Forest height retrieval from commercial X-band SAR products

Izzawati,; Wallington, E.D.; Woodhouse, Iain

doi:10.1109/tgrs.2006.870828

Cited by 52 publications

(54 citation statements)

References 23 publications

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“…Overall, the best results on bare ground have a mean value below 20 cm for TerraSAR-X and 50cm for COSMO-SkyMed with a standard deviation of 2 meters. However, when moving into regions of forest a systematic canopy height underestimation is visible (like predicted from previous studies on InSAR processing over forest [21][22][23][24][25]28]). Tables 6 and 7 reveal that the standard deviation of height error drops a bit in regions of forest, while the mean height errors show systematic bias.…”

Section: Multi-image Dsm Generationsupporting

confidence: 73%

“…The reason for that is the fact, that the SAR signal in X-band penetrates into the forest canopy changing the InSAR phase center and therefore the reconstructed height. This aspect has been observed on InSAR-based processing of airborne X-band data [21][22][23]28], on X-band SRTM satellite data [7], on Radarsat-2 data [25], and on simulations [22,24].…”

Section: Multi-image Dsm Generationmentioning

confidence: 91%

“…One crucial problem using X-band signals is the downward penetration into the forest canopy causing a shift of the InSAR phase center, which causes a systematic underestimation of the forest height ( [21][22][23][24] and indicated in [25]; it should be noted that the cited works do not deal with TerraSAR-X nor COSMO-SkyMed data). The presented solution is based on a relative calibration to reference data and the validation of such surface models is made through comparison with LiDAR data.…”

Section: Introductionmentioning

confidence: 99%

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Forest Assessment Using High Resolution SAR Data in X-Band

et al. 2011

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Novel radar satellite missions also include sensors operating in X-band at very high resolution. The presented study reports methodologies, algorithms and results on forest assessment utilizing such X-band satellite images, namely from TerraSAR-X and COSMO-SkyMed sensors. The proposed procedures cover advanced stereo-radargrammetric and interferometric data processing, as well as image segmentation and image classification. A core methodology is the multi-image matching concept for digital surface modeling based on geometrically constrained matching. Validation of generated surface models is made through comparison with LiDAR data, resulting in a standard deviation height error of less than 2 meters over forest. Image classification of forest regions is then based on X-band backscatter information, a canopy height model and interferometric coherence information yielding a classification accuracy above 90%. Such information is then directly used to extract forest border lines. High resolution X-band sensors deliver imagery that can be used for automatic forest assessment on a large scale.

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Section: Multi-image Dsm Generationsupporting

confidence: 73%

Section: Multi-image Dsm Generationmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

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Forest Assessment Using High Resolution SAR Data in X-Band

et al. 2011

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“…X-HH derived h spc is at or very near bare ground (Mercer, 2001; blue dashed line, Figure 3) in barren areas; whereas in forest canopies the location of h spc depends on the penetration depth of microwaves into the canopy. This depth depends on wavelength, incidence angle, size and density distribution of the scattering elements, geometric arrangement of the scatterers, canopy moisture condition, surface roughness, and moisture content of the ground layer (Andersen et al, 2006;Izzawati et al, 2006;Woodhouse et al, 2006). Vegetation canopy heights given by X-HH InSAR h spc data are typically located in the upper portion of the vegetation canopy.…”

Section: Insar Incidence Angle and Scattering Phase Centre Height Bacmentioning

confidence: 99%

“…digital surface model -DSM) to estimate the scattering phase centre height (h spc ; Kellndorfer et al, 2004;Simard et al, 2006;Andersen et al, 2008) to yield an estimate of vegetation canopy height. While a significant amount of research has been published on the application of InSAR for vegetation parameter extraction-in particular for vegetation canopy heightadditional research is needed to gain further understanding of the effect of incidence angle changes on InSAR derived vegetation canopy height given by h spc and methods must be International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 XXII ISPRS Congress, 25 August -01 September 2012, Melbourne, Australia employed that seek to minimize their influence, (Izzawati et al, 2006;Woodhouse et al, 2006;Balzter et al, 2007a).…”

Section: Introductionmentioning

confidence: 99%

Airborne X-Hh Incidence Angle Impact on Canopy Height Retreival: Implications for Spaceborne X-Hh Tandem-X Global Canopy Height Model

Tighe

King

Balzter

et al. 2012

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Commission VII WG2: SAR InterferometryKEY WORDS: Canopy Height, InSAR, X-band, DTM, DSM, DEM ABSTRACT:To support international climate change mitigation efforts, the United Nations REDD+ initiative (Reducing Emissions from Deforestation and Degradation) seeks to reduce land use induced greenhouse gas emissions to the atmosphere. It requires independent monitoring of forest cover and forest biomass information in a spatially explicit form. It is widely recognised that remote sensing is required to deliver this information. Synthetic Aperture Radar interferometry (InSAR) techniques have gained traction in the last decade as a viable technology from which vegetation canopy height and bare earth elevations can be derived. The viewing geometry of a SAR sensor is side-looking where the radar pulse is transmitted out to one side of the aircraft or satellite, defining an incidence angle (θ) range. The incidence angle will change from near-range (NR) to far-range (FR) across of the track of the SAR platform. InSAR uses image pairs and thus, contain two set of incidence angles. Changes in the InSAR incidence angles can alter the relative contributions from the vegetation canopy and the ground surface and thus, affect the retrieved vegetation canopy height. Incidence angle change is less pronounced in spaceborne data than in airborne data and mitigated somewhat when multiple InSAR-data takes are combined. This study uses NEXTMap ® single-and multi-pass X-band HH polarized InSAR to derive vegetation canopy height from the scattering phase centre height (h spc ). Comparisons with in situ vegetation canopy height over three test sites (Arizona-1, Minnesota-2); the effect of incidence angle changes across swath on the X-HH InSAR h spc was examined. Results indicate at steep incidence angles (θ = 35 º ), more exposure of lower vegetation canopy structure (e.g. tree trunks) led to greater lower canopy double bounce, increased ground scattering, and decreased volume scattering. This resulted in a lower scattering phase centre height (h spc ) or a greater underestimation of vegetation canopy height given by the single-pass X-HH InSAR data. The opposite effect occurs in the far range (θ = 55 º ), an increase in volume scattering resulted in more accurate vegetation canopy heights when compared to in situ measurements. These findings indicate that incidence angle corrections should be applied to airborne X-HH single-pass InSAR. In contrast, NEXTMap X-HH (multi-pass data) h spc data experienced little or no effect of incidence angle, possibly because NEXTMap is an aggregation of multi-pass flight line strips, which averages data over several incidence angles. These results may aid in the understanding of potential incidence angle effects in Astrium spaceborne Tandem-X data, which will have global digital surface elevation coverage by 2015.

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