Estimation of Pine Forest Height and Underlying DEM Using Multi-Baseline P-Band PolInSAR Data
نویسندگان
چکیده
On the basis of the Gaussian vertical backscatter (GVB) model, this paper proposes a new method for extracting pine forest height and forest underlying digital elevation model (FUDEM) from multi-baseline (MB) P-band polarimetric-interferometric radar (PolInSAR) data. Considering the linear ground-to-volume relationship, the GVB is linked to the interferometric coherences of different polarizations. Subsequently, an inversion algorithm, weighted complex least squares adjustment (WCLSA), is formulated, including the mathematical model, the stochastic model and the parameter estimation method. The WCLSA method can take full advantage of the redundant observations, adjust the contributions of different observations and avoid null ground-to-volume ratio (GVR) assumption. The simulated experiment demonstrates that the WCLSA method is feasible to estimate the pure ground and volume scattering contributions. Finally, the WCLSA method is applied to E-SAR P-band data acquired over Krycklan Catchment covered with mixed pine forest. It is shown that the FUDEM highly agrees with those derived by LiDAR, with a root mean square error (RMSE) of 3.45 m, improved by 23.0% in comparison to the three-stage method. The difference between the extracted forest height and LiDAR forest height is assessed with a RMSE of 1.45 m, improved by 37.5% and 26.0%, respectively, for model and inversion aspects in comparison to three-stage inversion based on random volume over ground (RVoG) model.
منابع مشابه
Underlying Topography Estimation over Forest Areas Using High-Resolution P-Band Single-Baseline PolInSAR Data
This paper discusses the potential and limitations of high-resolution P-band polarimetric synthetic aperture radar (SAR) interferometry (PolInSAR) in underlying topography estimation over forest areas. Time-frequency (TF) analysis in the azimuth direction is utilized to separate the ground scattering contribution from the total PolInSAR signal, without the use of any physical model, because the...
متن کاملThree-stage inversion improvement for forest height estimation using dual-PolInSAR data
This paper addresses an algorithm for forest height estimation using single frequency single baseline dual polarization radar interferometry data. The proposed method is based on a physical two layer volume over ground model and is represented using polarimetric synthetic aperture radar interferometry (PolInSAR) technique. The presented algorithm provides the opportunity to take advantages of t...
متن کاملA Modified Dual-Baseline PolInSAR Method for Forest Height Estimation
This paper investigates the potentials and limitations of a simple dual-baseline PolInSAR (DBPI) method for forest height inversion. This DBPI method follows the classical three-stage inversion method’s idea used in single baseline PolInSAR (SBPI) inversion, but it avoids the assumption of the smallest ground-to-volume amplitude ratio (GVR) by employing an additional baseline to constrain the i...
متن کاملEstimation 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 re...
متن کاملForest Height Extraction from PolInSAR Image Using a Hybrid Method
Forest height is one of the most important vegetation vertical structure for many forest management activities. It is closely related with forest biomass and absorption of carbon. PolInSAR is a promising remote sensing technique that has been frequently used for extracting forest height. Recently, there have been plenty of research on the retrieval of vegetation parameters by single frequency s...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Remote Sensing
دوره 8 شماره
صفحات -
تاریخ انتشار 2016