结合机载LiDAR和LANDSAT ETM+数据的温带森林郁闭度估测
Canopy closure estimation in a temperate forest using airborne LiDAR and LANDSAT ETM+ data
Online published: 2016-03-08
森林郁闭度是森林资源调查中的一个重要因子, 在森林生态系统管理中具有重要作用.研究如何有效地将激光雷达数据应用于森林郁闭度遥感估测具有重大意义.激光雷达数据的应用能够有效地弥补传统地面调查耗时,费力等不足, 不仅可以快速,准确地获取郁闭度遥感估测的模型训练数据和验证数据, 还有助于进一步推广应用于大区域的森林郁闭度反演, 为林业资源调查提供有力的依据.该研究结合激光雷达数据和LANDSAT ETM+数据估测温带森林郁闭度.以高密度机载激光雷达(ALS)点云数据估算的郁闭度作为模型训练数据和验证数据, 通过LANDSAT ETM+影像数据计算得到的8种植被指数作为自变量, 使用多元逐步回归(MSR),随机森林(RF)和Cubist 3种模型, 对内蒙古大兴安岭根河林区森林郁闭度进行估测.经验证, Cubist模型的效果比较好(决定系数R2 = 0.722, 均方根误差RMSE = 0.126, 相对均方根误差rRMSE = 0.209, 估计精度EA = 79.883%).结果表明, 结合激光雷达数据和LANDSAT ETM+影像数据估算温带森林郁闭度非常有潜力.但要将其推广应用于更大区域尺度的森林郁闭度遥感估测, 模型的预测能力还有待进一步改进和提高; 自变量应尝试加入更多种类遥感数据和其他遥感因子参与建模, 例如采用地形因子,高分辨率遥感影像提取纹理特征等, 最大可能地减少光学影像,植被指数,地形阴影等带来的影响, 提高反演精度; 激光雷达数据计算得到的郁闭度的准确性和可靠性还需进一步验证.
张瑞英, 庞勇, 李增元, 包玉海 . 结合机载LiDAR和LANDSAT ETM+数据的温带森林郁闭度估测[J]. 植物生态学报, 2016 , 40(2) : 102 -115 . DOI: 10.17521/cjpe.2014.0366
Aims Forest canopy closure is one of the essential factors in forest survey, and plays an important role in forest ecosystem management. It is of great significance to study how to apply LiDAR (light detection and ranging) data efficiently in remote sensing estimation of forest canopy closure. LiDAR can be used to obtain data fast and accurately and therefore be used as training and validation data to estimate forest canopy closure in large spatial scale. It can compensate for the insufficiency (e.g. labor-intensive, time-consuming) of conventional ground survey, and provide foundations to forest inventory.Methods In this study, we estimated canopy closure of a temperate forest in Genhe forest of Da Hinggan Ling area, Nei Mongol, China, using LiDAR and LANDSAT ETM+ data. Firstly, we calculated the canopy closure from ALS (Airborne Laser Scanning) high density point cloud data. Then, the estimated canopy closure from ALS data was used as training and validation data to modeling and inversion from eight vegetation indices computed from LANDSAT ETM+ data. Three approaches, multi-variable stepwise regression (MSR), random forest (RF) and Cubist, were developed and tested to estimate canopy closure from these vegetation indices, respectively.Important findings The validation results showed that the Cubist model yielded the highest accuracy compared to the other two models (determination coefficient (R2) = 0.722, root mean square error (RMSE) = 0.126, relative root mean square error (rRMSE) = 0.209, estimation accuracy (EA) = 79.883%). The combination of LiDAR data and LANDSAT ETM+ showed great potential to accurately estimate the canopy closure of the temperate forest. However, the model prediction capability needs to be further improved in order to be applied in larger spatial scale. More independent variables from other remotely sensed datasets, e.g. topographic data, texture information from high-resolution imagery, should be added into the model. These variables can help to reduce the influence of optical image, vegetation indices, terrain and shadow and so on. Moreover, the accuracy of the LiDAR-derived canopy closure needs to be further validated in future studies.
| [1] | Birth GS, McVey GR (1968). Measuring the color of growing turf with a reflectance spectrophotometer.Agronomy Journal, 60, 640-643. |
| [2] | Breiman L (2001). Random forests.Machine Learning, 45, 5-32. |
| [3] | Chen C, Zhu YJ, Ju WM (2011). Retrieval of subtropical forest canopy closure from remote sensing by using akaike information criterion and artificial neural network model.Acta Agriculturae Jiangxi, 23(5), 149-153.(in Chinese with English abstract)[陈崇, 朱延钧, 居为民 (2011). 基于赤池信息准则和人工神经网络的亚热带森林郁闭度遥感估算. 江西农业学报, 23(5), 149-153.] |
| [4] | Colombo R, Bellingeri D, Fasolini D, Marino CM (2003). Retrieval of leaf area index in different vegetation types using high resolution satellite data.Remote Sensing of Environment, 86, 120-131. |
| [5] | Coulston JW, Moisen GG, Wilson BT, Finco MV, Cohen WB, Brewer CK (2012). Modeling percent tree canopy cover: A pilot study.Photogrammetric Engineering & Remote Sensing, 78, 715-727. |
| [6] | Deering DW, Rouse JW, Haas RH, Schell JA (1975). Measuring 'Forage production' of grazing units from LANDSAT MSS data. International Symposium on Remote Sensing of Environment, 10th, Ann Arbor, Mich, 1169-1178. |
| [7] | Du WF, Wang FZ, Li Q (1999). Some suggestions for increasing accuracy of canopy closure investigation. Forest resources management, (3), 62-64(in Chinese).[杜文峰, 王凤臻, 李庆 (1999). 提高郁闭度调查精度的几点建议. 林业资源管理, (3), 62-64.] |
| [8] | Du XM, Cai TJ, Ju CY (2008). Estimation of forest canopy closure by using parital least square regression.Chinese Journal of Applied Ecology, 19, 273-277.(in Chinese with English abstract)[杜晓明, 蔡体久, 琚存勇 (2008). 采用偏最小二乘回归方法估测森林郁闭度. 应用生态学报, 19, 273-277.] |
| [9] | Fang KN, Wu JB, Zhu JP, Xie BC (2011). A review of technologies on random forest.Statistics & Information Tribune, 25(3), 32-37.(in Chinese with English abstract)[方匡南, 吴见彬, 朱建平, 谢邦昌 (2011). 随机森林方法研究综述. 统计与信息论坛,25(3), 32-37.] |
| [10] | Fu T, Pang Y, Huang QF, Liu QW, Xu GC (2011). Prediction of subtropical forest parameters using airborne laser scanner.Journal of Remote Sensing, 15, 1092-1104.(in English and Chinese)[付甜, 庞勇, 黄庆丰, 刘清旺, 徐光彩 (2011). 亚热带森林参数的机载激光雷达估测. 遥感学报, 15, 1092-1104.] |
| [11] | Gao YF, Li ZG, Yang ST, Liu XC, Cao Y (2012). Study on canopy density retrieval method from SPOT5.Research of Soil and Water Conservation, 19, 268-270.(in Chinese with English abstract)[高云飞, 李智广, 杨胜天, 刘宪春, 曹勇 (2012). 基于SPOT5影像的郁闭度反演方法. 水土保持研究, 19, 268-270.] |
| [12] | Gleason CJ, Im J (2012). Forest biomass estimation from airborne LiDAR data using machine learning approaches.Remote Sensing of Environment, 125, 80-91. |
| [13] | Hansen MC, Potapov PV, Moore R, Hancher M, Turubanova SA, Tyukavina A, Thau D, Stehman SV, Goetz SJ, Loveland TR, Kommareddy A, Egorov A, Chini L, Justice CO, Townshend JRG (2013). High-resolution global maps of 21st-century forest cover change.Science, 342, 850-853. |
| [14] | Hudak AT, Evans JS, Smith AMS (2009). LiDAR utility for natural resource managers.Remote Sensing, 1, 934-951. |
| [15] | Huete AR (1988). A soil-adjusted vegetation index (SAVI).Remote Sensing of Environment, 25, 295-309. |
| [16] | Korhonen L, Korpela I, Heiskanen J, Maltamo M (2011). Airborne discrete-return LiDAR data in the estimation of vertical canopy cover, angular canopy closure and leaf area index. Remote Sensing of Environment, 115, 1065-1080. |
| [17] | Kuhn M, Witson S, Keefer C, Coulter N (. |
| [18] | Lei CL, Ju CY, Cai TJ, Jing X, Wei XH, Di XY (2012). Estimating canopy closure density and above-ground tree biomass using partial least square methods in Chinese boreal forests.Journal of Forestry Research, 23, 191-196. |
| [19] | Li YN, Zhang BL, Qin SY, Li SY, Huang XR (2008). Review of research and application of forest canopy closure and its measuring methods.World Forestry Research, 21(1), 41-46.(in Chinese with English abstract)[李永宁, 张宾兰, 秦淑英, 李帅英, 黄选瑞 (2008). 郁闭度及其测定方法研究与应用. 世界林业研究,21, 41-46.] |
| [20] | Liu DW, Sun GQ, Pang Y, Cai YL (2006). Estimation of forest closure using LANDSAT TM data.Remote Sensing Information, (1), 41-42.(in Chinese with English abstract)[刘大伟, 孙国清, 庞勇, 蔡玉林 (2006). 利用LANDSAT TM数据对森林郁闭度进行遥感分级估测. 遥感信息, (1), 41-42.] |
| [21] | Moeser D, Roubinek J, Schleppi P, Morsdorf F, Jonas T (2014). Canopy closure, LAI and radiation transfer from Airborne LiDAR synthetic images.Agricultural and Forest Meteorology, 197(19), 158-168. |
| [22] | Nelson R, Krabill W, MacLean G (1984). Determining forest canopy characteristics using airborne laser data.Remote Sensing of Environment, 15, 201-212. |
| [23] | Nelson R, Krabill W, Tonelli J (1988). Estimating forest biomass and volume using airborne laser data.Remote Sensing of Environment, 24, 247-267. |
| [24] | Pang Y, Huang KB, Li ZY, Qin XL, Chen EX (2011). Forest aboveground biomass analysis using remote sensing in the Greater Mekong Subregion. Recourses Science, 33, 1863-1869.(in Chinese with English abstract)[庞勇, 黄克标, 李增元, 覃先林, 陈尔学 (2011). 基于遥感的湄公河次区域森林地上生物量分析 . 资源科学,33, 1863-1869.] |
| [25] | Pang Y, Li ZY (2012). Inversion of biomass components of the temperate forest using airborne LiDAR technology in Xiaoxing'an Mountains, Northeastern of China.Chinese Journal of Plant Ecology, 36, 1095-1105.(in Chinese with English abstract)[庞勇, 李增元 (2012). 基于机载激光雷达的小兴安岭温带森林组分生物量反演 . 植物生态学报,36, 1095-1105.] |
| [26] | Pang Y, Li ZY, Chen EX, Sun GQ (2005). LiDAR remote sensing technology and its application in forestry.Scientia Silvae Sinicae, 41(3), 129-136.(in Chinese with English abstract)[庞勇, 李增元, 陈尔学, 孙国清 (2005). 激光雷达技术及其在林业上的应用. 林业科学,41(3), 129-136.] |
| [27] | Powell SL, Cohen WB, Healey SP, Kennedy RE, Moisen GG, Pierce KB, Ohmann JL (2010). Quantification of live aboveground forest biomass dynamics with LANDSAT time-series and field inventory data: A comparison of empirical modeling approaches.Remote Sensing of Environment, 114, 1053-1068. |
| [28] | Qi J, Chehbouni A, Huete AR, Kerr YH, Sorooshian S (1994). A modified soil adjusted vegetation index.Remote Sensing of Environment, 48, 119-126. |
| [29] | Richardson AJ, Wiegand CL (1977). Distinguishing vegetation from soil background information.Phote Engin & Remote Sense, 43, 1541-1552. |
| [30] | Rosette JAB, North PRJ, Suárez JC (2008). Vegetation height estimates for a mixed temperate forest using satellite laser altimetry.International Journal of Remote Sensing, 29, 1475-1493. |
| [31] | Roujean JL, Breon FM (1995). Estimating PAR absorbed by vegetation from bidirectional reflectance measurements.Remote Sensing of Environment, 51, 375-384. |
| [32] | Rouse JW, Haas RH, Schell JA, Deering DW (1974). Monitoring vegetation systems in Great Plains with ERTS.NASA Special Publication, 351, 309. |
| [33] | Sexton JO, Song XP, Feng M, Noojipady P, Anand A, Huang CQ, Kim D, Collins KM, Channan S, Dimiceli C, Townshend JR (2014). Global, 30-m resolution continuous fields of tree cover: LANDSAT-based rescaling of MODIS vegetation continuous fields with LiDAR-based estimates of error.International Journal of Digital Earth, 6, 427-448. |
| [34] | Soininen A (. |
| [35] | Tan BX, Li ZY, Chen EX, Pang Y, Lei YC (2006). Estimating forest crown closure using hyperion hyperspectral data.Journal of Beijing Forestry University, 28(3), 95-101.(in Chinese with English abstract)[谭炳香, 李增元, 陈尔学, 庞勇, 雷渊才 (2006). Hyperion高光谱数据森林郁闭度定量估测研究 . 北京林业大学学报,28(3), 95-101.] |
| [36] | Wang T (2010). Application on M5 algorithm in sensory evaluation.Microcomputer Information, 26(11-3), 229-231.(in Chinese with English abstract)[王涛 (2010). M5算法在感觉评估中的应用. 微计算机信息, 26(11-3), 229-231.] |
| [37] | Wang YF, Pang Y, Shu QT (2013). Counter-estimation on aboveground biomass of Hevea brasiliensis plantation by remote sensing with random forest algorithm--A case study of Jinghong.Journal of Southwest Forestry University, 33(6), 38-45.(in Chinese with English abstract)[王云飞, 庞勇, 舒清态 (2013). 基于随机森林算法的橡胶林地上生物量遥感反演研究----以景洪市为例 . 西南林业大学学报,33(6), 38-45.] |
| [38] | Wu Y, Zhang DR, Zhang HK, Wu HG (2012). Remote sensing estimation of canopy density combined with texture features.Scientia Silvae Sinicae, 48(2), 48-53.(in Chinese with English abstract)[吴飏, 张登荣, 张汉奎, 武红敢 (2012). 结合图像纹理特征的森林郁闭度遥感估测. 林业科学, 48(2), 48-53.] |
| [39] | Xu D, Peng DL (2013). Estimation of forest canopy closure based on dimidiate pixel model.Journal of Northeast Forestry University, 41(2), 119-122.(in Chinese with English abstract) [徐定, 彭道黎 (2013). 基于像元二分模型的森林郁闭度估测方法. 东北林业大学学报,41(2), 119-122.] |
| [40] | Zeng T, Ju CY, Cai TJ, Liu WB, Yao YF (2010). Selection of parameters for estimation canopy closure density using variable importance of projection criterion.Journal of Beijing Forestry University, 32(6), 37-41.(in Chinese with English abstract)[曾涛, 琚存勇, 蔡体久, 刘文彬, 姚月锋 (2010). 利用变量投影重要性准则筛选郁闭度估测参数 . 北京林业大学学报,32(6), 37-41.] |
| [41] | Zhang J, Li XS, Wu BF (2014). Forest cover estimation based on classification and regression trees of Miyun Reservoir upstream area. Remote Sensing Technology and Application, 29, 394-400.(in Chinese with English abstract)[张瑾, 李晓松, 吴炳方 (2014). 基于分类回归树的密云水库上游森林覆盖度遥感估算. 遥感技术与应用,29, 394-400.] |
| [42] | Zhao YS (2003).Analysis Principle and Method of Remote Sensing Applications. 2nd edn. Science Press,Beijing. 368-380.(in Chinese)[赵英时 (2003). 遥感应用分析原理与方法(第二版). 科学出版社, 北京. 368-380.] |
| [43] | Zheng DM, Zeng WS, Zhi CG, Shi PC (2013). Remote sensing estimation of forest canopy closure in forests of Three Gorges Reservoir Region.Journal of Central South Forestry University, 33(9), 1-4.(in Chinese with English abstract)[郑冬梅, 曾伟生, 智长贵, 施鹏程 (2013). 三峡库区森林郁闭度的遥感定量估测. 中南林业科技大学学报, 33(9), 1-4.] |
| [44] | Zou J, Zhuge XD (2011). Forest canopy closure and the measured methodology.Heilongjiang Science and Technology Information, 35, 290.(in Chinese) [邹杰, 诸葛祥东 (2011). 森林郁闭度及其测定方法 . 黑龙江科技信息,35, 290.] |
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