Article
Environmental Sciences
Yue Huang, Qiaoping Zhang, Laurent Ferro-Famil
Summary: This paper addresses forest height estimation for boreal forests at the test site of Edson in Alberta, Canada, using dual-baseline PolInSAR dataset measured by Intermap's single-pass system. A tomographic approach, based on polarimetric Capon and MUSIC estimators, is proposed to estimate the elevation of tree top and of underlying ground, and hence forest height is estimated. The resulting forest DTM and DSM over the test site are validated against LiDAR-derived estimates, demonstrating the undeniable capability of the single-pass L-band PolInSAR system for forest monitoring.
Article
Geochemistry & Geophysics
Huiqiang Wang, Haiqiang Fu, Jianjun Zhu, Guangcai Feng, Zefa Yang, Changcheng Wang, Jun Hu, Yanan Yu
Summary: This research addresses the TVBE issue in airborne InSAR data by establishing a multibaseline parameterized model considering HDs and TVBEs, along with proposing a two-step strategy to improve TVBE extraction. Through the calibration of DEM and reestimation of TVBE, the accuracy of DEMs generated by LP is significantly improved, indicating the effectiveness of the proposed model.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2021)
Article
Environmental Sciences
Tayebe Managhebi, Yasser Maghsoudi, Meisam Amani
Summary: A new algorithm for forest height estimation based on dual polarimetric interferometric SAR data is proposed in this study. The efficiency of dual-polarization data compared to full polarimetric images for forest height retrieval is considered. The algorithm uses a three-stage method and an exhaustive search polarization optimization technique to improve the results. Experimental results show the high accuracy of dual PolInSAR data for forest height estimation.
Article
Environmental Sciences
Kunpeng Xu, Lei Zhao, Erxue Chen, Kun Li, Dacheng Liu, Tao Li, Zengyuan Li, Yaxiong Fan
Summary: This article introduces a forest height estimation approach that combines P-band and X-band InSAR. By extracting the digital terrain model (DTM) and digital surface model (DSM) using P-band and X-band InSAR data, respectively, and using improved time-frequency analysis and a novel compensation algorithm, the estimation accuracy is improved. The verification results in the Saihanba Forest Farm in Hebei, China demonstrate the improved accuracy of DTM and DSM extraction, as well as the better estimation accuracy compared to existing methods.
Article
Geochemistry & Geophysics
Yexian Ren, Aoran Xiao, Fengming Hu, Feng Xu, Xiaolan Qiu, Chibiao Ding, Ya-Qiu Jin
Summary: This study proposes a method to enlarge the baseline aperture restricted by conventional uniform sampling arrays using coprime sampling subarrays, and generates virtual observations by estimating cross-correlation matrices. The newly generated virtual measurements offer better imaging results and the potential to improve imaging without increasing hardware cost.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Remote Sensing
Yihao Zhang, Xing Peng, Qinghua Xie, Yanan Du, Bing Zhang, Xiaomin Luo, Shaobo Zhao, Zhentao Hu, Xinwu Li
Summary: This study combines polarimetric SAR variables and single-polarization TomoSAR features to estimate forest height for the first time. The results confirm the advantages of this method in terms of estimation accuracy and computational efficiency.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2023)
Article
Environmental Sciences
Hao Chen, Shane R. Cloude, Joanne C. White
Summary: This paper presents a new method for forest canopy height estimation by fusing TanDEM-X radar interferometric data with GEDI LiDAR waveforms. The study shows that the SINC function is more accurate in areas with shorter canopy heights.
Article
Multidisciplinary Sciences
Josef Kellndorfer, Oliver Cartus, Marco Lavalle, Christophe Magnard, Pietro Milillo, Shadi Oveisgharan, Batu Osmanoglu, Paul A. Rosen, Urs Wegmuller
Summary: This dataset is the first of its kind to provide spatial representation of multi-seasonal C-band Synthetic Aperture Radar (SAR) interferometric repeat-pass coherence and backscatter signatures globally. It contains detailed information on how decorrelation affects interferometric measurements of surface displacement, making it valuable for various mapping applications.
Article
Geochemistry & Geophysics
Andre Barros Cardoso da Silva, Stefan Valentin Baumgartner, Felipe Queiroz de Almeida, Gerhard Krieger
Summary: This article introduces a fast and efficient multichannel calibration algorithm, particularly suited for along-track multichannel systems and STAP techniques. The algorithm can accurately correct phase and magnitude offsets of receive channels, and takes into account the importance of Doppler centroid variation for clutter covariance matrix estimation.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2021)
Article
Chemistry, Multidisciplinary
Hui Sun, Hongguang Jia, Lina Wang, Fang Xu, Jinghong Liu
Summary: By analyzing the kinematic characteristics and error items of the airborne optoelectronic platform, a systematic geo-location error correction method is proposed. Experimental and simulation analysis show that this method effectively reduces geo-location errors and is suitable for error correction in relevant photoelectric equipment.
APPLIED SCIENCES-BASEL
(2021)
Article
Environmental Sciences
Ling Yang, Fubo Zhang, Yihong Sun, Longyong Chen, Zhenhua Li, Dawei Wang
Summary: This paper proposes a motion error estimation and compensation method for an airborne array flexible synthetic aperture radar (SAR) based on a multi-channel interferometric phase. The method establishes a flexible channel motion compensation model based on the multi-channel interference phase of the SAR and obtains accurate rigid baseline length and central incidence angle through a least square method and a global optimal search algorithm. The flexible data are then compensated in the time domain using the motion compensation model and the inversion of the multi-channel interference phase. The actual results demonstrate that the proposed method can obtain accurate flexible compensation data, improving the interference performance of the multi-channel data and laying a solid foundation for high-precision 3D reconstruction of airborne array flexible SAR.
Article
Environmental Sciences
Shadi Sadat Baghermanesh, Shabnam Jabari, Heather McGrath
Summary: Synthetic Aperture Radar (SAR) imagery is a crucial tool for flood mapping, especially in challenging urban environments. This study proposes a machine learning model that combines SAR simulated reflectivity maps, PolInSAR features, and five auxiliary features to improve flood mapping accuracy. The results show a significant improvement of 9.6% in overall classification accuracy using this approach.
Article
Environmental Sciences
Zhiyong Suo, Jingjing Ti, Hongli Xiang, Leru Zhang, Chao Xing, Tingting Wang
Summary: This paper proposes a complete processing chain for digital beamforming synthetic aperture radar (SAR) system that offers wide swath coverage and high signal-to-noise ratio (SNR). The processing chain includes airborne motion compensation method, sub-swaths division process, and relative amplitude and phase errors estimation and compensation method. The effectiveness of the proposed method is verified through simulations and real data.
Article
Remote Sensing
Wenxue Xu, Kai Guo, Yanxiong Liu, Ziwen Tian, Qiuhua Tang, Zhipeng Dong, Jie Li
Summary: This paper presents a method to correct the refraction errors of laser bathymetry data caused by sea surface waves, without complex modeling. The method calculates the seabed laser point coordinates by considering the wave-induced refraction error, showing a significant impact of sea surface waves on underwater topography.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2021)
Article
Environmental Sciences
Wenjie He, Jianjun Zhu, Juan M. Lopez-Sanchez, Cristina Gomez, Haiqiang Fu, Qinghua Xie
Summary: This study evaluates the capacity of TanDEM-X interferometric synthetic aperture radar (InSAR) data assisted by an external digital terrain model (DTM) to estimate forest canopy height. A ground-to-volume ratio estimation model is proposed for precise estimation of canopy height. The results show that the proposed method has high accuracy and performance in forest height estimation, compared with existing methods and LiDAR data.