期刊論文
| 學年 | 101 |
|---|---|
| 學期 | 2 |
| 出版（發表）日期 | 2013-04-01 |
| 作品名稱 | Spatial statistical analysis of tree deaths using airborne digital imagery |
| 作品名稱（其他語言） | |
| 著者 | Chang, Ya-Mei; Baddeley, Adrian; Wallace, Jeremy; Canci, Michael |
| 單位 | 淡江大學統計學系 |
| 出版者 | Amsterdam: Elsevier BV |
| 著錄名稱、卷期、頁數 | International Journal of Applied Earth Observation and Geoinformation 21, pp.418–426 |
| 摘要 | High resolution digital airborne imagery offers unprecedented opportunities for observation and monitoring of vegetation, providing the potential to identify, locate and track individual vegetation objects over time. Analytical tools are required to quantify relevant information. In this paper, locations of trees over a large area of native woodland vegetation were identified using morphological image analysis techniques. Methods of spatial point process statistics were then applied to estimate the spatially-varying tree death risk, and to show that it is significantly non-uniform. [Tree deaths over the area were detected in our previous work (Wallace et al., 2008).] The study area is a major source of ground water for the city of Perth, and the work was motivated by the need to understand and quantify vegetation changes in the context of water extraction and drying climate. The influence of hydrological variables on tree death risk was investigated using spatial statistics (graphical exploratory methods, spatial point pattern modelling and diagnostics). |
| 關鍵字 | Covariate effect; Kernel estimation; Morphological image analysis; Partial residual; Spatial point pattern; Tree location detection; Point process; Logistic regression; Leverage; Influence |
| 語言 | en_US |
| ISSN | 1872-826X 1569-8432 |
| 期刊性質 | 國外 |
| 收錄於 | SCI |
| 產學合作 | |
| 通訊作者 | Chang, Ya-Mei |
| 審稿制度 | 是 |
| 國別 | NLD |
| 公開徵稿 | |
| 出版型式 | 紙本 電子版 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/92334 ) |