Forest above Ground Biomass Inversion by Fusing GLAS with Optical Remote Sensing Data
文献类型：期刊论文
| 作者 | Xi, Xiaohuan1; Han, Tingting1; Wang, Cheng1; Luo, Shezhou1; Xia, Shaobo1; Pan, Feifei1 |
| 刊名 | ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
 |
| 出版日期 | 2016 |
| 卷号 | 5期号:4 |
| 关键词 | REMOTE-SENSING DATA LAND-USE CHANGE SPATIOTEMPORAL PATTERNS DRIVING FORCES URBANIZATION GROWTH IMPACT POLICY INFORMATION DYNAMICS |
| 通讯作者 | Wang, C (reprint author), Chinese Acad Sci, Key Lab Digital Earth, Inst Remote Sensing & Digital Earth, 9 Dengzhuang South Rd, Beijing 100094, Peoples R China. |
| 英文摘要 | Forest biomass is an important parameter for quantifying and understanding biological and physical processes on the Earth's surface. Rapid, reliable, and objective estimations of forest biomass are essential to terrestrial ecosystem research. The Geoscience Laser Altimeter System (GLAS) produced substantial scientific data for detecting the vegetation structure at the footprint level. This study combined GLAS data with MODIS/BRDF (Bidirectional Reflectance Distribution Function) and ASTER GDEM data to estimate forest aboveground biomass (AGB) in Xishuangbanna, Yunnan Province, China. The GLAS waveform characteristic parameters were extracted using the wavelet method. The ASTER DEM was used to compute the terrain index for reducing the topographic influence on the GLAS canopy height estimation. A neural network method was applied to assimilate the MODIS BRDF data with the canopy heights for estimating continuous forest heights. Forest leaf area indices (LAIs) were derived from Landsat TM imagery. A series of biomass estimation models were developed and validated using regression analyses between field-estimated biomass, canopy height, and LAI. The GLAS-derived canopy heights in Xishuangbanna correlated well with the field-estimated AGB (R-2 = 0.61, RMSE = 52.79 Mg/ha). Combining the GLAS estimated canopy heights and LAI yielded a stronger correlation with the field-estimated AGB (R-2 = 0.73, RMSE = 38.20 Mg/ha), which indicates that the accuracy of the estimated biomass in complex terrains can be improved significantly by integrating GLAS and optical remote sensing data. |
| 学科主题 | Physical Geography; Remote Sensing |
| 类目[WOS] | Geography, Physical ; Remote Sensing |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000375233100007 |
| 源URL | [http://ir.radi.ac.cn/handle/183411/39391]  |
| 专题 | 遥感与数字地球研究所_SCI/EI期刊论文_期刊论文 |
| 作者单位 | 1.Chinese Acad Sci, Key Lab Digital Earth, Inst Remote Sensing & Digital Earth, 9 Dengzhuang South Rd, Beijing 100094, Peoples R China 2.Univ Chinese Acad Sci, 19 Yuquan Rd, Beijing 100049, Peoples R China 3.Univ N Texas, Dept Geog, Denton, TX 76203 USA |
| 推荐引用方式 GB/T 7714 | Xi, Xiaohuan,Han, Tingting,Wang, Cheng,et al. Forest above Ground Biomass Inversion by Fusing GLAS with Optical Remote Sensing Data[J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,2016,5(4). |
| APA | Xi, Xiaohuan,Han, Tingting,Wang, Cheng,Luo, Shezhou,Xia, Shaobo,&Pan, Feifei.(2016).Forest above Ground Biomass Inversion by Fusing GLAS with Optical Remote Sensing Data.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,5(4). |
| MLA | Xi, Xiaohuan,et al."Forest above Ground Biomass Inversion by Fusing GLAS with Optical Remote Sensing Data".ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 5.4(2016). |
入库方式： OAI收割
来源：遥感与数字地球研究所
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