Singh Minerva, Evans Damian, Tan Boun Suy, Nin Chan Samean
Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom.
Departments of Asian Studies and Archaeology, University of Sydney, Sydney, Australia.
PLoS One. 2015 Apr 22;10(4):e0121558. doi: 10.1371/journal.pone.0121558. eCollection 2015.
At present, there is very limited information on the ecology, distribution, and structure of Cambodia's tree species to warrant suitable conservation measures. The aim of this study was to assess various methods of analysis of aerial imagery for characterization of the forest mensuration variables (i.e., tree height and crown width) of selected tree species found in the forested region around the temples of Angkor Thom, Cambodia. Object-based image analysis (OBIA) was used (using multiresolution segmentation) to delineate individual tree crowns from very-high-resolution (VHR) aerial imagery and light detection and ranging (LiDAR) data. Crown width and tree height values that were extracted using multiresolution segmentation showed a high level of congruence with field-measured values of the trees (Spearman's rho 0.782 and 0.589, respectively). Individual tree crowns that were delineated from aerial imagery using multiresolution segmentation had a high level of segmentation accuracy (69.22%), whereas tree crowns delineated using watershed segmentation underestimated the field-measured tree crown widths. Both spectral angle mapper (SAM) and maximum likelihood (ML) classifications were applied to the aerial imagery for mapping of selected tree species. The latter was found to be more suitable for tree species classification. Individual tree species were identified with high accuracy. Inclusion of textural information further improved species identification, albeit marginally. Our findings suggest that VHR aerial imagery, in conjunction with OBIA-based segmentation methods (such as multiresolution segmentation) and supervised classification techniques are useful for tree species mapping and for studies of the forest mensuration variables.
目前，关于柬埔寨树木物种的生态、分布和结构的信息非常有限，不足以采取适当的保护措施。本研究的目的是评估各种分析航空影像的方法，以表征柬埔寨吴哥通王城寺庙周边森林地区选定树木物种的森林测量变量（即树高和树冠宽度）。使用基于对象的图像分析（OBIA）（采用多分辨率分割）从超高分辨率（VHR）航空影像和光探测与测距（LiDAR）数据中勾勒出单个树冠。使用多分辨率分割提取的树冠宽度和树高值与实地测量的树木值高度一致（斯皮尔曼等级相关系数分别为0.782和0.589）。使用多分辨率分割从航空影像中勾勒出的单个树冠具有较高的分割精度（69.22%），而使用分水岭分割勾勒出的树冠则低估了实地测量的树冠宽度。光谱角映射器（SAM）和最大似然（ML）分类都应用于航空影像以绘制选定的树木物种。结果发现后者更适合树木物种分类。单个树木物种被高精度识别。纳入纹理信息进一步提高了物种识别率，尽管提高幅度不大。我们的研究结果表明，VHR航空影像与基于OBIA的分割方法（如多分辨率分割）和监督分类技术相结合，对于树木物种绘图和森林测量变量研究很有用。
