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| 1 | Feature analysis of LIDAR waveforms from forest canopies显示文摘Airborne light detection and ranging (LIDAR) can detect the three-dimensional structure of forest canopies by transmitting laser pulses and receiving returned waveforms which contain backscatter from branches and leaves at different heights.We established a solid scatterer model to explain the widened durations found in analyzing the relationship between laser pulses and forest canopies,and obtained the corresponding rule between laser pulse duration and scatterer depth.Based on returned waveform characteristics,scatterers were classified into three types:simple,solid and complex.We developed single-peak derivative and multiple-peak derivative analysis methods to retrieve waveform features and discriminate between scatterer types.Solid scatterer simulations showed that the returned waveforms were widened as scatterer depth increased,and as space between sub-scatterers increased the returned waveforms developed two peaks which subsequently developed into two separate sub-waveforms.There were slight differences between the durations of simulated and measured waveforms.LIDAR waveform data are able to describe the backscatter characteristics of forest canopies,and have potential to improve the estimation accuracy of forest parameters. | LIU QingWang LI ZengYuan CHEN ErXue PANG Yong LI ShiMing TIAN Xin | 2011 | Science China Earth Sciences2011，54，8： | 6 |
| 2 | Estimation of Crop Biomass Using GF-3 Polarization SAR Data Based on Genetic Algorithm Feature Selection显示文摘In recent years,Polarization SAR(PolSAR)has been widely used in the filed of crop biomass estimation.However,high dimensional features extracted from PolSAR data will lead to information redundancy which will result in low accuracy and poor transfer ability of the estimation model.Aiming at this problem,we proposed a estimation method of crop biomass based on automatic feature selection method using genetic algorithm(GA).Firstly,the backscattering coefficient,the polarization parameters and texture features were extracted from PolSAR data.Then,these features were automatically pre-selected by GA to obtain the optimal feature subset.Finally,based on this subset,a support vector regression machine(SVR)model was applied to estimate crop biomass.The proposed method was validated using the GaoFen-3(GF-3)QPSΙ(C-band,quad-polarization)SAR data.Based on wheat and rape biomass samples acquired from a synchronous field measurement campaign,the proposed method achieve relative high validation accuracy(over 80%)in both crop types.For further analyzing the improvement of proposed method,validation accuracies of biomass estimation models based on several different feature selection methods were compared.Compared with feature selection based on linear correlation,GA method has increased by 5.77%in wheat biomass estimation and 11.84%in rape biomass estimation.Compared with the method of recursive feature elimination(RFE)selection,the proposed method has improved crops biomass estimation accuracy by 3.90%and 5.21%,respectively. | Kunpeng XU Lei ZHAO Kun LI Erxue CHEN Wangfei ZHANG Hao YANG | 2020 | Journal of Geodesy and Geoinformation Science2020，3，4： | 3 |
| 3 | Analysis of forest backscattering characteristics based on polarization coherence tomography显示文摘It is difficult to make an inventory of vertical profiles of forest structure parameters in field measurements.However,analysis and understanding of forest backscattering characteristics contribute to estimation and detection of forest vertical structure because of the close relationships between backscattering characteristics and structure parameters.The vertical structure function in the complex interferometric coherence definition,which represents the vertical variation of microwave scattering with the penetration depth at a point in the 2-D radar image and can be used to analyze the forest backscattering characteristics,can be reconstructed from polarization coherence tomography(PCT).Based on PCT,the paper analyzes the forest backscattering characteristics and explores the inherent relationship between the result of PCT and the forest structure parameters from numerical simulation of Random Volume over Ground model(RVoG),Polarimetric SAR interferometry(PolInSAR)simulation of forest scene and PolInSAR data at L-band of the test site Traunstein.Firstly,the effects of the extinction coefficient and surface-to-volume scattering ratio in RVoG model on vertical backscattering characteristics are analyzed by means of numerical simulation.Secondly,by applying PCT to L-band POLInSAR simulations of forest scene,different variations of vertical backscattering due to different extinction coefficients and the ratios of surface-to-volume scattering resulting from different polarizations,forest types and densities are displayed and analyzed.Then a concept of relative average backscattering intensity is presented,and the factors which affect its vertical distribution are also discussed.Preliminary results show that there is high sensitivity of the vertical distribution of forest relative average backscattering intensity to the polarization,forest type and density.Finally,based on repeat pass DLR E-SAR L-band airborne POLInSAR data,the capability of PCT technology for detection of forest layer,type and density is discussed. | LUO HuanMin 1,LI XiaoWen 1,2,CHEN ErXue 3,CHENG Jian 4 & CAO ChunXiang 21 Institute of Geo-Spatial Information Science and Technology,University of Electronic Science and Technology of China,Chengdu 610054,China 2 State Key Laboratory of Remote Sensing Science,Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University,Beijing 100101,China 3Institute of Forest Resources Information Technique of Chinese Academy of Forestry,Beijing 100091,China 4 School of Electronic Engineering,University of Electronic Science and Technology of China,Chengdu 610054,China | 2010 | Science China(Technological Sciences)2010，53，S1： | 2 |
| 4 | Watershed Allied Telemetry Experimental Research显示文摘 | Li Xin Li Xiaowen Li Zengyuan Ma Mingguo Wang Jian Xiao Qing Liu Qiang Che Tao Chen Erxue Yan Guangjian Hu Zeyong Zhang Lixin Chu Rongzhong Su Peixi Liu Qinhuo Liu Shaomin Wang Jindi Niu Zheng Chen Yan Jin Rui Wang Weizhen Ran Youhua | 2009 | Journal of Geophysical Research Atmospheres2009，，22： | 1 |
| 5 | Fine scale optical remote sensing experiment of mixed stand over complex terrain(FOREST)in the Genhe Reserve Area:objective,observation and a case study显示文摘Optical remote sensing allows to efficiently monitor forest ecosystems at regional and global scales.However,most of the widely used optical forward models and backward estimation methods are only suitable for forest canopies in flat areas.To evaluate the recent progress in forest remote sensing over complex terrain,a satellite-airborne-ground synchronous Fine scale Optical Remote sensing Experiment of mixed Stand over complex Terrain(FOREST)was conducted over a 1 km×1 km key experiment area(KEA)located in the Genhe Reserve Areain 2016.Twenty 30 m×30 m elementary sampling units(ESUs)were established to represent the spatiotemporal variations of the KEA.Structural and spectral parameters were simultaneously measured for each ESU.As a case study,we first built two 3D scenes of the KEA with individual-tree and voxel-based approaches,and then simulated the canopy reflectance using the LargE-Scale remote sensing data and image Simulation framework over heterogeneous 3D scenes(LESS).The correlation coefficient between the LESS-simulated reflectance and the airborne-measured reflectance reaches 0.68-0.73 in the red band and 0.56-0.59 in the near-infrared band,indicating a good quality of the experiment dataset.More validation studies of the related forward models and retrieval methods will be done. | Biao Cao Jianbo Qi Erxue Chen Qing Xiao Qinhuo Liu Zengyuan Li | 2021 | International Journal of Digital Earth2021，14，10： | 1 |
| 6 | Forest above ground biomass estimation using polarization coherence tomography and PolSAR segmenta- tion 显示文摘 | Wenmei Li Erxue Chen Zengyuan Li Yinghai Ke Wen- feng Zhan | 2015 | International Journal of Remote Sensing2015，36，2： | 1 |
| 7 | Forest above ground biomass estimation using polarization co herence tomography and PolSAR segmentation显示文摘 | LI Wenmei CHEN Erxue LI Zengyuan | 2015 | In- ternational Journal of Remote Sensing2015，36，2： | 1 |
| 8 | Wheat lodgingmonitoring using polarimetric index from RADARSAT-2data显示文摘 | Yang Hao Chen Erxue Li Zengyuan | 2015 | International Journal of Applied Earth Observationand Geoinformation2015，34，1： | 1 |
| 9 | Estimation of forest above-ground biomass using multi-parameter remote sensing data over a cold and arid area显示文摘 | Xin Tian Zhongbo Su Erxue Chen Zengyuan Li Christiaan van der Tol Jianping Guo Qisheng He | 2011 | International Journal of Applied Earth Observations and Geoinformation2011，，1： | 1 |
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