Height Of Scattering Phase Center Research Articles

Methods for Processing Information of Radar Topographic Survey for Solving the Tasks for Determining Heights and Wood Stocks For Forest Stands

The paper studies the possibilities of using global elevation models SRTM (Shuttle radar topographic mission) to assess the characteristics of forest stands – average heights and wood stocks. It is known that in process of radar shooting vegetation is considered as a barrier to correctly determining the height of the earth’s surface. The surface, fixed by the sensors above the forest covered territory (scattering phase center height), is located in the upper part of the forest canopy. The review of publications confirms the relevance of this area of investigation in the world. , A brief theoretical basis of the SRTM survey, factors determining the values of the heights and the errors associated with them are presented based on literature reviews. The possibility of determining the height of forest canopy based on evaluation models is shown.
 The part of Uchebno-Opytnoe Forest District of the Leningrad region was chosen as the model territory. The geographic information databases, data of radar survey SRTM and topographic maps were the origin data for the study. The model territory is divided by a regular network into cells with 1 km step. Most of the territory is covered with forest vegetation. Relief modeling was performed on the basis of digitized topographic maps of 1:25000 scale by interpolation using TIN method. A visual and statistical comparison of both evaluation models – a surface model (based on SRTM radar survey data) and a relief model (based on topographic maps) was done. With help of the profiles construction an assessment of the nature of changes in the heights of the relief and surface models was performed. It is noted that for most of the model territory, the differences in height between the surface and relief models are 15-20 m. The convergence of graphs for heights is observed in areas, which are not covered with forest vegetation.
 The set of linear regression dependencies between the scattering phase center heights (independent variable) and average heights or wood stocks (dependent variable) within the borders of forest compartments, grouped by the predominated tree species, was obtained. The influence on the closeness of the relationship and the value of the regression coefficient of such factors as the value of basal area and the share of predominant tree species in composition was found.
 The established regularities can be used to improve the theory and practice of forest inventory, as well as to solve other problems related to the assessment of natural resources at the regional and global level (national forest inventory, carbon stock determination, assessment of biomass).

Simulation of Interferometric SAR Response for Characterizing Forest Successional Dynamics

The dynamics of scattering phase center height (SPCH) in a paper birch stand throughout its succession following clear cutting was studied to improve the interpretation of interferometric synthetic aperture radar (InSAR) response to forest structure changes. A forest growth model (ZELIG) and a fractal tree model (L-system) were utilized together for simulation of the three-dimensional (3-D) structure changes of the stand. Then, a high-fidelity coherent radar scattering model (CORSM) based on 3-D forest structure was employed to simulate the SPCH dynamics of the birch stand. The simulation experiment shows that correlation between L-band SPCH and forest parameters (Lorey's mean height (hL) and biomass) could be noticeably affected by changing pattern of 3-D forest structure at different successional stages, which should be considered in our future exploration of SPCH for forest parameter estimation.

Model-Based Analysis of the Influence of Forest Structures on the Scattering Phase Center at L-Band

The estimation of forest biomass from synthetic aperture radar (SAR) data is limited by the lack of forest structure information. Interferometric synthetic aperture radar (InSAR) provides a means for the extraction of forest structure. The crucial issue in InSAR application is to parameterize forest structure and to link the parameter with InSAR observations. Model-based analysis enables exploring the theoretical linkages between InSAR observations and forest structure free from temporal decorrelation effects. In this paper, a semicoherent model (SCSR) was first developed and verified. A series of simulations at L-band was then made for both homogeneous and heterogeneous forests generated from a forest growth model. The forest structure was parameterized by four height indices. Aside from the height of scattering phase center (HSPC), the depth of scattering phase center (DSPC) was also proposed to characterize the scattering phase center of InSAR. The results showed that the behavior of homogeneous forest on InSAR data was quite different from that of heterogeneous forest. Special care was needed when the retrieval algorithms of forest biomass developed on a homogeneous forest were applied to a heterogeneous forest. Crown size-weighted height (CWH) and Lorey's height were correlated with the HSPC at all polarizations and with the DSPC at copolarization in both cases of homogeneous and heterogeneous forests. These findings indicated that CWH could be an alternative biomass indicator of the Lorey's height for biomass estimation, which can be derived from the combination of InSAR data and the elevation of the forest canopy top from lidar or high-resolution stereo images.

Model-Based Estimation of Forest Canopy Height in Red and Austrian Pine Stands Using Shuttle Radar Topography Mission and Ancillary Data: A Proof-of-Concept Study

In this paper, accurate tree stand height retrieval is demonstrated using C-band Shuttle Radar Topography Mission (SRTM) height and ancillary data. The tree height retrieval algorithm is based on modeling uniform tree stands with a single layer of randomly oriented vegetation particles. For such scattering media, the scattering phase center height, as measured by SRTM, is a function of tree height, incidence angle, and the extinction coefficient of the medium. The extinction coefficient for uniform tree stands is calculated as a function of tree height and density using allometric equations and a fractal tree model. The accuracy of the proposed algorithm is demonstrated using SRTM and TOPSAR data for 15 red pine and Austrian pine stands (TOPSAR is an airborne interferometric synthetic aperture radar). The algorithm yields root-mean-square (rms) errors of 2.5-3.6 m, which is a substantial improvement over the 6.8-8.3-m rms errors from the raw SRTM minus National Elevation Dataset Heights.

Vegetation height estimation from Shuttle Radar Topography Mission and National Elevation Datasets

A study was conducted to determine the feasibility of obtaining estimates of vegetation canopy height from digital elevation data collected during the 2000 Shuttle Radar Topography Mission (SRTM). The SRTM sensor mapped 80% of the Earth's land mass with a C-band Interferometric Synthetic Aperture Radar (InSAR) instrument, producing the most complete digital surface map of Earth. Due to the relatively short wavelength (5.6 cm) of the SRTM instrument, the majority of incoming electromagnetic energy is reflected by scatterers located within the vegetation canopy at heights well above the “bald-Earth” surface. Interferometric SAR theory provides a basis for properly identifying and accounting for the dependence of this scattering phase center height on both instrument and target characteristics, including relative and absolute vertical error and vegetation structural attributes. An investigation to quantify the magnitude of the vertical error component was conducted using SRTM data from two vegetation-free areas in Iowa and North Dakota, revealing absolute errors of −4.0 and −1.1 m, respectively. It was also shown that the relative vertical error due to phase noise can be reduced significantly through sample averaging. The relative error range for the Iowa site was reduced from 13 to 4 m and for the North Dakota site from 7 to 3 m after averaging of 50 samples. Following error reduction, it was demonstrated that the SRTM elevation data can be successfully correlated via linear regression models with ground-measured canopy heights acquired during the general mission timeframe from test sites located in Georgia and California. Prior to outlier removal and phase noise reduction, initial adjusted r 2 values for the Georgia and California sites were 0.15 and 0.20, respectively. Following outlier analysis and averaging of at least 20 SRTM pixels per observation, adjusted r 2 values for the Georgia and California sites improved to 0.79 (rmse=1.1 m) and 0.75 (rmse=4.5 m), respectively. An independent validation of a novel bin-based modeling strategy designed for reducing phase noise in sample plot data confirmed both the robustness of the California model (adjusted r 2=0.74) as well as the capacity of the binning strategy to produce stable models suitable for inversion (validated rmse=4.1 m). The results suggest that a minimum mapping unit of approximately 1.8 ha is appropriate for SRTM-based vegetation canopy height mapping.