Sentence examples for forest classifications from inspiring English sources

Tensions among the program's social and environmental objectives as well as the combination of formal rigidity and practical flexibility manifest in ambiguous forest classifications and tremendous variation in outcomes.

The random forests-based approach could be also applied to continuous phenotype by modifying random forest classification to random forest regression.

This study investigates the ability of extracted Polarimetric Synthetic Aperture RADAR (PolSAR) features from Compact Polarimetry (CP) data for forest classification.

This library was then used to build a random forest classification model.

Concordance with resection diagnosis, statistical analysis including a random forest classification, and follow-up were recorded.

The classification approach builds on random forest classification with learning data extracted from higher resolution land cover maps.

In this study we demonstrate forest classification approaches using airborne lidar data as inputs to random forest and linear unmixing classification algorithms.

Throughout this paper, we have contrasted unsupervised and supervised classifications as a starting point for how to address forest classification for large forest inventory data sets.

Additionally, we performed a sensitivity analysis to assess the effect of different forest classification thresholds representing different forest definitions on the spatial estimates of the dependent forest area.

Furthermore, a hierarchical clustering method followed by a random forest classification method is proposed to boost the classification performance among confusing classes.

The multi-date NDVI distance measure emerges as very good quantitative surrogate for forest type and is a useful complement to existing forest classification systems.