Accuracy of Building Height Estimation from SAR Images

2006 ◽  
Author(s):  
G. Franceschetti ◽  
R. Guida ◽  
A. Iodice ◽  
D. Riccio ◽  
G. Ruello
Keyword(s):  
Sar Images ◽  
Height Estimation ◽  
Building Height

Stereo analysis of high-resolution SAR images for building height estimation in cases of orthogonal aspect directions

2009 ◽  
Vol 64 (5) ◽  
pp. 490-500 ◽  
Author(s):  
Uwe Soergel ◽  
Eckart Michaelsen ◽  
Antje Thiele ◽  
Erich Cadario ◽  
Ulrich Thoennessen
Keyword(s):  
High Resolution ◽  
Sar Images ◽  
Height Estimation ◽  
Building Height ◽  
Stereo Analysis

scholarly journals Multi-Scene Building Height Estimation Method Based on Shadow in High Resolution Imagery

2021 ◽  
Vol 13 (15) ◽  
pp. 2862
Author(s):  
Yakun Xie ◽  
Dejun Feng ◽  
Sifan Xiong ◽  
Jun Zhu ◽  
Yangge Liu
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Estimation Method ◽  
Absolute Error ◽  
Large Error ◽  
Estimation Methods ◽  
Height Estimation ◽  
Building Height ◽  
Remote Sensing Imagery ◽  
High Resolution Imagery

Accurately building height estimation from remote sensing imagery is an important and challenging task. However, the existing shadow-based building height estimation methods have large errors due to the complex environment in remote sensing imagery. In this paper, we propose a multi-scene building height estimation method based on shadow in high resolution imagery. First, the shadow of building is classified and described by analyzing the features of building shadow in remote sensing imagery. Second, a variety of shadow-based building height estimation models is established in different scenes. In addition, a method of shadow regularization extraction is proposed, which can solve the problem of mutual adhesion shadows in dense building areas effectively. Finally, we propose a method for shadow length calculation combines with the fish net and the pauta criterion, which means that the large error caused by the complex shape of building shadow can be avoided. Multi-scene areas are selected for experimental analysis to prove the validity of our method. The experiment results show that the accuracy rate is as high as 96% within 2 m of absolute error of our method. In addition, we compared our proposed approach with the existing methods, and the results show that the absolute error of our method are reduced by 1.24 m-3.76 m, which can achieve high-precision estimation of building height.

scholarly journals A HYBRID METHOD IN VEGETATION HEIGHT ESTIMATION USING POLINSAR IMAGES OF CAMPAIGN BIOSAR

2015 ◽  
Vol XL-1-W5 ◽  
pp. 141-146
Author(s):  
S. Dehnavi ◽  
Y. Maghsoudi
Keyword(s):  
Hybrid Method ◽  
Cross Correlation ◽  
Test Site ◽  
Sar Images ◽  
Height Estimation ◽  
Applied Model ◽  
Vegetation Height ◽  
Signal Parameters ◽  
Interferometric Phase ◽  
Two Parameters

Recently, there have been plenty of researches on the retrieval of forest height by PolInSAR data. This paper aims at the evaluation of a hybrid method in vegetation height estimation based on L-band multi-polarized air-borne SAR images. The SAR data used in this paper were collected by the airborne E-SAR system. The objective of this research is firstly to describe each interferometry cross correlation as a sum of contributions corresponding to single bounce, double bounce and volume scattering processes. Then, an ESPIRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) algorithm is implemented, to determine the interferometric phase of each local scatterer (ground and canopy). Secondly, the canopy height is estimated by phase differencing method, according to the RVOG (Random Volume Over Ground) concept. The applied model-based decomposition method is unrivaled, as it is not limited to specific type of vegetation, unlike the previous decomposition techniques. In fact, the usage of generalized probability density function based on the nth power of a cosine-squared function, which is characterized by two parameters, makes this method useful for different vegetation types. Experimental results show the efficiency of the approach for vegetation height estimation in the test site.

Polarimetric Dual-Baseline InSAR Building Height Estimation at L-Band

2009 ◽  
Vol 6 (3) ◽  
pp. 408-412 ◽  
Author(s):  
S. Sauer ◽  
L. Ferro-Famil ◽  
A. Reigber ◽  
E. Pottier
Keyword(s):  
Height Estimation ◽  
Building Height ◽  
L Band
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