Lidar (light detection and ranging) remote sensing is a breakthrough of active remote sensing technology in recent years. It has shown enormous potential for forest parameters retrieval. Lidar remote sensing has the u...Lidar (light detection and ranging) remote sensing is a breakthrough of active remote sensing technology in recent years. It has shown enormous potential for forest parameters retrieval. Lidar remote sensing has the unique advantage of providing horizontal and vertical information at high accuracies. Especially it can be used to measure forest height directly with unprecedented accuracy. Large footprint lidar has demonstrated its great potential for accurate estimation of many forest parameters. The geoscience laser altimeter system (GLAS) instrument aboard the ice, cloud and land elevation satellite (ICEsat) has acquired a large amount of data including topography and vegetation height information. Although GLAS’ primary mission is the topographic mapping of the ice sheets of greenland and antarctica, it has potential use over land, especially for vegetation height extraction. These data provide an unprecedented vegetation height data set over large area. After a general discussion of GLAS waveform pre_processing, the waveform length extraction method has been developed. Then the waveform length from GLAS Laser 2a data in the northeast China was calculated. The waveform length map was analyzed together with land cover map from Landsat ETM+. The waveform length shows good accordant with land cover types from Landsat ETM+ data. As for forest area, the waveform length map contains much more information about forest height information, which can be used to inverse other forest parameters quantitatively together with other remote sensing data.展开更多
The Amery Ice Shelf is the largest ice shelf in East Antarctica. A new DEM was generated for this ice shelf, using kriging to interpolate the data from ICE- Sat altimetry and the AIS-DEM. The ice thickness distributio...The Amery Ice Shelf is the largest ice shelf in East Antarctica. A new DEM was generated for this ice shelf, using kriging to interpolate the data from ICE- Sat altimetry and the AIS-DEM. The ice thickness distribution map is converted from the new DEM, assuming hydrostatic equilibrium. The Amery Ice Shelf marine ice, up to 230 m thick, is concentrated in the northwest of the ice shelf. The volume of the marine ice is 2.38 × 10^3 km^3 and accounts for about 5.6% of the shelf volume.展开更多
The ecosystem in northeastern China and the Russian Far East is a hotspot of scientific research into the global carbon balance.Forest aboveground biomass(AGB) is an important component in the land surface carbon cycl...The ecosystem in northeastern China and the Russian Far East is a hotspot of scientific research into the global carbon balance.Forest aboveground biomass(AGB) is an important component in the land surface carbon cycle.In this study,using forest inventory data and forest distribution data,the AGB was estimated for forest in Daxinganlin in northeastern China by combining charge-coupled device(CCD) data from the Small Satellite for Disaster and Environment Monitoring and Forecast(HJ-1) and Geoscience Laser Altimeter System(GLAS) waveform data from the Ice,Cloud and land Elevation Satellite(ICESat).The forest AGB prediction models were separately developed for different forest types in the research area at GLAS footprint level from GLAS waveform parameters and field survey plot biomass in the Changqing(CQ) Forest Center,which was calculated from forest inventory data.The resulted statistical regression models have a R2=0.68 for conifer and R2=0.71 for broadleaf forests.These models were used to estimate biomass for all GLAS footprints of forest located in the study area.All GLAS footprint biomass coupled with various spectral reflectivity parameters and vegetation indices derived from HJ-1 satellite CCD data were used in multiple regression analyses to establish biomass prediction models(R2=0.55 and R2=0.52 for needle and broadleaf respectively).Then the models were used to produce a forest AGB map for the whole study area using the HJ-1 data.Biomass data obtained from forest inventory data of the Zhuanglin(ZL) Forest Center were used as independent field measurements to validate the AGB estimated from HJ-1 CCD data(R2=0.71).About 80% of biomass samples had an error less than 20 t ha-1,and the mean error of all validation samples is 5.74 t ha-1.The pixel-level biomass map was then stratified into different biomass levels to illustrate the AGB spatial distribution pattern in this area.It was found that HJ-1 wide-swath data and GLAS waveform data can be combined to estimate forest biomass with good precision,and the b展开更多
航天飞机雷达地形测绘(shuttle radar topography mission,SRTM)和先进星载热发射和反射辐射成像仪全球数字高程模型(advanced spaceborne thermal emission and reflection radiometer global digital elevation model,ASTER GDEM)提...航天飞机雷达地形测绘(shuttle radar topography mission,SRTM)和先进星载热发射和反射辐射成像仪全球数字高程模型(advanced spaceborne thermal emission and reflection radiometer global digital elevation model,ASTER GDEM)提供了全球覆盖面积最广的数字高程模型(digital elevation model,DEM)数据,但其高程精度还未得到充分验证,传统地面测量方法很难适用于验证大面积范围的DEM精度.以冰、云和陆地高程卫星/地学激光测高系统(ICESat/GLAS)高程数据为参考,综合利用地理信息系统(geographic information system,GIS)空间分析、三维可视化与统计分析方法,对中国典型低海拔沿海平原地区和高海拔山地的两种DEM数据高程精度进行了对比分析.结果表明,高程值小于20m的低海拔地区,SRTM高程精度达到2.39m,ASTER GDEM的精度达到4.83m,均远远高于这两种数据的标称精度;而在西南山地,这两种DEM的精度大约为20m,与标称精度相当.最后,建立了ICESat/GLAS与SRTM和ASTER GDEM的一元线性回归模型,该模型具有较高的拟合度和显著线性关系,可用于改善这两种DEM的高程精度.展开更多
激光测高卫星在获取全球高程控制点方面具有独特的优势,本文针对ICESat(Ice,Cloud and land Elevation Satellite)卫星上搭载的地球激光测高系统GLAS(Geo-science Laser Altimetry System),提出了一种多准则约束的高程控制点筛选算法。...激光测高卫星在获取全球高程控制点方面具有独特的优势,本文针对ICESat(Ice,Cloud and land Elevation Satellite)卫星上搭载的地球激光测高系统GLAS(Geo-science Laser Altimetry System),提出了一种多准则约束的高程控制点筛选算法。算法综合利用全球公开版的SRTM(Shuttle Radar Topography Mission)DEM数据对GLAS进行粗差剔除,然后利用GLA14产品中的云量、姿态质量标记、饱和度参数、增益参数等多种与测距有关的属性参数进行粗粒度的筛选,保留受云层、大气、地表反射率等影响较小的激光足印点,最后结合GLA01的波形特征参数做进一步精细筛选,提取出高精度的激光点作为高程控制点。本文还采用天津、河北两个实验区的数据,利用高精度的DEM成果数据对筛选的结果进行了验证。实验结果表明,经多准则约束筛选后的激光足印点具有很高的高程精度,能够作为1∶50000甚至1∶10000立体测图时的高程控制点使用,研究结论可为国产高分辨率卫星在境外地区进行无地面控制点的立体测图提供参考。展开更多
传统激光雷达(light detection and ranging,LiDAR)数据处理均采用固定数的波形分解方法,容易遗漏部分重叠的返回波,降低波形拟合精度。为了实现可变数波形分解,本文提出了一种自动确定波形分解数的方法。假定波形数据服从混合高斯分布...传统激光雷达(light detection and ranging,LiDAR)数据处理均采用固定数的波形分解方法,容易遗漏部分重叠的返回波,降低波形拟合精度。为了实现可变数波形分解,本文提出了一种自动确定波形分解数的方法。假定波形数据服从混合高斯分布,并以此建立理想的波形模型;定义用于控制理想模型与实际波形拟合程度的能量函数,用吉布斯分布构建或然率;根据贝叶斯定理构建刻画波形分解的后验概率模型;设计可逆跳转马尔科夫链蒙特卡洛(reversible jump Markov chain Monte Carlo,RJMCMC)算法模拟该后验概率模型,以确定波形分解数并同时完成波形分解。为了验证提出算法的正确性,分别对不同区域的ICESat-GLAS波形数据进行了波形分解试验,定性和定量分析结果验证了本文方法的有效性、可靠性和准确性。展开更多
文摘Lidar (light detection and ranging) remote sensing is a breakthrough of active remote sensing technology in recent years. It has shown enormous potential for forest parameters retrieval. Lidar remote sensing has the unique advantage of providing horizontal and vertical information at high accuracies. Especially it can be used to measure forest height directly with unprecedented accuracy. Large footprint lidar has demonstrated its great potential for accurate estimation of many forest parameters. The geoscience laser altimeter system (GLAS) instrument aboard the ice, cloud and land elevation satellite (ICEsat) has acquired a large amount of data including topography and vegetation height information. Although GLAS’ primary mission is the topographic mapping of the ice sheets of greenland and antarctica, it has potential use over land, especially for vegetation height extraction. These data provide an unprecedented vegetation height data set over large area. After a general discussion of GLAS waveform pre_processing, the waveform length extraction method has been developed. Then the waveform length from GLAS Laser 2a data in the northeast China was calculated. The waveform length map was analyzed together with land cover map from Landsat ETM+. The waveform length shows good accordant with land cover types from Landsat ETM+ data. As for forest area, the waveform length map contains much more information about forest height information, which can be used to inverse other forest parameters quantitatively together with other remote sensing data.
文摘The Amery Ice Shelf is the largest ice shelf in East Antarctica. A new DEM was generated for this ice shelf, using kriging to interpolate the data from ICE- Sat altimetry and the AIS-DEM. The ice thickness distribution map is converted from the new DEM, assuming hydrostatic equilibrium. The Amery Ice Shelf marine ice, up to 230 m thick, is concentrated in the northwest of the ice shelf. The volume of the marine ice is 2.38 × 10^3 km^3 and accounts for about 5.6% of the shelf volume.
基金supported by National Basic Research Program of China (Grant No.2007CB714404)National Natural Science Foundation of China (Grant Nos.40701124,40930530)
文摘The ecosystem in northeastern China and the Russian Far East is a hotspot of scientific research into the global carbon balance.Forest aboveground biomass(AGB) is an important component in the land surface carbon cycle.In this study,using forest inventory data and forest distribution data,the AGB was estimated for forest in Daxinganlin in northeastern China by combining charge-coupled device(CCD) data from the Small Satellite for Disaster and Environment Monitoring and Forecast(HJ-1) and Geoscience Laser Altimeter System(GLAS) waveform data from the Ice,Cloud and land Elevation Satellite(ICESat).The forest AGB prediction models were separately developed for different forest types in the research area at GLAS footprint level from GLAS waveform parameters and field survey plot biomass in the Changqing(CQ) Forest Center,which was calculated from forest inventory data.The resulted statistical regression models have a R2=0.68 for conifer and R2=0.71 for broadleaf forests.These models were used to estimate biomass for all GLAS footprints of forest located in the study area.All GLAS footprint biomass coupled with various spectral reflectivity parameters and vegetation indices derived from HJ-1 satellite CCD data were used in multiple regression analyses to establish biomass prediction models(R2=0.55 and R2=0.52 for needle and broadleaf respectively).Then the models were used to produce a forest AGB map for the whole study area using the HJ-1 data.Biomass data obtained from forest inventory data of the Zhuanglin(ZL) Forest Center were used as independent field measurements to validate the AGB estimated from HJ-1 CCD data(R2=0.71).About 80% of biomass samples had an error less than 20 t ha-1,and the mean error of all validation samples is 5.74 t ha-1.The pixel-level biomass map was then stratified into different biomass levels to illustrate the AGB spatial distribution pattern in this area.It was found that HJ-1 wide-swath data and GLAS waveform data can be combined to estimate forest biomass with good precision,and the b
文摘传统激光雷达(light detection and ranging,LiDAR)数据处理均采用固定数的波形分解方法,容易遗漏部分重叠的返回波,降低波形拟合精度。为了实现可变数波形分解,本文提出了一种自动确定波形分解数的方法。假定波形数据服从混合高斯分布,并以此建立理想的波形模型;定义用于控制理想模型与实际波形拟合程度的能量函数,用吉布斯分布构建或然率;根据贝叶斯定理构建刻画波形分解的后验概率模型;设计可逆跳转马尔科夫链蒙特卡洛(reversible jump Markov chain Monte Carlo,RJMCMC)算法模拟该后验概率模型,以确定波形分解数并同时完成波形分解。为了验证提出算法的正确性,分别对不同区域的ICESat-GLAS波形数据进行了波形分解试验,定性和定量分析结果验证了本文方法的有效性、可靠性和准确性。
