scholarly journals Improved Three Component Decomposition Technique for Forest Parameters Estimation From PolInSAR Image

2018 ◽  
Author(s):  
Tân Ngọc Nguyễn ◽  
Nghĩa Minh Phạm ◽  
Thủy Ngọc Thủy
Keyword(s):  
Electromagnetic Waves ◽  
Simulated Data ◽  
Test Site ◽  
Parameters Estimation ◽  
Tien Shan ◽  
Sar Interferometry ◽  
Single Frequency ◽  
Decomposition Technique ◽  
Forest Height ◽  
Component Decomposition

Polarimetric SAR interferometry (PolInSAR) is a hot remote sensing technique that allows to extract forest heights by means of model-based inversion. Recently, there have been plenty of research on the retrieval of vegetation parameters by single frequency single baseline PolInSAR such as the ESPRIT method, three-stage inversion. However, these methods have several shortcomings which tend to underestimate the forest height due to attenuations of the electromagnetic waves in the ground medium. In order to overcome these shortcomings, an improved three component decomposition technique using PolInSAR image is proposed in this paper. By means of coherence set and a Newton-Raphson method, the proposed method improve the accuracy of forest height estimation. The proposed algorithm performance is evaluated with simulated data from PolSARProSim software and L-band PolInSAR image pair of Tien-Shan test site is acquired by the SIR-C/X-SAR system.

scholarly journals Four-Stage Inversion Algorithm for Forest Height Estimation Using Repeat Pass Polarimetric SAR Interferometry Data

2018 ◽  
Vol 10 (8) ◽  
pp. 1174 ◽  
Author(s):  
Tayebe Managhebi ◽  
Yasser Maghsoudi ◽  
Mohammad Valadan Zoej
Keyword(s):  
Extinction Coefficient ◽  
European Space Agency ◽  
Sar Interferometry ◽  
Experimental Result ◽  
Single Frequency ◽  
Height Estimation ◽  
Suggested Algorithm ◽  
Forest Height ◽  
Temporal Decorrelation ◽  
The Mean

This paper proposes a new method for forest height estimation using single-baseline single frequency polarimetric synthetic aperture radar interferometry (PolInSAR) data. The new algorithm estimates the forest height based on the random volume over the ground with a volume temporal decorrelation (RVoG+VTD) model. We approach the problem using a four-stage geometrical method without the need for any prior information. In order to decrease the number of unknown parameters in the RVoG+VTD model, the mean extinction coefficient is estimated in an independent procedure. In this respect, the suggested algorithm estimates the mean extinction coefficient as a function of a geometrical index based on the signal penetration in the volume layer. As a result, the proposed four-stage algorithm can be used for forest height estimation using the repeat pass PolInSAR data, affected by temporal decorrelation, without the need for any auxiliary data. The suggested algorithm was applied to the PolInSAR data of the European Space Agency (ESA), BioSAR 2007 campaign. For the performance analysis of the proposed approach, repeat pass experimental SAR (ESAR) L-band data, acquired over the Remningstorp test site in Southern Sweden, is employed. The experimental result shows that the four-stage method estimates the volume height with an average root mean square error (RMSE) of 2.47 m against LiDAR heights. It presents a significant improvement of forest height accuracy, i.e., 5.42 m, compared to the three-stage method result, which ignores the temporal decorrelation effect.

scholarly journals RESEARCH ON INVERSION MODELS FOR FOREST HEIGHT ESTIMATION USING POLARIMETRIC SAR INTERFEROMETRY

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 659-663 ◽  
Author(s):  
L. Zhang ◽  
B. Duan ◽  
B. Zou
Keyword(s):  
Simulated Data ◽  
Research Field ◽  
Sar Interferometry ◽  
Biomass Estimation ◽  
Resource Information ◽  
Advantages And Disadvantages ◽  
Inversion Methods ◽  
Forest Height ◽  
Information Parameter ◽  
Polarimetric Sar Interferometry

The forest height is an important forest resource information parameter and usually used in biomass estimation. Forest height extraction with PolInSAR is a hot research field of imaging SAR remote sensing. SAR interferometry is a well-established SAR technique to estimate the vertical location of the effective scattering center in each resolution cell through the phase difference in images acquired from spatially separated antennas. The manipulation of PolInSAR has applications ranging from climate monitoring to disaster detection especially when used in forest area, is of particular interest because it is quite sensitive to the location and vertical distribution of vegetation structure components. However, some of the existing methods can’t estimate forest height accurately. Here we introduce several available inversion models and compare the precision of some classical inversion approaches using simulated data. By comparing the advantages and disadvantages of these inversion methods, researchers can find better solutions conveniently based on these inversion methods.

Comparative Analysis of Forest Height Retrieval Methods by Polarimetric SAR Interferometry

2013 ◽  
Vol 726-731 ◽  
pp. 4686-4689
Author(s):  
Zhu Bo Zhou ◽  
Hong Zhang Ma ◽  
Xiao Bo Zhu ◽  
Lin Sun
Keyword(s):  
Comparative Analysis ◽  
Difference Method ◽  
Sar Interferometry ◽  
Combined Method ◽  
Polarimetric Sar ◽  
Forest Height ◽  
L Band ◽  
Polarimetric Sar Interferometry ◽  
Combined Methods

The objective of this paper is to compare and analyze the forest height retrieval methods from Polarimetric SAR Interferometry(POLINSAR).Both of the methods based on DEM difference and that on interferometry coherence amplitude are generalized, analyzed, and compared.Also in this paper combined methods of DEM difference and interferometry coherence amplitude are proposed and validated.The ESA fullpolarimetric interferometry L-band data are used for forest height analysis.The results show that the height is severely underestimated using DEM difference method,In constast,interferometry coherence amplitude method has a overest imation of height.The combined method of DEM difference and interferometry coherence amplitude has a much better estimate,closer to the true height than these two methods.

scholarly journals Forest mapping and monitoring with interferometric synthetic aperture radar (InSAR)

2001 ◽  
Vol 25 (2) ◽  
pp. 159-177 ◽  
Author(s):  
H. Balzter
Keyword(s):  
Synthetic Aperture Radar ◽  
Electromagnetic Waves ◽  
Forest Canopy ◽  
Thermal State ◽  
Time Lag ◽  
Sar Interferometry ◽  
Synthetic Aperture ◽  
Dimensional Structure ◽  
Forest Mapping ◽  
Aperture Radar

A synthetic aperture radar (SAR) is an active sensor transmitting pulses of polarized electromagnetic waves and receiving the backscattered radiation. SAR sensors at different wavelengths and with different polarimetric capabilities are being used in remote sensing of the earth. The value of an analysis of backscattered energy alone is limited due to ambiguities in the possible ecological factor configurations causing the signal. From two SAR images taken from similar viewing positions with a short time-lag, interference between the two waves can be observed. By subtracting the two phases of the signals, it is feasible to eliminate the random contribution of the scatterers to the phase. The interferometric correlation and the interferometric phase contain additional information on the three-dimensional structure of the scattering elements in the imaged area. A brief review of SAR sensors is given, followed by an outline of the physical foundations of SAR interferometry and the practical data-processing steps involved. An overview of applications of InSAR to forest mapping and monitoring is given, covering tree-bole volume and biomass, forest types and land cover, fire scars, forest thermal state and forest canopy height.

Monitoring Three Gorge Area Landslide currently movement by Mutilplatform SAR Interferometry

2020 ◽  
Author(s):  
Tao Li ◽  
Yangmao Wen ◽  
Lulu Chen ◽  
Jinge Wang
Keyword(s):  
High Resolution ◽  
Surface Deformation ◽  
Test Site ◽  
Deformation Monitoring ◽  
Sar Interferometry ◽  
Sar Image ◽  
Landslide Area ◽  
Sar Images ◽  
The Past ◽  
Huangtupo Landslide

<p>Three Gorge area landslide hazards developed very fast after the Dam started to impound the water since 2007. There were lots of research literatures concentrated on the Badong Huangtupo Landslide area for the whole city center had to change its position in 2009. Several literatures used Envisat SAR images time series to monitoring the surface deformation from 2008~2010. The results showed good consistent with the water level changes and precipitation.  The high resolution TerraSAR Spotlight images had been used to monitoring the Shuping landslide and Fanjiaping landslide area in Zigui country from 2009~2012,the InSAR results showed good details of the landslide boundary and deformation rate with DInSAR technology.</p><p>This paper studies several landslide area in the Three Gorge by InSAR technology in the past few years, such as Huangtupo, Huanglashi , Daping and  Baiheping landslide area , etc. al . The high resolution SAR images covered Badong and Wushan area have been collected, including the Sentinel-1, TerraSAR, RadarSAT-2, ALOS-2 SAR images. The high resolution topography in those landslide area have been collected both by UAV lidar and high resolution topography map.</p><p>The Huangtupo landslide area changed a lot in the past 3 years with the buildings ruins cleared and red soil covered by the local government. The time series results by Sentinel data in this area shows the big changes but could not derive reasonable deformation results.</p><p>Three Gorges Research Center for Geo-hazards (TGRC) of China University of Geosciences(CUG) built the Badong field test site in Huangtupo landslide area. This test site is composed with a tunnel group and a series of monitoring system including the inside sensors, surface deformation monitoring sensors and so on. In this paper, we mounted several new designed dihedral corner reflectors on the Huangtupo landslide area for high precision deformation monitoring by InSAR. Both the  ascending and the  descending orbit data of RadarSAT-2 high resolution SAR image  and TerraSAR Spotlight images have been collected in this field.</p><p>The preliminary results from those new acquiring SAR data series show that the traditional landslide area such as Huanglashi , Daping, Baiheping are all moving slowly with good coherence in SAR image series.  The poor vegetation coverage in those landslide area helped to get the credible  InSAR results. The high resolution DEM is the critical elements for the DInSAR techniques in those landslide area. The steep  topography in those landslide area distorted the SAR images correspondingly.</p><p>Our results shows that it is possible to use ascending and descending high resolution SAR images to monitor the landslide area with mm level precision, while the vegetation is not so dense. High resolution SAR interferometry helped a lot for the landslide boundary detection and detailed analysis. The lower resolution SAR images such as Sentinel-1 still could provide some deformation results in landslide area, but it need more auxiliary data to interpret the results.</p>

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