type and structure information from satellite imagery, (ii) defining the role of environmental variables and other factors for biomass estimation, and (iii) separating understorey and overstorey biomass.

Monitoring the state of a large boreal forest region in eastern Canada through the use of multitemporal classified satellite imagery

Multitemporal classification of Landsat imagery was used to measure and monitor the state of the forest over a large area (11.6 million ha) of boreal forest in eastern Canada using four criteria for a 20 year period (1985–2005). The Enhancement-Classification Method was used in this study. Forty-eight thematic classes based on Canadas National Forest Inventory were identified, then grouped into 13 indicators, and reorganized within four main criteria: (i) forest versus nonforest land cover, (ii) forest development stage, (iii) forest cover type, and (iv) forest cover density. Validation based on 2973 high-resolution geo-referenced digital aerial colour photos of the 2005 classified images showed an overall accuracy of the four criteria of 83%, 68%, 58%, and 62%, respectively. The change in each indicator between 1985 and 2005 could be summarized as: (i) a decrease in productive forest area of 0.4% (approx. 43 000 ha); (ii) a 4.6% decrease in mature stand area, with a concomitant increase in areas classified as vegetated (1.3%) and regenerated (3.4%); (iii) concentration of harvesting pressure on coniferous and mixed stands with respective reductions of 8.2% and 0.8%, due to their conversion to deciduous stands; and (iv) an increase in low-density stands (3.1%) and a decrease in high-density stands (8.3%). These results demonstrate that medium-resolution (30 m) remote sensing tools can be used both to monitor the state of the boreal forest and to produce key indicators, which were extracted from the multidate Landsat satellite imagery.

Using SIR-C SAR Data and the AMAP Model for Forest Attributes Retrieval and 3-D Stand Simulation

Abstract Space-borne Synthetic Aperture Radar (SAR) data and the plant architectural model AMAP are new tools, currently under development and validation, for the retrieval and mapping of forest parameters through a Geographical Information System (GIS). On one hand, L-band SAR data are useful for the retrieval of some forest attributes such as age and woody volume. On the other hand, validated growth model of tree architecture allows retrieval of many forest parameters at tree level and simulation of virtual 3-D views both at the tree and stand levels. To this aim, a methodology is proposed using L-HV SIR-C SAR data or AMAP alone or their coupling through a GIS for forest attributes retrieval and 3-D stand simulation. This approach is illustrated on a simple forest ecosystem, an Austrian pine forest over hilly terrain in southern of France. Results show the potentialities and interests in using such tools when retrieval bole volume is limited to 300 m 3 /ha; AMAP allowed estimation according to tree (compartment) partitioning as a function of growth stage. The coupling approach gives realistic 3-D stand visualization when it is exercised with GIS data sets and error sources are pointed out toward future improvement and generalization.