Comparison of Area-Based and Individual Tree-Based Methods for Predicting Plot-Level Forest Attributes
| Autor: | Mikko Vastaranta, Markus Holopainen, Juha Hyyppä, Xiaowei Yu |
|---|---|
| Přispěvatelé: | Department of Forest Sciences, Laboratory of Forest Resources Management and Geo-information Science, Forest Ecology and Management |
| Jazyk: | angličtina |
| Rok vydání: | 2010 |
| Předmět: |
random forests
010504 meteorology & atmospheric sciences Mean squared error Laser scanning Correlation coefficient 411 Agriculture and forestry education 0211 other engineering and technologies area-based method airborne laser scanning 02 engineering and technology 01 natural sciences Statistics lcsh:Science 021101 geological & geomatics engineering 0105 earth and related environmental sciences Remote sensing Mathematics Forest inventory Diameter at breast height 15. Life on land Random forest Tree (data structure) individual tree-based method General Earth and Planetary Sciences lcsh:Q Volume (compression) |
| Zdroj: | Remote Sensing, Vol 2, Iss 6, Pp 1481-1495 (2010) Remote Sensing; Volume 2; Issue 6; Pages: 1481-1495 |
| ISSN: | 2072-4292 |
| Popis: | Approaches to deriving forest information from laser scanner data have generally made use of two methods: the area-based and individual tree-based approaches. In this paper, these two methods were evaluated and compared for their abilities to predict forest attributes at the plot level using the same datasets. Airborne laser scanner data were collected over the Evo forest area, southern Finland, with an averaging point density of 2.6 points/m2. Mean height, mean diameter and volume were predicted from laser-derived features for plots (area-based method) or tree height, diameter at breast height and volume for individual trees (individual tree-based method) using random forests technique. To evaluate and compare the two forest inventory methods, the root-mean-squared error (RMSE) and correlation coefficient (R) between the predicted and observed plot-level values were computed. The results indicated that both area-based method (with an RMSE of 6.42% for mean height, 10.32% for mean diameter and 20.90% for volume) and individual tree-based method (with an RMSE of 5.69% for mean height, 10.77% for mean diameter and 18.55% for volume) produced promising and compatible results. Increase in point density is expected to increase the accuracy of the individual tree-based technique more than that of the area-based technique. |
| Databáze: | OpenAIRE |
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