DOI: 10.1016/j.foreco.2015.10.018
Scopus记录号: 2-s2.0-84944931039
论文题名: Use of WorldView-2 stereo imagery and National Forest Inventory data for wall-to-wall mapping of growing stock
作者: Immitzer M. ; Stepper C. ; Böck S. ; Straub C. ; Atzberger C.
刊名: Forest Ecology and Management
ISSN: 0378-1127
出版年: 2016
卷: 359 起始页码: 232
结束页码: 246
语种: 英语
英文关键词: Angle-count sampling
; Feature selection
; Forest inventory
; Random Forests
; Remote sensing
Scopus关键词: Decision trees
; Feature extraction
; Forestry
; Mapping
; Remote sensing
; Acceptable performance
; Auxiliary information
; Forest enterprise
; Forest inventory
; Mapping applications
; National forest inventories
; Random forests
; Very high resolution
; Stereo image processing
; algorithm
; comparative study
; coniferous forest
; forest inventory
; mixed forest
; performance assessment
; remote sensing
; satellite imagery
; spectral resolution
; stand dynamics
; WorldView
; Bavaria
; Germany
; Coniferophyta
英文摘要: Angle-count sampling (ACS) is an established method in forest mensuration and is implemented in different National Forest Inventories (NFI). However, due to the lack of fixed reference areas of the inventory plots, these ACS-based field data are seldom used as training data for wall-to-wall mapping applications at forest enterprise level. In this paper, we demonstrate an approach to overcome this shortcoming. For a study area in northern Bavaria, Germany, we used ACS-based NFI data for model training to generate wall-to-wall maps of growing stock for broadleaf, conifer and mixed forest stands. Both spectral and height information from the very high resolution WorldView-2 (WV2) satellite were used as auxiliary information and the non-parametric Random Forests (RF) algorithm was chosen as modeling approach. The growing stock predictions were validated using out-of-bag (OOB) samples and further verified at the plot and stand level using additional data. For validation, field plots from a Management Forest Inventory (MFI) and delineated forest stands were used. Compared to stand-level aggregations based on field plots from the MFI, our approach explained 56% of the variability in the growing stock (R2) with a relative RMSE of 15% at the stand level (n=252). As expected, the scatter was higher at the plot-level (n=3973). Nonetheless, the models still achieved acceptable performance measures (R2=0.44; RMSE=34%). © 2015 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/65206
Appears in Collections: 影响、适应和脆弱性
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作者单位: Institute of Surveying, Remote Sensing and Land Information (IVFL), University of Natural Resources and Life Sciences, Vienna (BOKU), Peter-Jordan-Straße 82, Vienna, Austria; Bavarian State Institute of Forestry (LWF), Department of Information Technology, Research Group: Remote Sensing, Hans-Carl-von-Carlowitz-Platz 1, Freising, Germany
Recommended Citation:
Immitzer M.,Stepper C.,Böck S.,et al. Use of WorldView-2 stereo imagery and National Forest Inventory data for wall-to-wall mapping of growing stock[J]. Forest Ecology and Management,2016-01-01,359