Spatial scale and pattern dependences of aboveground biomass estimation from satellite images: a case study of the Sierra National Forest, California
文献类型：期刊论文
| 作者 | Tao, Shengli1,2; Guo, Qinghua3 ; Wu, Fangfang; Li, Le4; Wang, Shaopeng5,6; Tang, Zhiyao1,2; Xue, Baolin; Liu, Jin; Fang, Jingyun1,2
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| 刊名 | LANDSCAPE ECOLOGY
 |
| 出版日期 | 2016 |
| 卷号 | 31期号:8页码:1711-1723 |
| 关键词 | LiDAR Above ground biomass (AGB) Landsat Scale Pattern Vegetation index NDVIc |
| ISSN号 | 0921-2973 |
| DOI | 10.1007/s10980-016-0357-y |
| 文献子类 | Article |
| 英文摘要 | Spatial scale and pattern play important roles in forest aboveground biomass (AGB) estimation in remote sensing. Changes in the accuracy of satellite images-estimated forest AGBs against spatial scales and pixel distribution patterns has not been evaluated, because it requires ground-truth AGBs of fine resolution over a large extent, and such data are difficult to obtain using traditional ground surveying methods. We intend to quantify the accuracy of AGB estimation from satellite images on changing spatial scales and varying pixel distribution patterns, in a typical mixed coniferous forest in Sierra Nevada mountains, California. A forest AGB map of a 143 km(2) area was created using small-footprint light detection and ranging. Landsat Thematic Mapper images were chosen as typical examples of satellite images, and resampled to successively coarser resolutions. At each spatial scale, pixels forming random, uniform, and clustered spatial patterns were then sampled. The accuracies of the AGB estimation based on Landsat images associated with varying spatial scales and patterns were finally quantified. The changes in the accuracy of AGB estimation from Landsat images are not monotonic, but increase up to 60-90 m in spatial scale, and then decrease. Random and uniform spatial patterns of pixel distributions yield better accuracy for AGB estimation than clustered spatial patterns. The corrected NDVI (NDVIc) was the best predictor of AGB estimation. A spatial scale of 60-90 m is recommended for forest AGB estimation at the Sierra Nevada mountains using Landsat images and those with similar spectral resolutions. |
| 学科主题 | Ecology ; Geography, Physical ; Geosciences, Multidisciplinary |
| 出版地 | DORDRECHT |
| 电子版国际标准刊号 | 1572-9761 |
| WOS关键词 | LEAF-AREA INDEX ; REMOTE-SENSING DATA ; LANDSAT TM DATA ; INVENTORY DATA ; VOLUME ESTIMATION ; STAND PARAMETERS ; ETM+ DATA ; CARBON ; LIDAR ; LANDSCAPE |
| WOS研究方向 | Science Citation Index Expanded (SCI-EXPANDED) |
| 语种 | 英语 |
| WOS记录号 | WOS:000382906600006 |
| 出版者 | SPRINGER |
| 资助机构 | National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [41471363, 41401505] ; National Key Basic Research Program of ChinaNational Basic Research Program of China [2013CB956604] ; Sierra Nevada Adaptive Management Project (SNMAP) ; Division Of Earth SciencesNational Science Foundation (NSF)NSF - Directorate for Geosciences (GEO) [1339015] Funding Source: National Science Foundation |
| 源URL | [http://ir.ibcas.ac.cn/handle/2S10CLM1/25145]  |
| 专题 | 植被与环境变化国家重点实验室 |
| 作者单位 | 1.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China 2.Peking Univ, Dept Ecol, Coll Environm Sci, Beijing 100871, Peoples R China 3.Peking Univ, Minist Educ, Key Lab Earth Surface Proc, Beijing 100871, Peoples R China 4.Univ Calif Merced, Sierra Nevada Res Inst, Sch Engn, Merced, CA 95343 USA 5.Beijing Normal Univ, State Key Lab Earth Proc & Resource Ecol, Beijing 100875, Peoples R China 6.German Ctr Integrat Biodivers Res iDiv, Leipzig, Germany 7.Univ Jena, Inst Ecol, Jena, Germany |
| 推荐引用方式 GB/T 7714 | Tao, Shengli,Guo, Qinghua,Wu, Fangfang,et al. Spatial scale and pattern dependences of aboveground biomass estimation from satellite images: a case study of the Sierra National Forest, California[J]. LANDSCAPE ECOLOGY,2016,31(8):1711-1723. |
| APA | Tao, Shengli.,Guo, Qinghua.,Wu, Fangfang.,Li, Le.,Wang, Shaopeng.,...&Fang, Jingyun.(2016).Spatial scale and pattern dependences of aboveground biomass estimation from satellite images: a case study of the Sierra National Forest, California.LANDSCAPE ECOLOGY,31(8),1711-1723. |
| MLA | Tao, Shengli,et al."Spatial scale and pattern dependences of aboveground biomass estimation from satellite images: a case study of the Sierra National Forest, California".LANDSCAPE ECOLOGY 31.8(2016):1711-1723. |
入库方式： OAI收割
来源：植物研究所
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