L-band Polarimetric Interferometry in Boreal Forest Parameter Estimation, a Case Study (original) (raw)
Related papers
Forest Height Estimates for Boreal Forest using L-and X-band POLinSAR and HUTSCAT Scatterometer
In this paper we present a airborne polarimetric interferometric SAR measurement campaign, carried out in Finland in 2003. The main aim of the FinSAR campaign was to validate POLinSAR tree height retrieval algorithms for boreal forest and it was arranged jointly by Helsinki University of Technology (TKK) and German Aerospace Center (DLR) Microwaves and Radar Institute. During the campaign airborne DLR's E-SAR radar (operating at L-and X-band) and TKK's HUTSCAT scatterometer (operating at X-and C-band) were operated over a boreal forest test site to retrieve tree height. The tree height from fully polarimetric L-band SAR data was retrieved by Random Volume over Ground inversion and it was compared with scatterometer measurements and forest stand wise inventory tree height values. Additionally we calculated tree height from X-band single polarisation interferometric images by means of restricted RVoG model inversion and compared the results with other data. Our results show that the tree height values, estimated by means of two different radar instruments, are in good agreement. We also found that single band X-band data allows to calculate the mean tree height with surprisingly good accuracy.
Comparison of Methods to Derive Forest Height from Polarimetric SAR Interferometry
2008
Six forest tree height inversion methods of polarimetric SAR interferometry were validated using repeat pass E-SAR datasets and the corresponding ground measured forest stand height. We show that SINC, three stage full model and three stage SINC inversions have good performance, and the SINC inversion with the first optimum coherence (OPT1) produces the best result among the eleven coherence types validated. Taking SINC inversion as one example, two inversion correction methods were investigated, RMSE can be reduced below 4.0m after correction. The phase and coherence inversion method achieved the second lowest RMSE among the six inversion methods validated, but the estimated tree height of it has very low correlation with ground truth, and this drawback was found caused by the poor performance of RVoG phase inversion method involved.
IEEE Geoscience and Remote Sensing Letters, 2000
In this letter we present results from the FinSAR project, where the E-SAR and HUTSCAT instruments were operated together in order to validate tree height retrieval algorithms for boreal forest. The campaign was carried out in Finland in fall 2003. The main instruments of the campaign were the E-SAR airborne radar (operating at L-and X-band) and the HUTSCAT helicopter-borne profiling scatterometer (operating at X-and C-band). We compare and discuss forest height obtained from the inversion quad-pol POLInSAR data sets at L-band and forest height obtained from the inversion of single-pol Xband inSAR data with forest height estimates from HUTSCAT scatterometer data. Our results show that the forest height values, estimated by means of two different radar instruments, are in good agreement. The correlation between HUTSCAT and ESAR height estimates (R=0.77 at L-and R=0.75 At X-band) underline the good agreement between the results obtained by the two approaches.
2011
World forests contain a significant amount of carbon that is, in consequence of natural and human induced deforestation and regrowth processes, affected by rapid changes and therefore difficult to quantify in terms of biomass/carbon storage. This uncertainty remains because of the lack of reliable and frequent information of biomass levels on a global scale. Spaceborne Synthetic Aperture Radar (SAR) could provide the required global and temporal coverage of the world's forested areas. Innovative new inversion approaches allow today accurate meassurement of vegetation structure parameters such as forest height and biomass [1][2] . The coherent combination of polarimetric and interferometric SAR at lower frequencies by means of Pol-InSAR is sensitive to the vertical distribution of scattering processes within a resolution cell and can be used for model-based inversion of forest height and structural parameters.
Forest biomass estimation using polarimetric SAR interferometry
IEEE International Geoscience and Remote Sensing Symposium, 2002
Forest biomass is one of the most important parameters for global carbon stock modelling yet can only be estimated with great uncertainties. Unfortunately, conventional remote sensing techniques for the estimation of forest biomass are not able to provide estimates on a global scale. An alternative approach is based on forest height estimates from single frequency polarimetric-interferometric SAR data. Here, forest biomass must be converted from forest height through allometric height-biomass relations. Based on the achieved forest height accuracy, this paper shall critically discuss the accuracy of the forest height-biomass relations as derived from standard forestry tables for temperate European forests. The potential of this approach shall be demonstrated by applying the forest height-biomass allometry to convert a forest height-map -acquired from experimental airborne SAR data over the Fichtelgebirge test site (Germany) -into a forest biomass-map.
Estimation and Monitoring of Tropical Forest Biomass Using Polarimetric Interferometric SAR Data
The purpose of the proposed work is to examine the feasibility of using Polarimetric Interferometric SAR (PolInSAR) techniques on ALOS PALSAR data to extract forest canopy heights with the ultimate objective of deriving biomass estimates. Previous work [1] has shown that in homogeneous European forest stands, tree height is a reasonably robust estimator of biomass through a simple allometric relationship. Moreover PolInSAR has proven itself as a valuable technology for tree height estimation at L-Band frequencies. The RVoG model (Random Volume over Ground) proposed in and elaborated in [3], permits a separation of ground and canopy scattering components of the interferometric phase. Through model inversion, the canopy height can be derived . Additionally, the bare earth elevation beneath canopy can also be recovered at least in airborne repeat-pass cases where temporal de-correlation is not prohibitive. While the PolInSAR results to date from airborne repeat-pass L-Band campaigns have been impressive, it is not clear to what extent it will be possible to derive similar results from ALOS data, owing to the much longer temporal baseline between acquisitions.
INDREX-II - Tropical forest height estimation with L and P band polarimetric interferometric SAR
J Texture Stud, 2006
Tropical forests are complex, heterogeneous, dense, remote and changing forest ecosystems. Low frequency synthetic aperture Radar (SAR) techniques allow monitoring and potentially estimation of key forest parameters such as vertical structure (height) and biomass. In the frame of INDREX-II repeat-pass SAR data in quad-pol mode (at L, and P Band) SAR data were acquired and simultaneously ground measurements have been collected. One of the most important -for a wide range of applications -forest parameter is biomass. Biomass appears to be more or less directly related to forest height, which can be estimated from model based inversion of polarimetric and interferometric SAR (Pol-InSAR) data. Indeed, successful height inversion has been demonstrated in several airborne experiments over temperate and boreal forests. In this paper results of model-based L and P Band Pol-InSAR data inversion over tropical forest are shown, including validation against ground measurements.
Boreal forest height estimation with SAR interferometry and laser measurements
2009 IEEE International Geoscience and Remote Sensing Symposium, 2009
In this paper we evaluate X-and L-band SAR coherence tomography in boreal forest with the help of detailed digital terrain and canopy height models, produced by laser scanning. Polarimetric coherence tomography (PCT) needs accurate estimates of ground phase and tree height. Supplemental accurate elevation models allow us to evaluate the performance of PCT in normal case when initial values are derived from RVoG model inversion and provides opportunity to use PCT for nonpolarimetric data. The work is based on E-SAR Lband and X-band measurements in Finland. Our results show that with accurate elevation and tree height information single polarization X-band coherence tomography is feasible and works well. Accurate ground elevation information improves also the performance of fully polarimetric repeat pass L-band PCT. The laser DEM provides better ground phase estimate than RVoG model inversion in the presence of temporal decorrelation. Our results show that accurate ground phase estimation is more critical for successful coherence tomography than other parameters.
IEEE Transactions on Geoscience and Remote Sensing, 2012
Biomass estimation performance using polarimetric interferometric synthetic aperture radar (PolInSAR) data is evaluated at Land P-band frequencies over boreal forest. PolInSAR data are decomposed into ground and volume contributions, retrieving vertical forest structure and polarimetric layer characteristics. The sensitivity of biomass to the obtained parameters is analyzed, and a set of these parameters is used for biomass estimation, evaluating one parametric and two non-parametric methodologies: multiple linear regression, support vector machine, and random forest. The methodology is applied to airborne SAR data over the Krycklan Catchment, a boreal forest test site in northern Sweden. The average forest biomass is 94 tons/ha and goes up to 183 tons/ha at forest stand level (317 tons/ha at plot level). The results indicate that the intensity at HH-VV is more sensitive to biomass than any other polarization at L-band. At P-band, polarimetric scattering mechanism type indicators are the most correlated with biomass. The combination of polarimetric indicators and estimated structure information, which consists of forest height and ground-volume ratio, improved the root mean square error (rmse) of biomass estimation by 17%-25% at L-band and 5%-27% at P-band, depending on the used parameter set. Together with additional ground and volume polarimetric characteristics, the rmse was improved up to 27% at L-band and 43% at P-band. The cross-validated biomass rmse was reduced to 20 tons/ha in the best case. Non-parametric estimation methods did not improve the cross-validated rmse of biomass estimation, but could provide a more realistic distribution of biomass values.
2018
Maintenance of a global forest inventory and regular monitoring of forests is necessary to assess the global carbon stock. Forests have versatile functionality for the mankind and the demands could be fulfilled only by judicious assessment of forest biophysical parameters. Forest height is a parameter essential for quantitative monitoring of forests. Remote sensing tools can efficiently monitor forests on a global scale. Many studies have attempted to use Synthetic Aperture Radar (SAR) remote sensing to estimate forest parameters. This research explores Polarimetric SAR Interferometry (PolInSAR), a technology well suited for forest height estimation. The focus of this work is the retrieval of tree heights in Barkot and Thano forests of India using multi-baseline X-band data while attempting to optimize the estimation performance by simulation of wavenumber. Coherence amplitude inversion and three-stage inversion are performed to estimate the tree heights. Previous studies have used datasets with baseline information suitable for height estimation. This research attempts to use datasets with inapt baseline information and imitates the ideal wavenumber condition. The wavenumber is calculated based on the prior knowledge of the maximum tree height in the region of study. The tree height estimates obtained from both inversions are validated against field data. The accuracy of tree height estimates increase from 24.91% to 88.28% when the ideal wavenumber is used. The minimum calculated RMSE is 1.46m for three-stage inversion and 1.96m for coherence amplitude inversion. The results suggest that using an optimal wavenumber can improve the tree height estimation process.