红外与毫米波学报, 2015, 34 (2): 243, 网络出版: 2015-05-20  

星载激光雷达GLAS与TM光学遥感联合反演森林叶面积指数

Forest leaf area index estimation using combined ICESat/GLAS and optical remote sensing image
作者单位
1 中国科学院遥感与数字地球研究所, 数字地球重点实验室, 北京 100094
2 北京城市学院, 北京 100083
摘要
通过对地球科学激光测高系统(Geoscience Laser Altimeter System, GLAS)波形数据进行高斯分解, 提取精确的波形特征信息, 计算出GLAS波形数据激光穿透指数(LPI), 基于LPI提出GLAS数据反演叶面积指数(LAI)的新方法, 建立了GLAS数据反演森林LAI的模型(R2=0.84, RMSE=0.64), 并用留一交叉验证法(LOOCV)对反演模型的可靠性进行了验证, 结果表明, 该模型没有过度拟合, 具有很好的泛化能力, 最后通过人工神经网络融合GLAS与TM(Thematic Mapper,专题制图仪)遥感数据实现区域尺度森林LAI反演, 用25个实测LAI对反演精度进行了验证, 研究表明反演LAI与实测值较为接近, 精度较高(R2=0.76, RMSE=0.69), 为生态环境研究提供精确的输入参数, 为GLAS数据大区域高精度LAI反演提供新的方法和思路.
Abstract
Based on Gaussian decomposition of the geoscience laser altimeter system(GLAS) waveform, accurate waveform characteristics were extracted, and then laser penetrate index (LPI) was computed for each GLAS waveform. The new method of leaf area index (LAI) estimation using LPI derived from GLAS data was proposed. Forest LAI estimation model based on GLAS data was established(R2=0.84, RMSE=0.64)and the models reliability was assessed using the Leave-One-Out Cross-Validation (LOOCV) method. The result indicates that the regression model is not overfitting the data and has a good generalization capability. Finally, regional scale forest LAI was estimated using combined GLAS and TM optical remotely sensed image by artificial neural network. And then, the accuracy of the predicted LAIs based on neural network was validated using the other 25 field-measured LAIs. The results show that forest LAI estimation are very close to the field-measured LAIs with a high accuracy (R2=0.76, RMSE=0.69). Therefore, the estimated LAIs provide accurate input parameters to the study on ecological environment. The study provides new methods and ideas to estimate LAI with large regional scale using GLAS waveform data.
参考文献

[1] FANG Jing-Yun, ZHU Jiang-Ling, WANG Shao-Peng, et al. Global warming, human-induced carbon emissions, and their uncertainties[J]. Science China Earth Sciences(方精云, 朱江玲, 王少鹏, 等.全球变暖、碳排放及不确定性.中国科学: 地球科学), 2011, 41(10): 1385-1395.

[2] Lowman M D, Rinker h B. Forest canopies. 2nd edition. Elsevier/Academic Press, SanDiego, CA, 2004.

[3] Chen J M, Pavlic G, Brown L, et al. Derivation and validation of canada wide coarse resolution leaf area index maps using high resolution satellite imagery and ground measurements[J]. Remote Sensing of Environment, 2001, 80(1): 165-184.

[4] Chen J M, Cihlar J. Retrieving leaf area index of boreal conifer forests using Landsat TM images[J]. Remote Sensing of Environment, 1996, 55(2): 153-162.

[5] Jonckheere I, Fleck S, Nackaerts K, et al. Review of methods for in situ leaf area index determination Part Ⅰ. Theories, sensors and hemispherical photography[J]. Agricultural and Forest Meteorology, 2004, 121(1-2): 19-35.

[6] ZHANG Jia-Hua, FU Cong-Bin, YAN Xiao-Dong, et al. Global respondence analysis of LAI versus surface air temperature and precipitation variations[J]. Chinese Journal of Geophysics(张佳华, 符淙斌, 延晓冬, 等.全球植被叶面积指数对温度和降水的响应研究.地球物理学报), 2002, 45(5): 631-637.

[7] Wang Q, Adiku S, Tenhunen J, et al. On the relationship of NDVI with leaf area index in a deciduous forest site[J]. Remote Sensing of Environment, 2005, 94(2): 244-255.

[8] LUO She-Zhou, CHENG Feng, WANG Fang-Jian, et al. Leaf area index inversion based on TM in Linzhi, Tibet[J]. Remote Sensing Technology and Application(骆社周, 程峰, 王方建, 等.基于TM遥感数据的西藏林芝地区叶面积指数反演.遥感技术与应用), 2012, 27(5): 740-745.

[9] LIU Liang-Yun, ZHANG Bing, ZHENG Lan-Fen, et al. Target classification and soil water content regression using land surface temperature (LST) and vegetation index (Ⅵ)[J]. Journal of Infrared Millimeter Waves(刘良云, 张兵, 郑兰芬, 等.利用温度和植被指数进行地物分类和土壤水分反演.红外与毫米波学报), 2002, 21(4): 269-273.

[10] Colombo R, Bellingeri D, Fasolini D, et al. Retrieval of leaf area index in different vegetation types using high resolution satellite data[J]. Remote Sensing of Environment, 2003, 86(1): 120-131.

[11] Eriksson H, Eklundh L, Kuusk A, et al. Impact of understory vegetation on forest canopy reflectance and remotely sensed LAI estimates[J]. Remote Sensing of Environment, 2006, 103(4): 408-418.

[12] Hall S A, Burke I C, Box D O, et al. Estimating stand structure using discrete-return LiDAR: an example from low density, fire prone ponderosa pine forests. Forest Ecology and Management[J]. 2005, 208(1-3): 189-209.

[13] Tang H, Dubayah R, Swatantran A, et al. Retrieval of vertical LAI profiles over tropical rain forests using waveform lidar at La Selva, Costa Rica[J]. Remote Sensing of Environment, 2012, 124: 242-250.

[14] LIU Cun, LI Nan, WU Hang-Bin, et al. Adjustment model of boundary extraction for urban complicate building based on LiDAR data[J]. Journal of Tongji University(Natural Science)(刘春, 李楠, 吴杭彬, 等.机载激光扫描中复杂建筑物轮廓线平差提取模型.同济大学学报(自然科学版)), 2012, 40(9): 1399-1405.

[15] MA Hong-Chao, YAO Chun-Jing, ZHANG Sheng-De. Some technical issues of airborne LIDAR system applied to Wenchuan earthquake relief works[J]. Journal of Remote Sensing(马洪超, 姚春静, 张生德.机载激光雷达在汶川地震应急响应中的若干关键问题探讨.遥感学报), 2008, 12(6): 925-932.

[16] LIU Zheng-Jun, QIAN Jian-Guo, ZHANG Zheng-Peng, et al. Experiment on high resolution DTM acquisition by 3D terrestrial laser scanner[J]. Science of surveying and Mpping(刘正军, 钱建国, 张正鹏, 等.三维激光扫描数据获取高分辨率DTM试验研究.测绘科学), 2006, 31(4): 72-74.

[17] Sun G, Ranson K J, Kimes D S, et al. Forest vertical structure from GLAS: An evaluation using LVIS and SRTM data[J]. Remote Sensing of Environment, 2008, 112(1): 107-117.

[18] Korhonen L, Korpela I, Heiskanen J, et al. Airborne discrete-return LiDAR data in the estimation of vertical canopy cover, angular canopy closure and leaf area index[J]. Remote Sensing of Environment, 2011, 115(4): 1065-1080.

[19] Peduzzi A, Wynne R H, Fox T R, et al. Estimating leaf area index in intensively managed pine plantations using airborne laser scanner data[J]. Forest Ecology and Management, 2012, 270: 54-65.

[20] Dupuya S, Lainéa G,Tassinb J, et al. Characterization of the horizontal structure of the tropical forest canopy using object-based LiDAR and multispectral image analysis[J]. International Journal of Applied Earth Observation and Geoinformation, 2013, 25: 76-86.

[21] ZHOU Meng-Wei, LIU Qin-Huo, LIU Qiang, et al. Inversion of leaf area index based on small-footprint waveform airborne LIDAR[J]. Transactions of the CSAE(周梦维, 柳钦火, 刘强, 等.机载激光雷达的作物叶面积指数定量反演.农业工程学报), 2011, 27(4): 207-213.

[22] CUI Yao-Kui, ZHAO Kai-Guang, FAN Wen-Jie, et al. Retrieving crop fractional cover and LAI based on airborne Lidar data[J]. Journal of Remote Sensing(崔要奎, 赵开广, 范闻捷, 等.机载Lidar数据的农作物覆盖度及LAI反演.遥感学报), 2011, 15(6): 1276-1288.

[23] Solberg S. Mapping gap fraction, LAI and defoliation using various ALS penetration variables[J]. International Journal of Remote Sensing, 2010, 31(5): 1227-1244.

[24] Lefsky M A, Hudak A T, Cohen W B, et al. Geographic variability in LiDAR predictions of forest stand structure in the Pacific Northwest[J]. Remote Sensing of Environment, 2005, 95(4): 532-548.

[25] Koch B. Status and future of laser scanning, synthetic aperture radar and hyperspectral remote sensing data for forest biomass assessment[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2010, 65(6): 581-590.

[26] Zhao K, Popescu S. Lidar-based mapping of leaf area index and its use for validating GLOBCARBON satellite LAI product in a temperate forest of the southern USA[J]. Remote Sensing of Environment, 2009, 113(8): 1628-1645.

[27] PANG Yong, YU Xin-Fang, LI Zeng-Yuan, et al. Waveform length extraction from ICEsat GLAS data and forest application analysis[J]. Scientia Silvae Sinicae(庞勇, 于信芳, 李增元, 等.星载激光雷达波形长度提取与林业应用潜力分析.林业科学), 2006, 42(7): 136-140.

[28] XING Yan-Qiu, WANG Li-Hai. ICESat-GLAS full waveform-based Study on forest canopy height retrieval in sloped area-a case study of forests in Changbai Mountains, Jilin[J]. Geomatics and Information Science of Wuhan University(邢艳秋, 王立海.基于ICESat-GLAS完整波形的坡地森林冠层高度反演研究一一以吉林长白山林区为例.武汉大学学报(信息科学版)), 2009, 34(6): 696-700.

[29] LI Ran, WANG Cheng, SU Guo-Zhong, et al. Development and applications of spaceborne LiDAR[J]. Science & Technology Review(李然, 王成, 苏国中, 等.星载激光雷达的发展与应用.科技导报), 2007, 25(14): 58-63.

[30] DONG Li-Xin, WU Bing-Fang, TANG Shi-Hao. Estimation of forest aboveground biomass by integrating GLAS and ETM data[J]. Acta Scientiarum Naturalium Universitatis Pekinensis(董立新, 吴炳方, 唐世浩.激光雷达GLAS与ETM联合反演森林地上生物量研究.北京大学学报(自然科学版)), 2011, 47(4): 703-710.

[31] Duong V H, Lindenbergh R, Pfeifer N, et al. Single and two epoch analysis of ICESat full waveform data over forested areas[J]. International Journal of Remote Sensing, 2008, 29(5): 1453-1473.

[32] Chen Q. Retrieving vegetation height of forests and woodlands over mountainous areas in the Pacific Coast region using satellite laser altimetry[J]. Remote Sensing of Environment, 2010, 114(7): 1610-1627.

[33] Jiang Z, Huete A R, Chen J. et al. Analysis of NDVI and scaled difference vegetation index retrievals of vegetation fraction[J]. Remote Sensing of Environment, 2006, 101(3): 366-378.

[34] LI Miao-Miao, WU Bing-Fang, YAN Chang-Zhen, et al. Estimation of vegetation fraction in the upper basin of Miyun reservoir by remote sensing[J]. Resources science(李苗苗,吴炳方,颜长珍,等.密云水库上游植被覆盖度的遥感估算.资源科学)2004, 26(4): 153-159.

[35] Pang Y, Lefsky M, Andersen H, et al. Validation of the ICEsat vegetation product using crown-area-weighted mean height derived using crown delineation with discrete return lidar data[J]. Canadian Journal of Remote Sensing, 2008, 34(Suppl.2), 471-484.

[36] Lefsky M A, Keller M, Pang Y, et al. Revised method for forest canopy height estimation from Geoscience laser Altimeter System waveforms[J]. Journal of Applied Remote Sensing, 2007, 1: 1-18.

[37] LUO She-Zhou,WANG Cheng, ZHANG Gui-Bin, et al. Forest leaf area index(LAI) inversion using airborne LiDAR data[J]. Chinese Journal of Geophysics(骆社周, 王成, 张贵宾, 等.机载激光雷达森林叶面积指数反演研究.地球物理学报), 2013, 56(5): 1467-1475.

[38] Lefsky M A, Cohen W B, Acker S A, et al. LiDAR remote sensing of the canopy structure and biophysical properties of Douglas-Fir Western Hemlock Forests[J]. Remote Sensing of Environment, 1999, 70(3): 339-361.

[39] Richardson J J, Moskal L M, Kim S H, et al. Modeling approaches to estimate effective leaf area index from aerial discrete-return LiDAR[J]. Agricultural and Forest Meteorology, 2009, 149(6-7): 1152-1160.

[40] Brovelli M A, Crespib M, Fratarcangeli F, et al. Accuracy assessment of high resolution satellite imagery orientation by leave-one-out method[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2008, 63(4): 427-440.

骆社周, 王成, 习晓环, 聂胜, 夏少波, 万怡平. 星载激光雷达GLAS与TM光学遥感联合反演森林叶面积指数[J]. 红外与毫米波学报, 2015, 34(2): 243. LUO She-Zhou, WANG Cheng, XI Xiao-Huan, NIE Sheng, XIA Shao-Bo, WAN Yi-Ping. Forest leaf area index estimation using combined ICESat/GLAS and optical remote sensing image[J]. Journal of Infrared and Millimeter Waves, 2015, 34(2): 243.

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!