基于粒子群一最小二乘法的glas波形分解及树高反演方法
An Approach to Decompose ICESat/GLAS Data Waveform and Estimate Canopy Height Based on PSOLSM Method
查看参考文献31篇
|
文摘
|
树高是陆地碳循环研究中的一个重要的生物物理参数。ICESat/GLAS系统是第一个实现全球连续观测的星载激光雷达系统,由于其具有光斑覆盖面积大、穿透力强的特征,在树高等森林结构参数反演方面具有显著的优势。该文设计了一种基于粒子群一最小二乘法的GLAS波形分解及树高反演方法,采用该方法对贡嘎山地区和茂县山区坡度小于10°的GLAS激光点波形进行了高斯分解和树高反演工作,拟合波形与原始波形吻合良好;树高估算结果与采用统计模型估算的树高非常接近(贡嘎山:R~2=0. 80,RMSE=5. 30 m;茂县:R~2=0. 96,RMSE= 3. 11 m)。研究结果表明该方法能很好应用于GLAS波形分解,并获得较好的树高反演结果。未来可以针对该方法在不同坡度地区的适用性和树高反演精度问题开展进一步的研究。 |
|
其他语种文摘
|
Canopy height is an important biophysical parameter for terrestrial carbon cycle study. The Geoscience Laser Altimeter System (GLAS) onboard NASA's Ice,Cloud and land Elevation Satellite (ICESat) provides a new potential for estimating forest canopy height worldwide. Analysis of the returned waveform over area of low topography allows for the direct retrieval of canopy heights. This study presented a new waveform decomposition method based on particle swarm optimization-least square method (PSO-LSM). This method decomposed the GLAS waveform into a series of Gaussian components. The initial parameters of Gaussian decomposition were obtained using particle swarm optimization algorithm,and then they were optimized using the Levenburg-Marquardt method. The first peak from ground direction, the intensity of which exceeded the tenth of maximum waveform intensity,was identified as ground peak. Eventually, the canopy height was estimated from vertical difference between the signal's start and the ground peak. The newly proposed method was applied to Gongga and Maoxian mountain forest. The results indicated that the sum of Gaussian components could be an accurate representation of the original waveform. And the estimated canopy height matched well with the height calculated by the empirical model established by Hayashi et al. in 2013 (Gongga mountain:R~2=0. 80,RMSE= 5. 30 m,Maoxian: R~2=0. 96,RMSE= 3. 11 m). However,the applicability and accuracy of the approach in areas with different slopes need to be further studied. |
|
来源
|
地理与地理信息科学
,2017,33(3):22-29 【核心库】
|
|
DOI
|
10.3969/j.issn.1672-0504.2017.03.005
|
|
关键词
|
GLAS
;
波形分解
;
粒子群算法
;
最小二乘法
;
树高
|
|
地址
|
中国科学院水利部成都山地灾害与环境研究所, 四川, 成都, 610041
|
|
语种
|
中文 |
|
文献类型
|
研究性论文 |
|
ISSN
|
1672-0504 |
|
学科
|
测绘学;林业 |
|
基金
|
国家自然科学基金项目
;
中国科学院国际合作局对外合作重点项目
;
中国科学院委托研究与专项咨询服务课题
|
|
文献收藏号
|
CSCD:6000627
|
参考文献 共
31
共2页
|
|
1.
Patenaude G. Quantifying forest above ground carbon content using LiDAR remote sensing.
Remote Sensing of Environment,2004,93(3):368-380
|
被引
7
次
|
|
|
|
|
2.
杨婷. 基于星载激光雷达GLAS和光学MODIS数据中国森林冠层高度制图.
中国科学(地球科学),2014(11):2487-2498
|
被引
9
次
|
|
|
|
|
3.
Nelson R. Modeling forest canopy heights:The effects of canopy shape.
Remote Sensing of Environment,1997,60(3):327-334
|
被引
3
次
|
|
|
|
|
4.
Lefsky M A. Estimates of forest canopy height and aboveground biomass using ICESat.
Geophysical Research Letters,2005,32(22):971-974
|
被引
56
次
|
|
|
|
|
5.
Lefsky M A. Revised method for forest canopy height estimation from Geoscience Laser Altimeter System waveforms.
Journal of Applied Remote Sensing,2007,1(1)
|
被引
1
次
|
|
|
|
|
6.
Sun G. Forest vertical structure from GLAS:An evaluation using LVIS and SRTM data.
Remote Sensing of Environment,2008,112(1):107-117
|
被引
42
次
|
|
|
|
|
7.
Chen Q. Assessment of terrain elevation derived from satellite laser altimetry over mountainous forest areas using airborne lidar data.
ISPRS Journal of Photogrammetry and Remote Sensing,2010,65(1):111-122
|
被引
3
次
|
|
|
|
|
8.
Popescu S C. Satellite lidar vs. small footprint airborne lidar:Comparing the accuracy of aboveground biomass estimates and forest structure metrics at footprint level.
Remote Sensing of Environment,2011,115(11):2786-2797
|
被引
10
次
|
|
|
|
|
9.
Rosette J A B. Vegetation height estimates for a mixed temperate forest using satellite laser altimetry.
International Journal of Remote Sensing,2008,29(5):1475-1493
|
被引
10
次
|
|
|
|
|
10.
Chen Q. Retrieving vegetation height of forests and woodlands over mountainous areas in the Pacific Coast region using satellite laser altimetry.
Remote Sensing of Environment,2010,114(7):1610-1627
|
被引
12
次
|
|
|
|
|
11.
Hayashi M. Forest canopy height estimation using ICESat/GLAS data and error factor analysis in Hokkaido,Japan.
ISPRS Journal of Photo-grammetry and Remote Sensing,2013,81:12-18
|
被引
12
次
|
|
|
|
|
12.
Wang X Y. Forest canopy height extraction in rugged areas with ICESat/GLAS data.
Ieee Transactions on Geoscience and Remote Sensing,2014,52(8):4650-4657
|
被引
2
次
|
|
|
|
|
13.
Duong V H. Single and two epoch analysis of ICESat full waveform data over forested areas.
International Journal of Remote Sensing,2008,29(5):1453-1473
|
被引
10
次
|
|
|
|
|
14.
Wang Y Y. A combined GLAS and MODIS estimation of the global distribution of mean forest canopy height.
Remote Sensing of Environment,2016,174:24-43
|
被引
6
次
|
|
|
|
|
15.
Yang T. Forest canopy height mapping over China using GLAS and MODIS data.
Science China-Earth Sciences,2015,58(1):96-105
|
被引
6
次
|
|
|
|
|
16.
Lefsky M A. A global forest canopy height map from the Moderate Resolution Imaging Spectroradiometer and the Geoscience Laser Altimeter System.
Geophysical Research Letters,2010,37(15):78-82
|
被引
28
次
|
|
|
|
|
17.
Dolan K A. Using ICE-Safs Geoscience leaser Altimeter System (GLAS) to assess largescale forest disturbance caused by hurricane Katrina.
Remote Sensing of Environment,2011,115(1):86-96
|
被引
8
次
|
|
|
|
|
18.
Hofton M A. Decomposition of laser altimeter waveforms.
Ieee Transactions on Geoscience and Remote Sensing,2000,38(4):1989-1996
|
被引
64
次
|
|
|
|
|
19.
Brenner A C.
Derivation of range and range distributions from laser pulse waveform analysis for surface elevations, roughness, slope, and vegetation heights,2003
|
被引
2
次
|
|
|
|
|
20.
吴红波. 坡度和粗糙度对ICESat-GLAS回波特征及其光斑脚点高程误差的影响研究.
地理与地理信息科学,2016,32(4):30-37
|
被引
4
次
|
|
|
|
|
了解气象卫星更多信息，请访问